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Universidad del Turabo
Heterogeneous Catalysis Applied To Advanced Oxidation Processes (AOPs) For
Degradation of Organic Pollutants
By
María del Carmen Cotto-Maldonado BS, Biology, University of Puerto Rico
BS, Chemistry, Interamerican University MS, Environmental Health, University of Puerto Rico
Dissertation
Submitted to the School of Science and Technology in partial fulfillment of the requirements for
the degree of Doctor of Philosophy
in Environmental Science
(Chemistry Option)
Gurabo, Puerto Rico
May, 2012
ii
Universidad del Turabo
A dissertation submitted in partial fulfillment of the requirement for the degree of
Doctor of Philosophy
4/24/2012
Heterogeneous Catalysis Applied To Advanced Oxidation Processes (AOPs) For
Degradation of Organic Pollutants
Maria del Carmen Cotto-Maldonado
Approved:
________________________________ Francisco M Marquez Linares, PhD Research Advisor ________________________________ Jose J Duconge, PhD Member ________________________________ Santander Nieto, PhD Member ________________________________ Fred C Schaffner, PhD Associate Dean, Graduates Studies and Research
______________________________ Marlio Paredes, PhD Member ______________________________ Angel L Morales Cruz, PhD Member ______________________________ Teresa Lipsett, PhD Dean
© Copyright 2012 María del Carmen Cotto-Maldonado. All Right Reserved.
iii
Dedications
To my angels in Heaven and Earth…
To my Family
iv
Acknowledgments
One day a friend said to me that sometimes it is necessary to touch the thorn of
the rose to reach the flower and I wish to say thanks to all of those people that helped
and supported me during this journey.
I wish to say thanks to Dr Francisco M Marquez-Linares for your mentoring. I
read in some place that a mentor is someone that not only helps the student to direct the
investigation project, but is part of it. Thanks for your patience, support and help, to
teach me what is a good professor and a human being, and as it is said in Puerto Rico:
“pasar conmigo la zarza y el guayacán”. It has been an honor being your student.
Thanks to the members of my dissertation committee; Dr Jose J Duconge, Dr
Santander Nieto Ramos, Dr Marlio Paredes and Dr Angel L Morales Cruz for your
support and trust during this process.
Thanks to Dr Fred Schaffner, Associated Dean for the Graduate Studies and
Research at the Universidad del Turabo for your guide and advice during all of this time.
Many people collaborated in different forms to develop this research. Thanks to
Dr Carmen Morant, Dr Eduardo Elizalde and Ms Teresa Campo at the Universidad
Autónoma de Madrid for all of your collaboration. I really appreciated all of your help
and support. To Dr Angel Rivera Collazo and Dr. Angel Ojeda at Universidad del
Turabo, for your time.
To my friends Mr Abraham (Kike) E Garcia, Ms Carmen Bonilla Rivera, Ms
Veronica Castro Simmons and Ms Gloria M Herrera for all of your help, thanks to share
with me the best of you during the long hours of laboratory work. Finally, but no less
important, thanks to my friend Ms Karlo Malave-Llamas for the “phone call” that initiated
this journey.
v
Curriculum Vitae
Maria del C Cotto-Maldonado
Education
2004-Present PhD in Environmental Science, University of Turabo, Gurabo,
Puerto Rico.
2002-2006 BS in Chemistry, Inter American, Metropolitan Campus, Río
Piedras, Puerto Rico
1994-1997 MS in Environmental Health, University of Puerto Rico, Medical
Science Campus, Río Piedras, Puerto Rico
1987-1992 BS in Biology, University of Puerto Rico, Río Piedras Campus,
Río Piedras, Puerto Rico
Academic Honors, Awards and Achievements
2011 Scientific Authors Award, Vice-Chancellor Office of Academic Affairs,
University of Turabo, Gurabo Campus, Gurabo, Puerto Rico
2010 Minigrant Award, Associate Dean Office of Graduate Studies, School of
Science and Technology, University of Turabo, Gurabo Campus, Gurabo,
Puerto Rico
2009 Scientific Authors Award, Vice-Chancellor Office of Academic Affairs,
University of Turabo, Gurabo Campus, Gurabo, Puerto Rico
Minigrant Awards, Associate Dean Office of Graduate Studies, School of
Science and Technology, University of Turabo, Gurabo Campus, Gurabo,
Puerto Rico
vi
2008 Minigrant Award, Dean Office of Graduate Studies, School of Science
and Technology, University of Turabo, Gurabo Campus, Gurabo, Puerto
Rico
Scientific Authors Awards, Vice-Chancellor Office of Academic Affair,
University of Turabo, Gurabo Campus, Gurabo, Puerto Rico
2006 Graduate with Honors of the InterAmerican University, Metropolitan
Campus
2005 Founder Member of the Environmental Science Doctoral Student
Association at University of Turabo
2003 Second Place in the Inorganic Advance Chemistry Competitions 2003
(Olimpiadas de Química 2003), InterAmerican University, Metropolitan
Campus
1995 Founder Member of the Environmental Health Student Association at the
University of Puerto Rico, Medical Science Campus
1993 Graduate with Honors (Cum Laude) of the University of Puerto Rico, Río
Piedras Campus
Scientific Meetings
12. Cotto M, Campo T, Elizalde E, Morant C, Marquez F. 2011. Hydrothermal
Synthesis and Photocatalytic Activity of Titanium Oxide Nanowires Poster
session presented at: 43rd IUPAC World Chemistry Congress, August 2011. San
Juan PR.
11. Cotto M, Masa A, Garcia A, Duconge J, Campo T, Elizalde E, Morant C,
Márquez F.2011. ZnCd Based Photocatalysts for Hydrogen Production from
Water under Visible-UV Light. Poster session presented at: 43rd IUPAC World
Chemistry Congress, August 2011. San Juan PR.
vii
10. Herrera GM, Campo T, Cotto M, Sanz JM, Elizalde E, Morant C, Marquez F.
2011. Synthesis and Characterization of Hollow Magnetite Microspheres. Poster
session presented at: 43rd IUPAC World Chemistry Congress, August 2011. San
Juan PR.
9. Herrera GM, Campo T, Cotto M, Sanz JM, Elizalde E, Morant C, Marquez F.
2011. Preparation of Hollow Magnetite Microspheres and their Applications as
Drugs Carriers. Poster session presented at: 43rd IUPAC World Chemistry
Congress, August 2011. San Juan PR.
8. Campo T, Marquez F, Cotto M, Elizalde E, Morant C. 2011. Silicon Nanowires
grown from Silicon Substrates for Ion-Li Batteries Applications. Poster session
presented at: 43rd IUPAC World Chemistry Congress, August 2011. San Juan
PR.
7. Duconge J, Bonilla C, Garcia A, Herrera GM, Cotto M, Campo T, Elizalde E,
Morant C Marquez F. 2012. Synthesis and Characterization of Copper Oxide
Nanowires. Poster session presented at: 43rd IUPAC World Chemistry
Congress, August 2011. San Juan PR.
6. Duconge J, Bonilla C, Cotto M, Herrera GM, Campo T, Elizalde E, Morant C,
Marquez F. 2012. Hydrothermal Synthesis of Crystalline CuO Nanorods. Poster
session presented at: 43rd IUPAC World Chemistry Congress, August 2011. San
Juan PR.
5. Herrera GM, Felix H, Campo T, Cotto M, Sanz JM, Elizalde E, Morant C,
Hernández-Rivera S, Márquez F. 2012. Synthesis and characterization of Au
coated TiO2 nanowires as ERS solid substrates. Poster session presented at:
43rd IUPAC World Chemistry Congress, August 2011. San Juan PR.
viii
4. Cotto-Maldonado MC, Roque-Malherbe R, Nieto S, Duconge J. 2008. Phenol
Decomposition by Mechanical Activation of Rutile. Poster session presented at:
28th Congreso Latinoamericano de Quimica. 2008. San Juan, Puerto Rico.
3. Cotto MC, Malave K. 2003. Environmental Health Risk Communication for
Hispanic Communities. Presented at: 2003 ATSDR Partners in Public Health
Meeting. March 3-5 2003, Atlanta, Georgia.
2. Cotto MC. Risk Communication. Presented at: University of Puerto Rico. [Rio
Piedras (PR)]:University of Puerto Rico, Medical Science Campus.
1. Marcantoni C, Cotto MC. 1998. Growth of Microbial Population in the
Schmutzdecke of a Slow Sand Filter and its Relationship with Treated Water.
Poster session presented at: AWWA Annual Conference June 21-25 1998,
Dallas, Texas.
Scientific Papers
10. Cotto M, Duconge J, Campo T, Elizalde E, Morant C, Márquez F. Hydrothermal
Synthesis and Catalytic Activity of TiO2 nanowires. (To be submitted to J Catal).
9. Marquez F, Masa A, Cotto M, Bonilla C, Garcia A, Duconge J, Campo T, Elizalde
E, Morant C. Photocatalytic Hydrogen Production by Water Splitting using
ZnCdFeS nanoparticles under UV-Vis Light Irradiation. (To be submitted to Int J
Hydrogen Energy).
8. Marquez F, Cotto M, Campo T, Elizalde E, Morant C. Photocatalytic degradation
of Rhodamine B on different nanostructured catalyst. (To be submitted to Soft
Nanoscience Lett).
7. Marquez F, Cotto M, Bonilla C, Duconge J, Campo T, Elizalde E, Morant C. High
Catalytic Activity of CuO Nanorods Synthesized by an Hydrothermal Approach.
(Submitted to J Catal)
ix
6. Marquez FM, Herrera GM, Campo T, Cotto MC, Duconge J, Sanz JM, Elizalde E,
Perales O, Morant C. 2012. Preparation of hollow magnetite microspheres and
their applications as drug carriers. Nanoscale Res Lett 7: 210.
5. Marquez F, Campo T, Cotto M, Polanco R, Roque R, Fierro P, Sanz JM, Elizalde
E, Morant C. 2011. Synthesis and Characterization of Monodisperse Magnetite
Hollow Microsphere. Soft Nanoscience Lett: 25-32.
4. Malave K, Cotto-Maldonado MC. 2010. Community environmental risk in
developing countries. Environmental and Human Health: Risk Management in
Developing Countries. Taylor and Francis Group.
3. Cotto MC, Emiliano A, Nieto S, Duconge J, Roque-Malherbe R. 2009.
Degradation of Phenol by Mechanical Activation of a Rutile Catalyst. J Colloid
Interf Sci. 339: 133-139.
2. Marcantoni C, Cotto MC. 1998. Growth of Microbial Population in the
Schmutzdecke of a Slow Sand Filter and its Relationship with Treated Water.
Proceedings of the AWWA Annual Conference. June 21-25 1998, Dallas
(Texas). Vol. C, p. 751-776.
1. Marcantoni C, Maldonado E, Cotto, MC. 1996. Determinación de las densidades
poblacionales microbiológicas existentes en el schmutzdecke de un filtro de
arena lento y su relación con la calidad del efluente [master’s thesis].[Rio Piedras
(PR)]:University of Puerto Rico, Medical Science Campus.
x
Table of Contents
Page
List of Tables ................................................................................................................ xiv
List of Figures ................................................................................................................ xv
List of Appendices ........................................................................................................xxii
Abstract ....................................................................................................................... xxiii
Resumen .....................................................................................................................xxiv
Chapter One. Introduction ............................................................................................... 1
ChapterTwo. Experimental Techniques ....................................................................... 276
2.01. X-Ray Diffraction (XRD) ................................................................................. 276
2.02. Magnetic Susceptibility ..................................................................................... 29
2.03. Thermogravimetric Analysis (TGA) .................................................................. 32
2.04. Specific Surface Area (BET) ............................................................................ 34
2.05. Raman Spectroscopy ....................................................................................... 36
2.06. X-Ray Photoelectron Spectroscopy (XPS) ....................................................... 40
2.07. Field Emission Scanning Microscopy (FE-SEM)............................................... 42
2.08. Total Organic Carbon Analysis ......................................................................... 45
2.09. UV-Visible Spectroscopy .................................................................................. 46
2.10. Fluorescence Spectroscopy .............................................................................. 49
Chapter Three. Synthesis Procedures ........................................................................... 52
3.1. Synthesis of Titanium Oxide Nanowires ............................................................. 52
3.2. Synthesis of Zinc Oxide ..................................................................................... 53
3.3. Synthesis of Titanium Oxide@Multiwalled Carbon Nanotubes ........................... 53
3.3.1. Carbon Nanotubes Modification ................................................................... 53
3.3.2. Synthesis and Incorporation of the Titanium Oxide on the MWCNT ............. 54
3.4. Synthesis of Capped Magnetite Nanoparticles ................................................... 54
3.5. Synthesis of Iron Oxide Nanowires .................................................................... 55
Chapter Four.Material Characterization .......................................................... ………….57
4.1. Photocatalysis .................................................................................................... 57
xi
Page
4.1.1. Titanium Oxide (TiO2, Rutile Phase) ............................................................ 57
4.1.2. Titanium Oxide (TiO2, Anatase Phase) ........................................................ 61
4.1.3. Titanium Oxide Nanowires ........................................................................... 65
4.1.4. Titanium Oxide @Multiwalled Carbon Nanotubes ........................................ 68
4.1.5. Zinc Oxide ................................................................................................... 73
4.2. Fenton Catalysts ................................................................................................ 76
4.2.1. Iron Oxide Nanowires (Fe2O3NWs) .............................................................. 76
4.2.2. Capped Magnetite Nanoparticles (Fe3O4) .................................................... 81
4.2.3. Ferrous Chloride (FeCl2) .............................................................................. 86
4.2.4. Copper Oxide (CuO) .................................................................................... 88
Chapter Five. Results and Discussion ........................................................................... 91
5.1. Defining the Experimental Parameters ............................................................... 91
5.1.1. Effects of the Concentration ......................................................................... 91
5.1.2. Effects of the pH .......................................................................................... 94
5.1.3. Effects of Temperature ................................................................................ 95
5.2. Photochemical degradation ................................................................................ 96
5.2.1. Description of the Photocatalytic System ................................................... 100
5.3. Sono-Fenton Process ...................................................................................... 117
5.3.1. Description of the Sono-Fenton System ..................................................... 117
5.4. Photo-Fenton Process ..................................................................................... 124
5.4.1. Description of the Photo-Fenton System .................................................... 124
5.5. Statistical analysis ............................................................................................ 129
Chapter Six. Conclusion .............................................................................................. 132
Literature Cited ............................................................................................................ 134
Appendix One. Dyes Solutions .................................................................................... 151
Appendix Two. Photocatalytic Process ........................................................................ 152
Appendix Three. Sono-Fenton Process ....................................................................... 182
xii
Appendix Four. Photo-Fenton Process……………………………………………………..206
xiii
List of Tables
Page
Table 1.1. Characteristics of the most important dyes classes 19
Table 5.1. Basic information of the studied organic compounds 103
Table 5.2. Degradation percent of dye solutions during the
Photocatalytic Process 107
Table 5.3. Kinetic reaction rates and R2 values for the degradation
reaction of the organic compounds during the
photocatalytic process 109
Table 5.4. Kinetic reaction rates and R2 values for de degradation
reaction of the organic compounds during the sono-Fenton
process 120
Table 5.5. Kinetic reaction rates and R2 values for de degradation
reaction of the organic compunds during the sono-Fenton
process 122
Table 5.6. Degradation percent of dye solutions during the Photo-
Fenton Process 127
Table 5.7. Kinetic reaction rates and R2 values for the degradation
reaction of the organic compounds during the photo-
Fenton process 129
xiv
List of Figures
Page
Figure 1.01. Schematic diagram for the photoexcitation process in a
semiconductor via photon irradiation 8
Figure 1.02. Molecular structure of Methylene blue 20
Figure 1.03. Molecular structure of Rhodamine B 21
Figure 1.04. Molecular structure of the Methyl Orange 22
Figure 1.05. Molecular structure of Crystal Violet and the molecular
structure of Methyl Violet 23
Figure 1.06. Molecular structure of p-amino benzoic acid (pABA) 24
Figure 2.01. Schematic representation of the diffraction process from
atoms in a crystalline lattice 28
Figure 2.02. Images of the PANalytical XRD system 29
Figure 2.03. Typical hysteresis loop of capped magnetite nanoparticles 30
Figure 2.04. VSM components 31
Figure 2.05. Lake Shore-7400 Vibrating Sample Magnetometer 32
Figure 2.06. Schematic illustration of the TGA instrument 33
Figure 2.07. Thermal Gravimetric Analysis (TGA), TA instrument, Q500 34
Figure 2.08. Micromeritics ASAP 2020 Accelerated Surface Area
and Porosimetry 36
Figure 2.09. Raman vibrational and scattering modes 38
Figure 2.10. Image of the micro Raman scattering equipment 39
Figure 2.11. Perkin-Elmer PHI 3027 spectrometer and VG Escalab 210
Spectrometer 42
Figure 2.12. Main components of a FE-SEM instrument 44
xv
Figure 2.13. FE-SEM JEOL JM-6400 microscope 44
Figure 2.14. TOC analyzer (Tekmar Dohmann Phoenix 8000 UV-
Persulfate TOC Analyzer 46
Figure 2.15. Image of the Leco CHNS 932 analyzer and scheme of its
different components parts 46
Figure 2.16. Representation of the different electronic transitions
generated during the absorption process under UV-Visible
irradiation 48
Figure 2.17. Image of the fluorescence spectrophotometer Varian Cary
Eclipse and a diagram of the fluorescence spectrometer 51
Figure 3.01. Image of the CVD system and scheme of the CVD system
and thermal treatment used for the synthesis of the Fe2O3
nanowires 56
Figure 4.01. FE-SEM image of the titanium oxide (rutile phase) at a
magnification of 5000x 58
Figure 4.02. TGA scan of titanium oxide (rutile phase) 58
Figure 4.03. Raman spectrum of TiO2 sample (rutile phase) 59
Figure 4.04. XPS spectrum corresponding to the O1s region of the TiO2
catalyst (rutile phase) 60
Figure 4.05. XPS spectrum corresponding to the Ti2p region of the TiO2
catalyst (rutile phase) 60
Figure 4.06. XRD diffraction pattern for TiO2-Anatase, TiO2-Rutile,
TiO2@MWCNTs and TiO2NWs 61
Figure 4.07. FE-SEM image of the titanium oxide (anatese phase) at a
magnification of 50 000x 62
Figure 4.08. TGA scan of titanium oxide (anatase phase) 62
xvi
Figure 4.09. Raman spectrum of titanium oxide catalyst (anatase
phase) 63
Figure 4.10. XPS spectrum of Ti2p peak on titanium oxide (anatase
phase) 64
Figure 4.11. XPS spectrum of TiO2 showing the O1s transition
(anatase phase) 64
Figure 4.12. FE-SEM image of the as-synthesized TiO2NWs at different
Magnifications 65
Figure 4.13. TGA analysis of the as-synthesized TiO2NWs 66
Figure 4.14. Raman spectrum of the as-synthesized TiO2NWs 67
Figure 4.15. XPS spectrum of Ti2p region of the as-synthesized TiO2NWs 67
Figure 4.16. XPS spectrum of O1s region of the as-synthesized TiO2NWs 68
Figure 4.17. FE-SEM image of the as-synthesized TiO2@MWCNTs 69
Figure 4.18. TGA analysis of the as-synthesized TiO2@MWCNTs 70
Figure 4.19. Raman spectrum of the as-synthesized TiO2@MWCNTs 71
Figure 4.20. XPS spectrum corresponding to the C1s region of the as-
synthesized TiO2@MWCNTs catalyst 72
Figure 4.21. XPS spectrum corresponding to the Ti2p region of the as-
synthesized TiO2@MWCNTs catalyst 72
Figure 4.22. XPS spectrum corresponding to the O1s region of the as-
synthesized TiO2@MWCNTs catalyst 73
Figure 4.23. FE-SEM image of the as-synthesized ZnO particles at
different magnification 74
Figure 4.24. TG curve of the as-synthesized ZnO particles 75
Figure 4.25. Raman spectrum of the as-synthesized ZnO particles 75
Figure 4.26. XRD diffraction pattern of the as-synthesized ZnO particles 76
xvii
Figure 4.27. FE-SEM image of the as- as-synthesized iron oxide
nanowires (Fe2O3NWs) at different magnifications 77
Figure 4.28. TG curve of raw Fe2O3NWs 77
Figure 4.29. XPS spectrum corresponding to the Fe2p region of the as-
synthesized Fe2O3NWs 78
Figure 4.30. XPS spectrum corresponding to the O1s region of the as-
synthesized Fe2O3NWs 79
Figure 4.31. Raman spectrum of the as-synthesized Fe2O3NWs particles 79
Figure 4.32. Magnetic susceptibility of the as-synthesized Fe2O3NWs,
measured at room temperature 80
Figure 4.33. XRD diffraction patterns of Fe2O3NWs synthesized at
600 °C and 700 °C at atmspheric pressure and in flowing
Oxygen 81
Figure 4.34. FE-SEM images of the as-synthesized capped magnetite
nanoparticles (Fe3O4) at different magnifications 83
Figure 4.35. XPS spectrum corresponding to the Fe2p region, of the as-
synthesized capped magnetite nanoparticles (Fe3O4) 84
Figure 4.36. XPS spectrum corresponding to the O1s region, of the as-
synthesized capped magnetite nanoparticles (Fe3O4) 84
Figure 4.37. Raman spectrum of the as-synthesized capped magnetite
Nanoparticles 85
Figure 4.38. Temperature effect on the magnetite properties of the
magnetite at different temperatures 85
Figure 4.39. TG curve of the ferrous chloride 86
Figure 4.40. XPS spectrum corresponding to the Cl2p region, of the
FeCl2 catalyst 87
xviii
Figure 4.41. XPS spectrum corresponding to the Fe2p region, of the
FeCl2 catalyst 87
Figure 4.42. XRD diffraction pattern of the FeCl2 catalyst 88
Figure 4.43. FE-SEM images of CuO at different magnification 89
Figure 4.44. TG curve of the cupric oxide catalyst 89
Figure 4.45. XRD diffraction pattern of the CuO catalyst 90
Figure 5.01. Effects of the concentration of anatase on the
photodegradation process of RhB 92
Figure 5.02. Effects of the catalyst and hydrogen peroxide on the
photodegradation process of RhB 93
Figure 5.03. Effects of the pH of the reaction mixture on the
photodegradation process of RhB 94
Figure 5.04. Effects of the temperature of the solution on the
photodegradation process of RhB 96
Figure 5.05. Experimental setup used during this research, without
irradiation and during the irradiation 101
Figure 5.06. Dye solution used during the investigation 101
Figure 5.07. Methylene blue visible absorption spectrum 102
Figure 5.08. Visible absorbance abd fluorescence spectrum of MB in
presence of rutile 104
Figure 5.09. Possible degradation intermediates of RhB during the
photocatalytic process 105
Figure 5.10. Graphic of the percent of degradation of the different
organic compounds by the Photocatalytic process 107
Figure 5.11. Regression curve of the Methylene Blue (MB) with rutile
under photochemical process 108
xix
Figure 5.12. Possible processes involved in the degradation reaction
using TiO2 as catalyst 112
Figure 5.13. Absorption spectrum corresponding to the degradation of
Rhodamine B by TiO2@MWCNTs under photochemical
Process 113
Figure 5.14. Four principal by-products of the MO degradation process 115
Figure 5.15. Possible intermediates of degradation of MO during the
photocatalytic degradation 116
Figure 5.16. Schematic diagram of the sonochemical generation of the
degradation radicals 118
Figure 5.17. Degradation curves of RhB; UV-vis absorbance , TOC,
fluorescence and dye solution before and after the sono-
Fenton degradation process 119
Figure 5.18. Graphic of percent of degradation of the organic
compounds by the Sono-Fenton process 120
Figure 5.19. Regression curve of the Methylene Blue (MB) with Fe3O4
under sono-Fenton process 121
Figure 5.20. Scheme of the different areas of interest during the
sonochemical process 124
Figure 5.21. Degradation curves of MO; UV-vis absorbance, TOC,
fluorescence and dye solution before and after the photo-
Fenton degradation process 126
Figure 5.22. Graphic of percent of degradation of the organic
compounds by the Photo-Fenton process 128
Figure 5.23. Regression curve of the Methylene Blue (MB) with Fe3O4
during photo-Fenton degradation process 128
xx
Figure 5.24. Graphic of comparison between the Photocatalytic process
and the Photo-Fenton process 130
Figure 5.25. Graphic of comparison between the Photocatalytic process
and the Sono-Fenton process for MB, RhB and MO 131
xxi
List of Appendices
Page
Appendix One Dyes Solutions 151
Appendix Two Photocatalytic Process 152
Appendix Three Sono-Fenton Process 182
Appendix Four Photo-Fenton Process 206
xxii
Abstract
María del Carmen Cotto-Maldonado (PhD, Environmental Science)
Heterogeneous Catalysis Applied To Advanced Oxidation Processes (AOPs) For
Degradation of Organic Pollutants (April/2012)
Abstract of a doctoral dissertation at the Universidad del Turabo
Dissertation supervised by Professor Francisco M Marquez Linares
No. of pages in text 260
Water is an essencial resource for humankind and biomes. Actually, the
pollution of the water resources, specially the contamination of the fresh water is great
concern in our society. Develop of new and more efficient method for degradation of
pollutant in water increase the research in this area, especially in the AOPs. During this
investigation a comparison between different AOPs methods (photocatalysis, sono-
Fenton and photo-Fenton) to determine the most efficient process of them was done. To
reach our goal, different catalysts, namely TiO2 nanowires, TiO2@CNTs, ZnO
nanoparticles, Fe2O3 nanowires and magnetite nanoparticles were synthesized and
characterized by different techniques including FE-SEM, TGA, specific surface area
(BET), XRD, Raman spectroscopy, XPS and magnetic susceptibility. Commercial and
synthesized catalysts were used in photocatalysis, sono-Fenton and photo-Fenton
processes for the degradation of model organic compounds (Methylene Blue,
Rhodamine B, Methyl Orange, Gential Violet, Methyl Violet and p-aminobenzoic acid).
According with the experimental results, no significant differences were observed
between the photo-Fenton and sono-Fenton processes when the same catalysts were
used. For the photocatalytic process, the more effective catalyst was TiO2NWs and for
the sono-Fenton and photo-Fenton processes, the more effective catalyst was FeCl2.
xxiii
Resumen
María del Carmen Cotto Maldonado (PhD, Environmental Science)
Heterogeneous Catalysis Applied To Advanced Oxidation Processes (AOPs) For
Degradation of Organic Pollutants (Abril/2012)
Resumen de disertación doctoral en Universidad del Turabo
Disertación fue supervisada por el Profesor Francisco M Marquez Linares
No. de páginas 260
El agua es un recurso esencial para la vida humana y los biomas. Actualmente,
la contaminación de los recursos acuáticos, especialmente de la contaminación de los
abastos de agua potable ha creado una gran preocupación en nuestra sociedad. El
desarrollo de nuevos y más eficientes métodos para la degradación de los
contaminantes en agua se ha incrementado, especialmente en la utilización de los
procesos de oxidación avanzada (AOPs, por sus siglas en ingles). Durante esta
investigación se llevó a cabo una comparación de la eficiencia entre diferentes procesos
de “AOPs” (fotocatálisis, sono-Fenton y foto-Fenton). Para alcanzar la meta de nuestra
investigación se han sintetizado diferentes catalizadores como nanohilos de TiO2, TiO2
depositado sobre nanotubos de carbono, partículas de ZnO, nanohilos de Fe2O3 y
nanopartículas de magnetita. Estos materiales han sido caracterizados mediante
diferentes técnicas entre las que se incluyen microscopia electrónica de barrido con
emisión de campo (FE-SEM, por sus siglas en inglés) análisis termogravimétrico,
determinación de área específica (BET), difracción de rayos X (DRX), espectroscopia
Raman, espectroscopia fotoelectrónica de rayos X (XPS, por sus siglas en inglés) y
susceptibilidad magnética. Estos catalizadores de síntesis y otros comerciales fueron
utilizados en los procesos de degradación estudiados (fotocatálisis, sono-Fenton y foto-
xxiv
Fenton). El Azul de metileno, Rodamina B, Naranja de metilo, Cristal Violeta y ácido p-
amino benzoico fueron los compuestos orgánicos modelos utilizados durante los
procesos de degradación. Según los resultados experimentales, no se observan
diferencias significativas entre los procesos sono-Fenton y foto-Fenton cuando los
mismos catalizadores son utilizados. En el proceso fotocatalítico de degradación, el
fotocatalizador que presentó mayor eficiencia fue el correspondiente a nanohilos de
óxido de titanio. Durante los procesos sono-Fenton y foto-Fenton, el catalizador más
activo en la degradación de los compuestos estudiados fue el FeCl2.
1
Chapter One
Introduction
Water is an important resource in our society. Less than a 0.7% of the total of
water in the Planet is fresh water and only 0.01% is accessible to be used (Garriga I
Cabo 2007). This resource is essential for sustaining the basic human functions as
health, agriculture and the integrity of the biomes (Garriga I Cabo 2007, UNEP et al.
2002). One of the human basic rights, especially children, is access to safe water for
drinking and other uses (UNEP et al. 2002) because biological and chemical
contaminants compromise the water quality in the world. Today, some of the most
discussed issues around the world are the sanitation, soil and water chemical pollution,
air pollution, the degradation of water sources and natural resources (Garriga I Cabo
2007, UNEP et al. 2002). Organic, inorganic, bionutrients and microorganisms are some
of the most common contaminants in water (Garriga I Cabo 2007). One of the facts
mentioned by UNEP et al. (2002) said:
“at the dawn of the 21st Century, about 18 per cent of the
world’s population do not have access to safe drinking
water, and nearly 40 per cent lack adequate sanitation”.
In many regions of the world, water is a scarce resource, and in these places the reuse
of the water is a relevant issue (Marin et al. 2007).
The production and use of synthetic chemical products have experienced an
important increase during the last century. These products imply a challenge to the
environment (UNEP et al. 2002), due to the fact that the environment does not have the
2
required mechanisms to promote the degradation, and these contaminants can become
highly toxic to many species including the human being. Humankind is responsible for
the release of the pollutants to the environment in many of their normal activities like
industrial processes, wastewater discharges, excessive use of pesticides, fertilizers, etc.
Many contaminants could move through the trophic chains and be accumulated in the
organisms (UNEP et al. 2002). This situation highlights the importance of more
epidemiological studies to understand the effect (synergistic or antagonist) of the
population exposure to environmental contaminants.
According to the OAS (2010), one of the objectives of the “Sustainable
development of the Americas” is the protection of the public health by keeping the
drinking water free of microorganisms, heavy metals and hazardous pollutants and trying
to strengthen the development and implementing laws, regulations and policies.
Organizations in different countries as “Alianza para el Desarrollo Sostenible” (ALIDES),
“Organización Panamericana de la Salud” (OPS), the “Comité Coordinador de
Instituciones de Agua Potable y Saneamiento de Centroamerica”, the Environmental
Protection Agency (EPA), etc. work together to establish laws and regulations to protect
the environment (OAS 2010). Examples of countries that are working with to achieve a
better quality of water and environment protection are Belize, Costa Rica, Guatemala,
etc. (OAS 2010). Chile is another example of a Latin American country that presents a
relevant interest in the protection of the water sources and the environment (UNEP
[undated]). According to the report of the UNEP et al. (2002), in 2002 the 30% of the
industrial effluents were discharged into sewage systems without the appropriate
discharge treatments.
Another example of the strong interest of the countries for the conservation and
management of the water resources was the UNEP Conference entitled “Greening
Water Law in Africa: Managing Freshwater Resources for People and the Environment”
3
held in Kampala, Uganda. The main objective of this meeting was the analysis of the
socio-economic infrastructure with the environmental protection and conservation of the
resources in the African continent (UNEP 2010).
The Clean Water Act (CWA) of 1977 described in the 33 USC §1251 et seq.
establishes all the basis and regulations to avoid the pollution of the waters of the United
States of America regulating the discharges. The CWA enables the Environmental
Protection Agency to implement the regulatory standards for water quality and
discharges through the National Pollutant Discharge Elimination System (NPDES).
However, the NPDES only regulates specific discharges, including industrial and
treatment plant effluents. Non specific discharges, as for instance the septic systems,
are not regulated by NPDES. In Puerto Rico, Environmental Quality Board (EQB)
establishes some discharge regulations to protect the quality of the waters according
with the uses.
The EPA has proposed a “Strategic Plan” for the fiscal years of 2011 to 2012 to
protect and restore the waters in the USA, and specifically to protect the human and
aquatic ecosystem health (USEPA [undated]). In the “Notice of Final 2010 Effluent
Guidelines Program Plan”, the effluents guidelines and pretreatment standards are
evaluated to maintain the integrity of the water sources (FR 2010). Meanwhile, Best
Available Technology Economically Achievable (BAT) are promulgates for reach the
EPAs goal as suggest in the Federal Register as a form to increase the effectivity of the
treatments processes.
The United States Geological Survey (USGS) as part of the US Department of
the Interior is developing different studies to determine the level of contamination of
different streams in the US. A survey from 1999 to 2000 of the USGS (Barnes et al.
2002a, 2002b) has demonstrated the presence of 82 of the 95 organic wastewater
contaminants analyzed. A total of 80% of the samples taken from 30 of the states were
4
positive for the presence of at least 1 of the contaminants including antibiotics,
hormones, detergents, plasticizers, disinfectants, insecticides, fire retarded (using during
fibers synthesis), and antioxidants. Most commonly detected products are steroids, non-
prescript drugs and insect repellents.
Emerging Contaminants Project of the USGS (USGS 2011a) has the goal of
provide information (analytical methods, environmental occurrence, pathways and
ecological effects) of the contaminants that are not monitored due to the lack of
regulation but have the potential to reach the environment in significant amounts, having
adverse effects on the biosphere and specifically in humans. Different studies
developed in New York and New Jersey were undertaken to determine the occurrence
and concentration of emerging contaminants after treatment processes (USGS 2008).
The coordinator of the USGS Toxic Substances Hydrology Program, Herb Buxton,
declared that:
“The wastewater treatments are not really designed to remove
those trace-organic chemicals”
and these contaminants are normally released to the environment (USGS 2011b).
Among the emerging contaminants found in the environment, the group of
cosmetic and personal care products (PPCs) deserves special attention. The UV filters
is one of the products commonly used and several studies demonstrate the presence in
different water samples. The UV filters also possess potential risks derived from the
presence of single or multiple aromatic groups in their structures and these substances
are normally used in sunscreen lotions and many cosmetics. Comparison studies in
Switzerland, between river and lake fish as Salmo trutta fario, Coregonus spp and R
rutilus demonstrated the presence of UV-filters in muscle tissue of the fishes (Buser et
al. 2006). Another study of Schlumpf et al. (2008) demonstrated the presence of
sunscreen compounds from analyses of human milk.
5
These results demonstrate the need for efficient water treatment technologies
able to remove or degrade hazardous contaminants present in the effluents, making the
water resources both safe and potable to human consumption. For example, to maintain
the aesthetic and diminish the environmental impact of industrial effluents is necessary
the discoloration of the wastewaters (Hussein et al. 2008). Currently, the most used
treatment methods for the removal of contaminants from water are the reverse osmosis,
ion-exchange technology, precipitation of materials and adsorption of the contaminants,
especially using activated carbon (charcoal) and biological degradation (Gupta et al.
2004; Mezohegyi et al. 2007). Other processes as Fenton, photochemistry, radiolysis or
sonolysis generate highly reactive hydroxyl radicals for bleaching; finally arising to the
mineralization of recalcitrant compounds (Ozen et al. 2005). In the boom of the eco-
conservation and the eco-friendly techniques to degrade the pollutants in water and
wastewater, the Advance Oxidation Processes or AOPs are seen as alternative
techniques (Gupta et al. 2004) to the traditional processes.
Techniques as hydrogen peroxide oxidation, ozonation, photolysis, Fenton
process, photocatalytic oxidation, wet-air oxidation and ultrasonic sonication are
considered as part of the AOPs used for the degradation of contaminants (Gupta et al.
2004; Garriga I Cabo 2007). The AOPs use chemical procedures based on the use of
catalysts or photochemical compounds which generate highly reactive transient species
as the hydroxyl radical which possesses high affectivity for the oxidation of organic
compounds (Marin et al. 2007). The AOPs are defined as “processes that involve in situ
generation of free radicals” (Priyas and Madras 2006) with a highly potential oxidant
such as the hydroxyl radicals (•OH) (Priyas and Madras 2006; Ai et al. 2007a; Garriga I
Cabo 2007; Marin et al. 2007; Mosteo et al. 2008) being non-selective chemical oxidant
processes (Ai et al. 2007a; Mosteo et al. 2008). These radicals are produced by the
combination of the hydrogen peroxide, UV radiation, ozone and a semiconductor as
6
titanium oxide or the combination of hydrogen peroxide with iron ions (Fenton reaction)
(Marin et al. 2007). The radicals (OH•) produced during the AOPs are powerful oxidants
because they have high oxidative potential (E0OH/H2O=2.8 V) when compared with the
normal hydrogen electrode (Abdelmalek et al. 2006).
AOPs have many advantages as: the complete mineralization of the pollutant,
are non-selective process, can be used in low concentration of contaminants and can be
combined with other methods (Garriga I Cabo 2007). The use and development of
photocatalytic processes for the removal of harmful contaminants, as a treatment for
wastewater and air pollutants is becoming increasingly popular (Yin et al. 2009).
Heterogeneous photocatalysis is one of the AOP’s and is based on the direct or indirect
absorption of photons from ultraviolet (UV) or visible light by a semiconductor that
possesses the appropriate energy gap. According with Ruan and Zhang (2009) the “UV
–driven photocatalytic activity of the sample is much higher than the visible light –driven
photocatalytic activity” because the shorter the wavelength the higher quantum yield.
Velegraki and Mantvinos (2008) describe the importance of the heterogeneous
photocatalytic degradation as
“organic compounds can then undergo both oxidative degradation
through their reactions with valence band holes, hydroxyl and
peroxide radicals and reductive cleavage through their reactions
with electrons yielding various by-products and eventually mineral
end-products.”
The excitation of the semiconductor can take place by two different ways: i) the direct
excitation of the semiconductor (direct absorption of the photons by the surface of the
semiconductor) or ii) the excitation of molecules previously adsorbed on the surface of
the semiconductor which transfer the electrons to the semiconductor (Marin et al. 2007).
The direct absorption process of the photon causes the excitation of the surface or
7
interface region between the solid and the liquid avoiding any chemical change in the
catalyst (Marin et al. 2007). A distinctive characteristic of the interface is the charge
redistribution to both sides of the interface (Marin et al. 2007). Vinu and Madras (2010)
define photocatalysis as
“the acceleration of the rate of chemical reactions
(oxidation/reduction) brought about by the activation of a catalyst,
usually a semiconductor oxide, by UV or visible radiation”.
Other authors (Aarthi and Madras 2007) argue that
“in aqueous environment, the holes created under the UV
irradiation are scavenged by the hydroxyl groups present on the
surface, generating OH• radicals, which promote the oxidation of
the organics”.
The semiconductor for the photocatalyst should be chemical and biological inert,
stable, inexpensive, of easy synthesis and production, and without human and
environmental risks (Garriga I Cabo 2007). When a dye is used, the mechanism of
photodegradation involves the excitation of the dye and the transference of the electrons
to the conduction band of the photocatalyst (i.e. TiO2) to generate the dye radicals.
These radicals react with the oxygen on the surface of the catalyst generating oxygen
radical species as O2•-, H2O2 and •O2 remaining the valence band unaffected (Yin et al.
2009).
Another form to simplify this complex process is considering that the
photocatalyst (i.e. titanium oxide) absorbs a photon having energy greater than or equal
to the band gap (hv≥ EBG); This energy absorption implies the promotion of an electron
from the valence band to the conduction band of the photocatalyst. This promotion
leaves a “hole” (positive charge) in the valence band giving place to the formation of
8
“electron-hole” pairs. If the pairs migrate to the surface of the metal they can react with
the solution (Prakash et al. 2009; Vinu and Madras 2010). Figure 1.01 shows a
schematic view of the photoexcitation process experienced by a semiconductor.
Figure 1.01. Schematic diagram for the photoexcitation process
in a semiconductor via photon irradiation (Adapted from: Hu et al.
2010; Vinu and Madras 2010).
Considering this photocatalytic mechanism, the photodegradation process should
be affected by the light source (irradiation energy), dye concentration, catalyst
concentration and the presence of other organic substances or ions in the solution
(Aarthi and Madras 2007, Yin et al. 2009). Some of the most common photocatalysts
include TiO2, ZnO, ZnS, CdS, WO3, SrTiO3, and SnO2 (Sokmen et al. 2000; Priya and
Madra 2006). Additionally, catalysts with perovskite structure (Yu et al. 2009; Torres
Martínez et al. 2010) are also used for photochemical reactions. For degradation on wet
oxidation, different types of catalysts are used including heterogeneous catalysts of
metal oxides (ZnO, CuO, MnO2, SeO2, TiO2, ZrO2, etc.), noble metals on alumina
9
support and metal impregnation on activated carbon (Cu, Co, Bi, Fe, Mn) (Ma et al.
2007).
The photocatalysis is an AOP commonly used because is able to mineralize
organic pollutants at low cost (Yu et al. 2009). Other important AOP is the ultrasonic
irradiation. At the beginning of the 20th century, Richards and Loomis described the use
of the ultrasound irradiation technique as driving force for a chemical transformation
(Priya and Madras 2006). Degradation process using ultrasound irradiation in
heterogeneous catalysis can be increased due the formation of radicals as •OH during
the cavitation process (Shimizu et al. 2007). Cavitation phenomenon in liquids includes
the nucleation, growth and collapse of small bubbles (Shimizu et al. 2007). According to
the authors (Shimizu et al. 2007), cavitation is fundamental for the chemical and
mechanical process occurring during the ultrasound irradiation. This process can induce
the increase of temperature in hot spots of thousands of Kelvin (T=4000 K) in an
adiabatic heating, and pressures in the scale of hundreds of atmospheres (313 atm)
leading the dissociation of the water molecules producing hydrogen atoms and hydroxyl
radicals (•OH) (Priyas and Madras 2006; Shimizu et al. 2007). These radicals can
produce many chemical reactions (sonochemical reactions) (Shimizu et al. 2007;
Kavitha and Palanisamy 2011). The use of the sonochemical reactions could be
potentially used in environmental processes as wastewater treatments (Shimizu et al.
2007). Semiconductor catalysts commonly used in ultrasonic degradation are Fe2O3,
TiO2, ZnO and CuO (Priya and Madra 2006).
Priya and Madra (2006) point out that one of the main advantages of the
ultrasonic irradiation with respect to the photocatalytic process is the elimination of the
“spatial limitation” over the catalyst, because cavitation process increases the generation
of radicals and is extended along the solution and it is not exclusively limited to the
10
catalyst surface. This process increases the surface area, avoiding the occlusion of the
active sites on the surface, reducing the mass-transfer limitations. Authors describe the
“spatial limitation” as a problem caused by light screening effects produced during the
photocatalytic reaction that reduces the excitation area on the surface of the catalyst
(Priya and Madra 2006). Use of the ultrasonic irradiation for the degradation process of
a dye could be affected by many factors as the concentration of the catalyst and the dye,
the presence of anions, the pH and presence of scavenger agents in the solution
(Shimizu et al. 2007). Some authors (Shimizu et al. 2007) studied the synergistic effect
of the photochemical process on the sonochemical process (ie. degradation of salicylic
acid).
The Fenton reaction as part of the AOPs generates hydroxyl radicals. This
process is clearly non selective (Ai et al. 2007b) and represents a viable technique to
degrade hazardous organic compounds. Horstman-Fenton and Jackson (1899)
demonstrated the importance of iron and hydrogen peroxide during the oxidation of
some substances. A characteristic of the Fenton process is that the reaction requires
acid conditions to work more efficiently (pH ranging from 2 to 3) (Ai et al. 2007b). The
development of a Fenton process working efficiently in a neutral pH should be an
advance, because it is unnecessary the decrease of the pH before the reaction takes
place, decreasing the generation of sludges during the process and increasing the
possibility to recuperate the Fenton reagent (iron) from the media (Ai et al. 2007b).
Toxicological studies with L gibba demonstrated the degradation of substances as
sulfonamides (antibiotics) using anodic Fenton treatment (AFT) in solutions with
concentration of 100 μM (Neafsey et al. 2010).
In a biological process, Hotta et al. (2010) demonstrated that the addition of Fe2+
ion stimulated the cell growth of Sphingomonas spp increasing the biodegradation
activity of the alkylphenol polyethoxylates or APEOn (used as detergents, emulsifiers and
11
pesticides) increasing the production of endocrine active metabolites. According with
the authors (Hotta et al. 2010) three possible classifications of the microbial degradation
of man-made compounds in the environment are possible; biodegradation rate increases
by stimulation of the cell growth by a chemical substance, by minerals presents in the
media and by enzyme induced and/or stimulation of the minerals.
It is relevant to define some important terms concerning these reactions (i.e.
Fenton and Fenton-like reagents). According to Ai et al. (2007a), the Fenton reagent
can be defined as the combination of hydrogen peroxide and iron (II) (Fe2+/H2O2).
Fenton-like reagent does not include iron (II) species and normally this term is used for
the combination of Fe3+/H2O2 although both reagents (Fenton and Fenton-like) are
present during the reaction because both iron species are in equilibrium during the
reaction. The Fenton-like reagent is capable of oxidizing organic substrates, but it is
somewhat less reactive than Fenton reagent. Similarly to Fenton reactions produced by
Fe2+/Fe3+ in presence of hydrogen peroxide, Randorn et al. (2004) demonstrated that
analogous processes are also observed with other transition metals as titanium. The
reactive titanium species involved in the Fenton reaction are Ti3+/Ti4+.
Use of the Fenton and Fenton-like reactions has two principal disadvantages for
the use in large scale; the first one is the high cost of the reagents required (H2O2) and
their instability in solution, and the second one is the concerns involved in the use of
acidic pH (pH < 4) and with a narrow range of pH values during the process (Ai et al.
2007b). As Fenton reagents (Ai et al. 2007b) different compounds including hematite,
goethite, clays, iron hydroxide and iron supported on different materials have been
evaluated.
An alternative to the typical Fenton reactions based on the use of soluble
Fe2+/Fe3+ species is the use of Fe0 phase as a supported or immobilized catalyst and
hydrogen peroxide as oxidizer (Ai et al. 2007a). Examples of possible reagents for
12
environmental remediation include Fe0, Fe3O4 (magnetite) and Fe2O3 (maghemite) (Ai et
al. 2007a). The Fe0 is used to remove organic compounds from the soil and Fe3O4 and
Fe2O3 are normally used for the degradation of organic compounds in solution. Ai et al.
(2007a) demonstrated the efficiency of the Fe@Fe2O3 core-shell nanowires for the
degradation of RhB. These materials have been synthesized by using different
procedures as chemical vapor deposition, different metal oxidation processes and wet
chemistry (Huh et al. 2010). Some authors point out the disadvantage of using zinc
compounds because they are easily oxidized and the zinc oxide is weak and instable
forming zinc hydroxide in some solutions (Randorn et al. 2004).
Magnetites and related materials attracted a great deal of attention when a
Martian meteorite was analyzed and these materials where found as one of their main
components (Nyiro-Kosa et al. 2009). The magnetite is a versatile material due to their
interesting applications in different fields such as catalysis, information storage,
optoelectronics and biomedical applications that include magnetic bioseparation,
magnetic resonance imaging contrast enhancement and targeted drug (Marquez et al.
2011, 2012). For these applications, the particle size of the magnetites should range
from 30 to 120 nm (Nyiro-Kosa et al. 2009). Proteins of magnetotactic bacteria can be
used to biomimetic the natural process in the lab (Nyiro-Kosa et al. 2009. The magnetite
size is influenced by different parameters, including the concentration of the reagents,
temperature, pH of the solution and the reaction time (Nyiro-Kosa et al. 2009). Among
the possible methods for the synthesis of magnetites the co-precipitation, pyrolysis,
ultrasound irradiation, hydrothermal or electrochemical approach can be considered as
the most useful and with higher yields than other processes (Nyiro-Kosa et al. 2009).
The use of the nanomaterials for environmental and energy applications has
experienced an important increase due to the development of new synthesis processes
to manufacture these new materials at atomic and molecular scale. As a result,
13
materials can be designed to have different chemical and/or physical properties
according to the interest of the investigator (Hu et al. 2010). The electronic band
structures finally determine the properties of the inorganic catalyst (Osterloh 2008). The
use of transition metals is relevant due to the presence of d orbitals in their electronic
configuration (Randorn et al. 2004). Many synthesis techniques as co-precipitation, sol-
gel, microemulsions, freeze drying (or lyophilization), hydrothermal processes, chemical
vapor deposition, etc. are commonly used to control the morphology, size and the
uniformity of the structured nanoparticles so grown (Hu et al. 2010). Cao (2004) studied
the electrophoretic deposition for the synthesis of titanium oxide nanorods synthesis.
The use of heterogeneous catalysis, by using nanosized catalysts as TiO2,
demonstrated the complete mineralization of the hazardous substances to CO2 and
water by means of •OH radicals generated during the photochemical process (Shimizu
et al. 2007). The TiO2 has important applications in green chemistry because it is
commonly used as a catalyst for the synthesis of pharmaceutical products, reducing the
traditional large amount of waste because can be recoverable, increasing the yield of
products (Prakash et al. 2009). An example of this improvement in the pharmaceutical
production is the modification in the Biginelli’s reaction on the synthesis of
dihydropyrimidin-2 (1H)-ones (Prakash et al. 2009). The titanium oxide is inexpensive,
non-toxic in nature, stable under ambient conditions, environmental friendly, able to use
the solar radiation (Randorn et al. 2004, Marin et al. 2007, Yin et al. 2009, Velegraki and
Mantvinos 2008), antibacterial activity (Parthasarathi and Thilagavathi 2009), interesting
optical and electronic properties, low cost, abundance (Velegraki and Mantvinos 2008)
and it is appropriate for some oxidation or reduction reactions in aqueous solutions
(Prakash et al. 2009). Titanium oxide nanowires are other interesting structures of the
oxide and have been used, among other applications, for the degradation of pollutants
by photocatalysis and for the production of hydrogen by a photocatalytic water splitting
14
process (Huh et al. 2010). The TiO2 has a band gap of 3.2 eV (Marin et al. 2007;
Prakash et al. 2009) which is relevant for the photocatalytic activity. Other advantages
of the titanium nanowires include the high specific surface area and an easy recovery
process by filtration, centrifugation, etc. (Huh et al. 2010). The titanium oxide is widely
studied because it possesses photocatalytic and photoconductor characteristics; is used
for the degradation of azo dyes, volatile organic compounds and others (Hernandez
Enriquez et al. 2008) and could be recoverable after the process (Rahmani et al. 2008).
Another pollutant studied was phenol by titanium oxide (anatase) (Rahmani et al. 2008).
Titanium oxide nanostructured films have also been used for the degradation of stearic
acid (Takahashi et al. 2011).
In the recombination process between the valence band and conduction band a
low quantum yield should be observed; to resolve this situation some authors
recommend the use of the transition metal and their oxide to create an electron trap to
increase the efficiency (Li and Shang 2010; Zhou et al. 2010). The use of PdO
nanoparticles on titanium oxide nanotubes is an alternative to create an electron trap to
increase the lifetime of charge carriers and subsequently improve the photoactivity (Li
and Shang 2010). Several materials as the Pt@TiO2 NWs synthesized by hydrothermal
process are an example of materials in which the Schottky effect for the degradation
process is relevant (Wang et al. 2010). Synthesis in gas phase of titanium oxide doped
with SiO2 and the synthesis of Ag2O/TiO2 are also known (Remnev et al. 2009, Zhou et
al. 2010). Other types of oxide catalysts with catalytic applications are the
nanostructured Mn2O3 (Su et al. 2010) and CuO-MoO3-P2O5 materials (Ma et al. 2007).
According to Marin et al. (2007), the use of a sol-gel approach for the synthesis
of TiO2 over different supports (i.e. glass) is a good method because the synthesized
product is obtained as a stable and homogeneous sheet of titanium oxide, catalytically
active and resistant. Randorn et al. (2004) mentioned the importance of some thermal
15
treatments in this catalyst (i.e. calcination in presence of oxygen) to increase the
interactions between OH- from water to the surface of the catalyst.
The carbon nanotubes (CNTs) are another important group of materials in the
development of nano-optical and electronic devices as quantum memory elements,
magnetic storage media and semiconducting devices due to their internal structures,
high surface area, low density and chemical stability (Hussein Sharif Zein and
Boccaccini 2008). These materials can be modified adding other materials to the
surface of the CNTs (Hussein Sharif Zein and Boccaccini 2008). The carbon nanotubes
are “cylindrical molecules formed by one or more sheets of carbon atoms rolled one over
one” (Anson Casaos 2005) with a diverse range of diameters and lengths. This material
has been extensively studied during the last years due to its special geometry and
amazing properties (Anson Casaos 2005).
The carbon nanotubes are classified in two main groups: multiple concentric
nanotubes precisely nested within one another namely multi walled carbon nanotubes
(MWCNTs) and nanotubes with a single wall (SWCNTs) (Lopez-Fernandez 2009). The
nanotubes are composed by sheets of graphene. The graphene structure is composed
by carbon atoms having a hexagonal arrangement of carbons with sp2 hybridization
(Anson Casaos 2005). In the SWCNTs the graphene sheet is rolled to form the tube,
meanwhile in the case of MWCNTs the structure is formed by concentric cylinders
(Lopez-Fernandez 2009, Hernández Rueda 2010). A secondary classification of the
nanotubes is based on the chirality (as “zig-zag”, “armchair” and chiral), diameter and
quantity of walls (Anson Casaos 2005; Hernandez Rueda 2010). The chirality defines
the possible behavior of the nanotube; i.e. metallic behavior defines electrical properties
of the material (Lopez-Fernandez 2009). The surface of carbon nanotubes can be
related to the possible uses in some applications (Anson-Casaos 2005) including
hydrogen storage and fuel cells (Anson Casaos 2005).
16
The nanotubes are commonly as aggregates. To disperse these materials is
necessary to use mechanical dispersion, ultrasound and functionalization techniques
(Hernandez Rueda 2010). These materials can be functionalized by two principal
approaches; the covalent and supramolecular functionalization. These methods
preserve the structural and electronic integrity of the materials (Lopez-Fernandez 2009).
Treatments as purification with acids (acid reflux), thermal oxidations (in air and high
temperature) or chemical activations can partially modify the structure of the nanotubes
(Anson Casaos 2005). The most relevant structural modification consists in opening the
ends of the nanotubes because the original structure is closed as a capsule (Anson
Casaos 2005).
The use of model contaminants is relevant for the study of many processes. The
most common substances used as model contaminants are the organic dyes. Until the
XIX century, synthetic dyes were used as inks (Confortin et al. [unknown date]). The
dyes have different applications in paper industries, leather, cosmetics, drugs,
electronics, plastics and printing (Vinu and Madras 2009). According to the authors
(Vinu and Madras 2009) 80% of the synthetic dyes are consumed by the textile industry.
Some authors have determined that the annual discharge of waters containing dyes
ranges from 30 000-150 000 tons (Vanhulle et al. 2008). These wastewaters also
contain other chemicals used during the processes (Vinus and Madras 2009). Torres
Martinez et al. (2010) point out that according to some statistical results approximately
12% of the synthetic textile dyes used during a year are “lost” during the manufacturing
and operational procedures and from that 12%, the 20% will be finally released to the
ecosystem through the industrial water discharges.
In the textile industry, more than 10 000 different dyes and pigments are
available in the market and 20-30% of them are reactive dyes (Karadag et al. 2006;
Dafnopatidou et al. 2007). These dyes are characterized by their brilliant colors, high
17
wet fastness, easy application and a minimum of energy applied during the process.
These dyes have, as part of the structure, azo, anthraquinone, phthalocyanine, formazin
or oxazine functional groups (Karadag et al. 2006). Approximately 60% of the reactive
dyes used contain an azo group (Karadag et al. 2006).
Dyes are nonbiodegradable compounds (Mahanta et al. 2008). Industrial
wastewaters that contain biorefractory compounds are normally limited to the use of
chemical treatments because the chemicals are toxic to the microorganisms used in the
conventional biological treatments (Barrera-Diaz et al. 2009). Potential human exposure
to wastewater which contains dyes is a concern because are carcinogenic compounds,
showing high resistance against biological, physical and chemical reactions (Vanhulle et
al. 2008). Different processes are employed to remove color from wastewaters including
the use of activated carbon, membrane filtration, ultrafiltration, coagulation-flocculation,
electrocoagulation, UV light and ozone (Barrera-Diaz et al. 2009).
The effluents of the textile industry have high concentrations of organic and
inorganic dyes which are strongly colored, have high chemical oxygen demand (COD),
present important fluctuations in the pH, and are toxic to the organism (Abdelmalek et al.
2006). The common techniques used to remove the dyes include chemical, physical
and biological processes (Dafnopatidou et al. 2007). Nevertheless, these conventional
processes for the treatment of sewage waters including the degradation of residual
dyestuffs are inefficient because these compounds have high molecular weight and
biochemical stability (aromatic rings) (Panizza et al. 2006; Ma et al. 2007). The
adsorption process using activated carbon to eliminate the contaminants has the
advantage that is very easy to use but this method is expensive (Gupta et al. 2004) and
produces another problem during the disposition of the contaminated material. Another
method is the adsorption of the dye by polymers and other materials (Karadag et al.
2006; Mahanta et al. 2008). The conventional treatments do not reduce the toxicity of
18
the dyes (Barrera-Diaz et al. 2009). One of the principal disadvantages of the physical
methods as coagulation, precipitation and adsorption is the sludge formation, possible
toxic by-products and the chemical processes are expensive (Panizza et al. 2006; Ma et
al. 2007; Hernandez Enriquez et al. 2008; Mahanta et al. 2008).
Most of the dyes are organic or organometallic compounds characterized by
having aromatic rings. This characteristic necessarily implies the use of treatments by
unconventional methods (Torres Martinez et al. 2010). The decomposition of many
organic compounds as pesticides, dyes, aromatics, halogenated aliphatic compounds,
metallurgical residuals, oil and chemical compounds derived from steel processes are
based on photocatalytic degradation processes (Sokmen et al. 2000). Meanwhile, to
maintain the aesthetic and reduce the environmental impacts of the industrial effluents is
necessary the discoloration of wastewaters (Hussein Sharif Zein et al. 2008).
The degradation process of the organic dyes could be defined in two different
ways: one is the discoloration and the other one is the mineralization (Vinu and Madras
2010). The authors (Vinu and Madras 2010) also clarify the difference between
discoloration process (reduction of the parent dye) and mineralization (complete removal
of the organic components and their transformation in CO2). Intermediates that are
generated during the degradation process could be colored (Vinu and Madras 2010).
The total organic carbon (TOC) analysis helps to determine the carbon content and its
variation during the degradation process. Different dyes exposed to photochemical
degradation under visible light show the following degradation order: indigo
≈phenanthrene > triphenylmethane > azo ≈ quinoline > xanthenes ≈ thiazine >
anthraquinone. The order of the light sources is: natural sunlight >> 90 W halogen flood
light > 150 W spotlight (Vinu and Madras 2010).
19
The organic dyes are classified according to their functional groups as: azoic,
anthraquinonic, heteropolyaromatic, aryl methanes, xanthenes, indigo, acridine, nitro,
nitroso, cyanine and stilbene (Vinu and Madras 2010).
Table 1.1 Characteristics of the most important dyes classes (Adapted from: Parshetti et
al. 2006; Vanhulle et al. 2008).
Classes of
Dyes
Type of Fiber
Chemical Class
Acid
Polyamide, wool
and nylon
Anthraquinones, azo, triarymethanes azo
or metal complex azo, phtalocyanines
Reactive
Disperse
Cellulose, polyester,
acetates
Small azo or nitro compounds, multi azo,
phtalocyanines, stilbenes
Direct vat Cellulose, rayon Indigoids, diarylmethanes, triarylmethanes
Basic Sulfur Acrylic, polyester,
cellulose
Polymer with S-containig heterocycles,
azo
Different model organic dyes have been selected for this research due to their
different structures (functional groups) and their presence in the environment. According
to Vinu and Madras (2009), the degradation reaction of a dye by a hydroxyl radical
generated by UV irradiation of ultrasonic is as follow:
TiO2(OH·)ads – Dads + TiO2 – Dads(or D) → intermediates (P) → CO2 + H2O
20
Methylene blue (MB) (Figure 1.02) is a hetero-polyaromatic dye (Ma et al. 2007)
commonly used for printing cotton, as textile tannin and for coloring leather. MB is also
used in chemistry as a base-acid indicator and in the medical field as an antiseptic
(Gupta et al. 2004). During the photocatalytic degradation process of MB, some
transients were detected when nanosized TiO2 was used as catalyst, including 3-
dimethylamino aniline, benzene sulfonic acid, phenol and hydroxylated products of
amino and sulfoxide groups (Vinu and Madras 2010). Huh et al. (2010) developed a
study on the degradation of MB using visible light. Authors used a standard white light
bulb (100 mW•cm-2) as the visible light source. Starting concentration of the MB was
10-5 mol/L.
S+
N
NCH3
CH3
NCH3
CH3Cl-
Figure 1.02. Molecular structure of Methylene
blue.
Rhodamine B (RhB) is a dye that belongs to a class of compounds called
xanthenes (Figure1.03), extensively used as model compound because it shows a
strong absorption band in the visible region of the electromagnetic spectrum (555 nm)
and this dye is characterized by having a high stability at different pH values. Ai et al.
(2007), argue two possible competitive mechanisms during the degradation of the RhB.
The first one is the N-demethylation and the second one is the breakdown of the
xanthene structures. This dye is currently used as dye laser material (Aarthi and Madras
2007) and is part of the triphenylmetane family of dyes that contain four N-ethyl groups
at both sides of the xanthene rings (Yu et al. 2009). Also it is stable in aqueous solution
21
(Yin et al. 2009). The RhB is also used as a dye for wool and as analytical reagent
during the determination of metals in solution, especially alkali, and alkaline earth
metals. This dye is used in the textile, food and cosmetic industries but can cause
aesthetic pollution in the aquatic environments showing high resistance to biological and
chemical degradation (Yu et al. 2009). Currently this dye has been prohibited for the
use as food color because it is suspected that RhB could be a carcinogenic substance
(Gupta et al. 2004).
O N+
CH3
CH3
N
CH3
CH3
COOH
Figure 1.03. Molecular structure of Rhodamine B.
Azo colorants are released to the environment by many industrial sources as
textile, pharmaceutical, paper and cosmetic. They are very important pollutants because
are very recalcitrant and even at low concentrations can affect the water sources giving
an undesirable color, which reduce the sunlight penetration through the water column
(Mezohegyi et al. 2009). Additionally, another important problem derives from the fact
that their degradation products could have toxic or even mutagenic properties
(Mezohegyi et al. 2009). Some azo dyes are commonly used in the food industries
although some studies reveal that these dyes can cause hyperactivity in children
(Mezohegyi et al. 2009) and, some of them, during the hydrolysis process, can produce
by-products potentially dangerous, including carcinogenic amines (Ozen et al. 2005).
Many research groups have studied the use of biological methods for the degradation of
22
the azo dyes but these processes are normally very slow (Mezohegyi et al. 2009) and
sometimes need red-ox mediators to accelerate the degradation rate.
Azo dyes under reductive conditions could be excised in one of the 22 potencial
carcinogenic aromatic amines, which are categorized as dangerous substances
involving kidney, urinary bladder and liver (Vanhulle et al. 2008). Example of some azo
dyes are the methyl orange, methyl red, phenolphthalein and 1,10-Phenanthroline (Hong
et al. 2009).
Methyl orange (MO) (Figure 1.04) is commonly used as a dye in the textile
industry and in chemistry as an acid-base indicator (Marin et al. 2007). MO is not a
biodegradable substance when is in aqueous solution. The azo dyes possess basically
two aryl groups (benzene rings) connected by the azo group (-N=N-) as a bridge
between the aryl rings; these structures conform the chromophore (Ozen et al. 2005). If
one protic group is conjugate to the azo a tautomer is formed (azo-hydrazine
tautomerism) (Ozen et al. 2005). The hydroxyl radical reactions experienced by azo
compounds include the addition to the aryl ring, hydrogen removal or one-electron
oxidation (Ozen et al. 2005). Bi2Fe4O9 nanosheets are another type of photocatalyst for
degradation of MO (Ruan and Zhang 2009).
N N NCH3
CH3
SONa3
Figure 1.04. Molecular structure of the Methyl
Orange.
Crystal violet dye (Hexamethyl pararosaniline chloride or CV) is part of the
triphenyl methane dye group, commonly named Basic Violet 3, and is used as a DNA
label (Ma et al. 2011), in textile, ball point pens, on artist pallet, in paper industry, as a
23
fungicidal, human anti-parasitic and also in veterinary medicine (Abdelmalek et al. 2006)
but affect the aquatic life acting as a mutagenic agent because affects the mitotic
process (Pattapu et al. 2008; Confortin et al. [unknown date]). The triphenylmethane
dyes are carcinogenic to animals (Parshetti et al. 2006). Many studies were performed
for the degradation of CV in aqueous media under aerobic conditions (Pattapu et al.
2008). Some authors studied the degradation process of the CV under aerobic
conditions using MnO2 as a catalyst and they conclude that the degradation process
could be affected by many factors as the presence of possible ions, the catalyst and dye
concentration, pH of the solution and other factors (Pattapu et al. 2008). Also, the
kinetic of degradation for the reaction is a first order (Pattapu et al. 2008).
The CV and the Methyl Violet (MV) have similar structures. The only difference
between both structures is the presence of one NHCH3 group (in MV) instead of an
CH2(CH3)2 in CV (see Figure 1.05a and Figure 1.05.b).
Figure 1.5. Molecular structure of Crystal Violet (a) and the molecular
structure of Methyl Violet (b).
Aromatic compounds constitute an important source of environmental pollution
reaching the atmosphere and groundwaters because there are widely used as
intermediates in the production of pesticides, synthetic polymers and dyes (Huang et al.
24
2010a). The presence of these substances in the environment is a concern because
possess carcinogenic, teratogenic and toxic properties (specially the azo dyes),
decrease the light penetration through the water column, and affect aesthetically
(Karadag et al. 2006; Vanhulle et al. 2008; Huang et al. 2010b) damaging the
environment (Dafnopatidou et al. 2007).
The organic pollutant selected for comparison purposes has been the p-amino
benzoic acid (pABA) (see Figure 1.06). The yeast Saccharomyces cerevisiae uses the
p-aminobenzoic acid as a precursor in some biosynthesis processes but in mammalian
cells (human and rats cells) pABA competes with synthesis processes inhibiting the
biosynthesis of some enzymes (Marbois et al. 2010). Based aminobenzoic acid
compounds are present in clinical, pharmaceutical, anesthetic drug metabolite,
cosmetics, sunscreen products and ammunition waste (Schmidt et al. 1997).
O OH
NH2
Figure 1.06. Molecular structure of p-amino
benzoic acid (pABA).
The presence of anthropogenic substances in fresh waters is a concern. Some
authors (Gaulke et al. 2009) studied different methods for treatment of this type of
compounds. Presence of exogenous estrogenic substances, for example, in aquatic
system in concentrations less than 1 ng L-1 affects aquatic species as fishes because in
25
the organism is an endocrine disruptor. The mayor sources of these substances are the
municipal wastewater treatment plants and the operation of animal feeding areas. Other
important contaminants in the aquatic environments as some antibiotics (sulfonamides)
commonly used in the agriculture and p-ABA which is used as a component of
sunscreens, have a very similar structure with a substituent in the C1 (Neafsey et al.
2010).
Eichenseher (2006) developed different studies that evidence the presence of
compounds used as UV filters in the lipid tissue of fishes. In this study was stated that
these compounds enter into the environment when people use sunscreens swimming in
the rivers or lakes. The UV filters are present in lip balms, sunscreen lotions and many
cosmetic and personal care products (PPCPs) but some of the UV filters compounds are
endocrine disrupter and can alter the reproductive functions of the organism. The 4-
methylbenzylidene camphor (4-MBC) and octocrylene (OC), for example, are UV filters
which can bioaccumulate in the aquatic food chain and are biologically degraded
although they get degraded very slowly in the environment and persist for a long time.
(Eichenseher 2006).
The fundamental research question for this study is to determine which of the
possible degradation processes, including catalytic photodegradation, photo-Fenton or
Sono-Fenton is more efficient for the degradation of organic contaminants dissolved in
water. To reach this goal, many objectives should be previously satisfied as: i) the
synthesis of different catalysts as TiO2 nanowires, TiO2@CNTs, ZnO nanoparticles,
Fe2O3 nanowires and magnetite nanoparticles, used in different catalytic processes
(Sono-Fento, Photo-Fento and photocatalysis reactions) to degrade model compounds
(dyes) as Methylene Blue, Rhodamine B, Methyl Orange, Gential Violet and Methyl
Violet and an organic contaminant as p-aminobenzoic acid, ii) determine the rate of
reaction of the different processes, and iii) finally, to establish which degradation
26
processes (photocatalysis, Sono-Fenton and Photo-Fenton) are more effective for the
degradation of organic compounds as possible alternatives as wastewater treatments.
26
ChapterTwo
Experimental Techniques
In this chapter we report on the experimental techniques and synthesis methods
used during the development of this experimental work. An important part will be
focused on the synthesis of the catalysts used for the degradation of organic
compounds. The experimental setup for the irradiation (photo and sono irradiation) of
organic compounds in solution will be explained. Spectroscopy (UV-vis, Fluorescence,
Raman and XPS), Total Organic Carbon (TOC), magnetometry (VSM) and microscopy
(FESEM) techniques used during the present work are included in this chapter. Some of
the instruments described here are located at the School of Science and Technology
(Universidad del Turabo), Autonomous University of Madrid (Spain) and at the
Complutense University of Madrid (Spain). Magnetometry measurements were carried
out with the research group of Prof. Óscar Perales at Department of General
Engineering, University of Puerto Rico in Mayagüez. Raman experiments were
performed at the University of Puerto Rico in Rio Piedras.
2.01. X-Ray Diffraction (XRD)
The X-ray diffraction or XRD allows obtaining relevant information on solid
samples. Among the different information to be obtained by XRD to be mentioned are
the crystalline structure, the averaged particle size, the unit cell dimensions, and the
constituents of the cell. Additionally, this information can be obtained in situ to
characterize the different transitions (crystallinity, particle size or even the variation of
the chemical composition) during a chemical reaction (Thomas and Thomas 1997). This
technique is based on the principle of the diffraction or dispersion of light waves when an
X-ray beam bombards a sample.
27
X-rays are electromagnetic radiation with photon energies typically in the range
of 100 eV - 100 keV. For diffraction applications, only short wavelength X-rays (hard X-
rays) in the range of 10 to 0.01 nanometers (1 - 120 keV) are used. Because the
wavelength of X-rays is comparable to the interatomic spacing, they are ideally suited for
probing the structural arrangement of atoms and molecules in a wide range of materials.
X-rays are generated after bombardment by an electron beam of a stationary or
rotating solid target. Electrons collide with atoms in the solid target producing a
continuous spectrum of X-rays (Bremsstrahlung radiation). Common solid targets used
in X-ray tubes include Cu and Mo, which emits 8 keV and 14 keV X-rays with
corresponding wavelengths of 1.54 Å and 0.8 Å, respectively. According with the Bragg
theorem, the diffraction pattern is done by the “constructed interference of the waves
scattered from the successive lattice planes in the crystal” and this occurs when the
difference of the path is equal to an integer number of the wavelength (Gersten and
Smith 2001). The Bragg Equation which describes the diffraction process is defined as:
2dsinθnλ
In a solid material, the deviation angle Ф is defined as 2Θ, and Θ is the angle
done by the beam with respect to the crystalline plane and d is the distance between
consecutives planes (see Figure 2.01) (Gersten and Smith 2001; Flewitt and Wild 2003).
Using this equation, the crystal spacing can be measured (Gersten and Smith 2001).
28
2ϴ
d
Figure 2.01. Schematic representation of the
diffraction process from atoms in a crystalline
lattice (Adapted from Flewitt et al. 2003).
Diffractograms consist of a plot of reflected intensities against the detector angle
2-theta. In powder samples, all possible diffraction directions of the lattice should be
attained due to the random orientation of the powdered material.
Using β as the full width at half maximum or FWHM of a broad diffraction peak,
the averaged particle sizes can be estimated (Thomas and Thomas 1997; Hadj Salah et
al. 2004; Sridevi and Rajendra 2009) by applying the Scherrer’s equation:
Dcosθ
Kλβ
where λ is the X-ray wavelength, Θ is the Bragg’s angle and K is the Scherrer constant
that depends on the peak shape (Thomas and Thomas 1997, Hong et al. 2009).
According to Gersten and Smith (2001), there are four different ways available to
perform XRD experiments. The first one is to use a broadband (non monochromatic) X-
ray source and to analyze the back reflection. The second one is the use of a diverging
(noncollimated) X-ray beam. The third one consists of using a non monochromatic
29
source and non collimated beam and in this case the diffraction conditions are reached
during the rotation of the crystal and finally, the fourth way consists of using a
monochromatic X-ray source.
X-ray powder diffraction patterns (XRD) were collected using an X´Pert PRO X-
ray diffractometer (PANalytical, The Netherlands) in Bragg-Brentano goniometer
configuration. X-ray radiation source was a ceramic X-ray diffraction Cu anode tube
type Empyrean of 2.2 kW. Angular measurements (θ - 2θ) were made with
reproducibility of: ±0.0001 degree, applying steps of 0.05 degrees from 5 to 60 degrees.
Figure 2.02-a shows an image of the XRD diffractometer. A detailed view of the
goniometer is shown in Figure 2.02-b.
Figure 2.02. Images of the PANalytical XRD system used in
this research (a) and detail of the goniometer (b).
2.02. Magnetic Susceptibility
Magnetometry has been widely used for determining magnetic properties of
materials. This technique is one of the most appropriate to study and characterize
magnetic materials due to the vast information that can be obtained by the hysteresis
cycles. A hysteresis cycle shows the relationship between the induced magnetic flux
30
density (B) and the magnetizing force (H). It is often referred to as the B-H loop. An
example of hysteresis loop is shown in Figure 2.02.
Figure 2.03. Typical hysteresis loop of capped magnetite
nanoparticles (Marquez et al. 2012, discussion about the
results of "Dimensionality effects on the magnetization
processes in magnetite nanoparticles".
This loop is obtained by measuring the magnetic flux of the magnetic material
under scanning of the magnetizing force. Any magnetic material that has never been
previously magnetized or has been thoroughly demagnetized will follow a similar
hysteresis loop. Greater the applied magnetic field (G), stronger the magnetization
observed. At the saturation level almost all of the magnetic domains are aligned and
additional increases in G will produce subtle changes in magnetization.
Vibrating sample magnetometer, VSM, is based on Faraday’s law of magnetic
induction, which states that a changing magnetic flux enclosed by a coil induces a
voltage in that coil. In this technique, an external magnetic field produces the
magnetization of the sample. Magnetic dipole moments in the sample create a magnetic
31
field around the sample (magnetic stray field). In VSM, the sample is vibrating in the z
direction as a function of time and the stray field is determined as a function of time from
pick up coils and converted into electronic data as a voltage output (see Figure 2.04.).
Figure 2.04. VSM components. Sample
is placed between large diameter poles
for obtaining homogeneous magnetic
fields. The arrow indicates the vibrational
motion of the sample.
Materials may be classified according their magnetic susceptibility to an applied
magnetic field. A paramagnetic material could be defined as a material which is
attracted toward an external magnetic field. In contrast with this, diamagnetic materials
are repulsive when placed in a magnetic field (Gersten and Smith 2001).
The study of magnetic variability was done using a Lake Shore-7400 vibrating
sample magnetometer (VSM) at room temperature (see Figure 2.05). This VSM
instrument can attain fields up to 3.1 Tesla in the presence of 3 inch gap between
magnets and the sample rod vibrates at 84 Hz. At room temperature the magnetization
sensitivity is 0.1 μemu and the maximum limit is 1000 emu.
32
Figure 2.05. Lake Shore-7400 Vibrating Sample Magnetometer (VSM).
2.03. Thermogravimetric Analysis (TGA)
Thermogravimetric Analysis (TGA) is an experimental test that is performed on
powder samples for determining changes in weight in relation to change in temperature.
Such analysis requires high degrees of precision in three measurements: weight,
temperature, and temperature change. The weight change observed during a specific
temperature range can be correlated with the composition of the sample and thermal
stability. This technique is extensively used to determine the composition, thermal
stability, oxidative stability, moisture and volatile content, lifetime and kinetics of
decomposition or dehydration of samples (TA [undate]; Anson Casaos 2005).
Figure 2.06. shows a schematic illustration of a TGA instrument. This instrument
is composed by a sensitive analytical balance, a furnace, a purge gas system, and the
microprocessors to control and display the data. The balance cell is the most important
33
part of any TGA system and consists of a high-precision balance with a pan loaded with
the sample. The sample is placed within an electrically heated oven with a
thermocouple to accurately measure the variations of temperature. During the
measurement, the atmosphere in contact with the sample is controlled by flowing pure
nitrogen as inert purge gas. Analysis is carried out by raising the temperature gradually
and plotting weight against temperature.
Microprocessor
Purge gas outlet
Furnace
Thermal Balance
Tare pan
Purge gas inlet
Sample holder
Thermocuple
PhotodiodeLamp
Curve
Figure 2.06. Schematic illustration of the TGA instrument
(Adapted from TA [unknown date]).
This method has the advantage that only a small amount of substance is needed
(around 10-20 mg). Nevertheless, the main disadvantage of the TGA method is the
limited information that can be obtained from this technique, due to the fact that only
information concerning to the lost or gain of weight by the sample is obtained. The
curves obtained during the analysis are just a behavior pattern and not a fingerprint of
the materials because any small change in the parameters as temperature rampage,
purge gas, sample size or even the sample morphology can affect the shape of the
curve (TA [unknown date]).
34
The thermogravimetric analyses were done with a TGA Q-500 instrument (TA
Instruments) under an inert atmosphere of nitrogen. The heating rampage was of 20
°C/min from 100 to 600 °C. Figure 2.07 shows the instrument used for these
measurements.
Figure 2.07. Thermal Gravimetric Analysis
(TGA), TA instrument, Q500.
2.04. Specific Surface Area (BET)
The study of the surface area of catalysts has a great relevance to determine the
activity of the catalysts because the rate of the product formation can be directly related
to the surface area available. According to Thomas and Thomas (1997), the synthesis
procedure of metal oxide catalysts could have relevant effects on their catalytic
properties due to the different surface area or even the presence of open pore structures
that are appropriate to control the catalytic behavior. The determination of the surface
area is important because can be used to determine catalyst poisoning, thermal
deactivation and other degradation effects over time and also to predict the performance
35
of the catalyst. Three methods are commonly used to determine the surface area; the
volumetric method, the gravimetric method and the dynamic method (Thomas and
Thomas 1997).
The volumetric method was selected to determine the surface area of the
catalysts used in this research. According to Thomas and Thomas (1997), the
monolayer capacity may be identified either by noting the ordinate value of the volume
(when V is plotted against p) as the isotherm bends over sharply or by applying the
Brunauer-Emmett-Teller (BET) theory (Chandras et al. 2010).
Brunauer, Emmett and Teller derived a theory from a statistical and gas-kinetic
model based on the principle that the increase of the adsorbate partial pressure over a
dry powder sample corresponds to the increase of multi-layers on the sample surface.
This technique is normally based on the physical adsorption of nitrogen at low
temperature. This technique measures gas uptake (corresponding to the adsorption
process) under increasing the partial pressure of nitrogen in contact with the powder
sample and the release of nitrogen (desorption process) (Garriga I Cabo 2007).
The BET equation is commonly used when the isotherm curve is well defined
(Thomas and Thomas 1997). The equation is defined as:
0mm0 p
p
cV
1c
cV
1
p)V(p
p
If p)V(p
p
0 is plotted against
0p
p (where 0p is the vapor pressure of the absorbate at
the adsorption temperature) a straight line is obtained. Using the slope and the intercept
the mV can be finally calculated (Thomas and Thomas 1997; Anson Casaos 2005;
Lopez-Fernandez 2009).
The specific surface areas of the catalysts used in the present research were
determined by the BET method using a Micromeritics ASAP 2020 (Figure 2.08). The
36
micropore volume, WMP [cm2/g], was measured using the Barrett-Joyner-Halenda (BJH)
approach (Barret et al. 1951; Marquez et al. 2012).
Figure 2.08. Micromeritics' ASAP 2020
Accelerated Surface Area and
Porosimetry, used in this research.
2.05. Raman Spectroscopy
The most common vibrational spectroscopies are the infrared (IR) and Raman.
Both techniques can be used to assess the molecular motion and to identify species and
functional groups in a sample (Hernandez Rueda 2010).
Raman spectroscopy is a technique based on the Raman Effect, consisting in an
inelastic scattering process discovered in 1928 by the Indian physicist C.V. Raman. In
this process, a monochromatic beam of light is focused onto the sample and the energy-
shifted fraction of the scattered light is detected and measured (Schwartz [unknown
37
date]). Raman Effect can be easily explained using an electro-dynamical or a quantum-
mechanical model.
According to the electro-dynamical model, when an electromagnetic radiation
collides with a body, most of the scattered light appears at the same wavelength of the
incident laser. This effect is due to the fact that this incident light does not undergo any
interaction with molecular vibrations of the sample. This scattered light is produced by
an elastic scatter and is called Rayleigh peak. However, an extremely low fraction of the
excitation light may inelastically interact with atomic vibrations, producing the Raman
scattering. During the Raman Effect, the high frequency vibration of the electric field
vector of the laser source induces a time-dependent dipole moment. The interaction
between the dipole moment and the electromagnetic wave is controlled by the
polarizability of the excited molecule. Only those vibrations leading to variations of the
polarizability are responsible for Raman transitions.
From the quantum-mechanical point of view, all molecules are characterized by
having vibrational states with a limited number of allowed discrete energies. When a
molecule in its ground state is excited by an input of energy this molecule is promoted to
an excited vibrational state. Nevertheless, excitation photons can only be absorbed
when their energy is equivalent to the energy difference between two allowed vibrational
levels. This absorption is possible when excitation radiation is in the infrared range. On
the contrary, excitation radiation of higher energies (i.e. visible or ultraviolet) cannot be
absorbed because its energy is much higher than that concerning to vibrational
transitions. Hence, in most cases no interaction occurs and, in this way, the molecule
does not experience vibrational changes producing a scattered peak at the same energy
as the excitation laser (Rayleigh transition). Only with an extremely low probability, the
Raman scattering is observed at higher or lower vibrational state than before the
interaction is reached.
38
A Raman spectrum is a plot of the detected light intensity (usually given in counts
or arbitrary units) as a function of the photon energy (Raman shift). The Rayleigh line is
observed at zero Raman shift. Anti-Stokes and Stokes Raman bands appear at
negative and positive Raman shifts, respectively. In general, only the most intense
Raman bands (Stokes) are used for characterizing materials (Figure 2.09).
Figure 2.09. Raman vibrational and scattering modes (Adapted from Flewitt
et al. 2003; Hernandez Rueda 2010).
The bands in a Raman spectrum represent the interaction of the incident light
with specific vibrations of the nuclei. These vibrations clearly depend on the sizes,
masses and valences of the atoms, the bond forces and the symmetry of the material
and, for this reason interpretation of Raman spectra provides relevant information about
the sample.
A conventional problem of Raman spectroscopy is the fluorescence emission
that is simultaneously produced by laser beam excitation; this fluorescence emission can
mask the Raman signal. This problem can be avoided by using Raman excitation
wavelengths in a spectral range that is not affected by the luminescence signal (i.e.
infrared radiation). Other possible artifacts are caused by the increase of the local
39
temperature due to the high power density and very high absorptivity of the sample,
which may result in alteration or decomposition of the sample.
Raman spectroscopy can be used in a vast number of applications including
pharmaceutics, forensic science, polymer science, semiconductor physics, and
chemistry of materials. Raman spectroscopy is highly specific for a certain type of
samples (for example, carbon nanotubes of fullerenes) and for this reason, this
technique is used for the identification and structural characterization of materials.
Raman spectroscopy is a non-destructive technique that can be applied to study solids
as well as liquids (even in aqueous solution) or gases, having the additional advantage
that no special sample preparation is needed.
Figure 2.10. Image of the micro Raman
scattering equipment used in this research.
During this research, the Raman spectra of the catalyst samples were recorded
using an ISA T64000 triple monochromator (Figures 2.10). To focus the line (514.5 nm)
of the Coherent Innova 99 Ar+ laser and to collect the backscattered radiation an optical
microscope (Olimpus BH2-UMA) with an 80X magnification was used. This microscope
was equipped with a NEC NC-15 camera. The scattered light dispersed by the
40
spectrophotometer was detected by a charge-coupled device (CCD) cooled with liquid
nitrogen (by using a 2.5 cm CCD and 1800 grooves mm-1 grating, the spectral resolution
obtained was typically less than 1 cm-1) (Dixit 2003).
2.06. X-Ray Photoelectron Spectroscopy (XPS)
X-ray photoelectron spectroscopy (XPS), traditionally called ESCA, is a surface
analytical technique which has proved to be extremely useful for the study and
characterization of the oxidation states. Intensities and positions of photoelectron peaks
depend on over-layer thickness, chemical state of near-surface atoms and the
stoichiometry of the over-layer. This spectroscopic technique is based on the
photoelectric effect, i.e., the ejection of an electron from a core level by an X-ray photon
of energy hv. The sample is irradiated by photons by using an X-ray gun. In the surface
of the sample, photoelectrons (and Auger electrons) are produced. Energy of the
emitted photoelectrons is then analyzed by an electron detector (normally a
hemispherical analyzer, HSA, operated using a constant pass energy mode) that is
placed near of the sample surface to detect the kinetic energy of the electrons leaving
the sample. Kinetic energy (KE) of the electrons is the experimental quantity measured
by the spectrometer, although this value will depend on the X-ray energy used to
produce them. The binding energy of the electron (BE) is the standard parameter which
identifies an element specifically. The next equation establishes the relation among
these different parameters:
W-KE-hvBE
where hv is the X-ray energy and W is the work function of the spectrometer (Garriga I
Cabo 2007).
XPS spectra provide chemical information on the sample surface (typically 20-
100 Ǻ) depending on the nature of the specimen and the angle of the incident X-ray
beam. Maximum sampling depth is obtained when the sample is perpendicular to the
41
incident X-ray beam. When the incident angle with respect to the surface is very low
(i.e. Φ < 10º) the incident radiation can be exploited to study changes in sample
composition at depths of only some angstroms from the surface. In this way, spectra
can be obtained using different incident angles and then compared to finally study the
homogeneity of the sample with respect to depth. The binding energies of core
electrons are directly affected by the energy of the valence electrons. Consequently, if
we consider as an example the core electrons of carbon, the binding energy
corresponding to the C1s transition will depend on the bonded atom: C-H (285·0 eV), C-
Br (286·0 eV), C-Cl (286·5 eV) and C-F (287·9 eV). Due to this effect, it is possible to
distinguish among possible environments around specific atoms. In this example, when
electronegative atoms are bonded to carbon, a δ+ charge is generated on the carbon
atom. As a result, the carbon atom holds electrons more tightly producing a higher
binding energy than for the case of C bonded to H. Contrarily, the excess of negative
charge on an atom has the opposite effect, making the electrons easier to remove,
lowering their binding energies.
The XPS measurements were performed on both an ESCALAB 210
spectrometer (equipped with a hemispherical analyzer) and on a Perkin–Elmer PHI 3027
spectrometer (equipped with a double-pass cylindrical mirror analyzer), using a non-
monochromatic Mg Kα (1253.6 eV) radiation of a twin-anode (Figure 2.11). In all cases,
the spectra were recorded at 20 mA and 12 kV in the constant analyzer energy mode
using a pass energy (PE) of 50 eV. The samples were previously degassed at the
preparation chamber of the spectrometer for at least 24 hours before the analysis and
the vacuum during the spectroscopic analysis was better than 5x10-9 mbar. The binding
energies were corrected using the C-C peak component to remove any charging shifts
and deal with the Fermi edge coupling problems. The C-C peak (at 284.6 eV) used as a
reference peak is originated from the environmental contamination with carbon
42
compounds as CO2 and hydrocarbons (Corma et al. 1997a, Corma et al. 1997b; Arribas
et al. 1999). In the case of samples with copper and with the aim to avoid the X-ray
induced reduction of Cu2+ to Cu+1, samples were maintained at 173 K during the spectral
acquisition and the X-ray power was limited to 200 W (20 mA–10 kV). The spectral
acquisition time was also reduced to the maximum to prevent the damage of the
samples and the possible reduction of Cu2+ to Cu1+.
Figure 2.11. Perkin–Elmer PHI 3027 spectrometer (a), and VG Escalab
210 spectrometer (b) used in this research.
2.07. Field Emission Scanning Microscopy (FE-SEM)
Although optical microscopy is the most conventional and simple solid state
materials characterization technique, this microscopy is clearly limited in its resolution by
the wavelength of light. This technique uses visible light with wavelengths varying
between 400 and 700 nanometers. In most optical microscopes, the presence of
spherical aberration limits the resolution to several micrometers. Distinct from optical
microscopy, the images obtained using scanning electron microscopy are generated by
electrons (Garriga I Cabo 2007) instead of visible light and for this reason the resolution
of this microscopy is limited by the wavelength of electrons (as an example, using a
43
standard energy of 5 keV the theoretical resolution is 0.55 nm). Nevertheless, and as
occurs in optical microscopy, the presence of other limiting factors (lens aberration or
astigmatism) is responsible for the decrease of the theoretical resolution to values on the
order of a few nanometers.
Electrons in a SEM carry significant amounts of kinetic energy, and this energy is
dissipated in a variety of events produced by different interactions between the electron
beam and the sample. These events include secondary electrons (SE) responsible for
the SEM images, backscattered electrons (BSE) (responsible for SEM images with
relevant information concerning the chemical nature of the sample), diffracted
backscattered electrons (DBE) used to obtain similar information to that obtained using
X-ray diffraction, photons that are used for elemental analysis, visible light
(cathodoluminescence), and heat. SE and BSE are the most conventional electron
emission techniques used for imaging samples. SE is mainly used to characterize the
morphology of solid samples and BSE is most valuable to characterize differences in
chemical composition (see Figure 2.12). The scheme of a scanning electron microscope
(Field emission SEM) is shown in Figure 2.12.
In this research, Field emission scanning electron microscopy (FE-SEM) images
were obtained using a JEOL JM-6400 microscope. The microscope is a high-resolution
FE-SEM. It can provide beam voltages ranging from 0.2kV to 40 kV and beam currents
from 10 picoamps to 10 microamps. This instrument offers high performance and low
noise at low accelerating voltages. Resolution of ca. 3 nm is attainable, and
magnifications can be obtained ranging from 10 X to 300,000 X. The cathode is a high-
brightness lanthanum hexaboride (LaB6) source. The SEM is equipped with two-inch
and four-inch airlocks and a Faraday cup for beam current measurements. The sample
stage is computer-driven. Figure 2.13 shows an image of the FE-SEM instrument used
in this research.
44
Cold Cathode Field Emitter
Electron detector
(Scincillator)
Anodes
Electromagnetic
Lenses
Sample holder and
Sample
Digital
Processor
Image
Figure 2.12. Main components of a FE-SEM instrument
(Adapted from Flewitt et al. 2003; NMT Materials Dept
2012).
Figure 2.13. FE-SEM JEOL JM-6400 microscope
(“Centro de Microscopía Luis Bru” at the
Complutense University of Madrid, Spain).
45
2.08. Total Organic Carbon Analysis
Carbon content is one of the most relevant parameters measured in different
types of solutions, including drinking water, industrial wastewater, etc. Carbon analyzers
are instruments devoted to the analysis of organic, inorganic and total carbon content in
these water or liquid solutions. The method is based on the oxidation of the carbon
based compounds to finally produce CO2. During the oxidation process, potassium
persulfate, in presence of UV irradiation, initiates a quick reaction to oxidize the
compounds. Sulfate ions and hydroxyl groups act as free radicals reacting with the
organic compounds. The CO2 produced during the oxidation is carried by the nitrogen
gas to the nondispersive infrared (NDIR) detector and the signal is produced. The
carbon concentration is expressed in mg L-1, parts per million or ppm.
For a typical analysis, a 10 mL sample is diluted to 40 mL in carbon-free distilled
water. The sample is taken by an automatic syringe and read in triplicates for
reproducibility. A duplicate and an internal standard were used during each analysis to
standardize the analysis procedure. The method used in this research was the total
organic carbon analysis (TOC) method with a range of 0.01 – 20 ppm C.
The equipments used to determine the TOC concentration were both a Tekmar
Dohomann, Phoenix 8000 UV-Persulfate TOC Analyzer (Figure 2.14) and a Leco
CHNS-932 (Figure 2.15). This last instrument is commonly used to determine the
carbon, hydrogen, sulfur and oxygen concentrations. The Leco CHNS-932 allows the
detection of carbon in a large concentration range (0.002 to 100%), with a precision of
±0.001. For both instruments used in the present research, the detection method is
based on highly selective, infrared detection systems. The instruments used in this
research can only measure dissolved organic carbon (DOC) (Garriga I Cabo 2007). The
suspended solids in the sample have to be previously removed before the injection into
46
the analyzer and, for this reason, 0.22 μm pore size PTFE syringe-driven filters were
used. After filtration, samples were directly injected and analyzed.
Figure 2.14. TOC analyzer (Tekmar Dohrmann
Phoenix 8000 UV-Persulfate TOC Analyzer).
Figure 2.15. Image of the Leco CHNS 932 analyzer
(a) and scheme of its different component parts (b).
2.09. UV-Visible Spectroscopy
The UV-Visible spectroscopy is commonly used due to its simplicity, versatility,
accuracy and cost-effectiveness. UV-Visible wavelengths cover a range from
47
approximately 10 nm (far UV irradiation) to 780 nm (visible irradiation). These energies
are sufficient to promote or excite a molecular electron to a higher energy orbital. For
this reason, absorption spectroscopy carried out in this region is also called "electron
spectroscopy". Figure 2.19 shows the different types of electronic transitions that may
occur in organic molecules.
The energy of a photon is defined as:
λ
hcE
Where h is the Planck’s constant, c is the speed of light in a vacuum and λ is the
wavelength. According to this equation, the energy of the photon decrease when the
wavelength increases. A photon energetically higher is necessary to excite a molecule
and promote an electron to another quantum state.
In a simple way, when a sample is irradiated by using a white light, this irradiation
could be totally reflected and in this case the sample looks white but if all irradiation is
totally absorbed the sample, in this case, looks black. Meanwhile, when only a portion of
the irradiation is absorbed and the remaining portion is reflected, the sample shows
different color. The color observed is the portion of the light reflected; a complementary
wavelength of the absorbed irradiation wavelength. Non-colored samples do not show
absorption spectrum in the UV-visible range, but can absorb in the IR portion of the
spectrum.
The atomic structure and the presence of color in a sample are closely related
because an electronic transition is necessary for the occurrence of the absorption. The
electronic promotion can occur from the ground state to different excited states. The
possible transitions can involve different orbitals (i.e. σ, π, n, σ* and π*) arising in
different electronic transitions (σ → σ*, n → σ*, n → π* and π → π*) (Figure 2.16). The
transition to the first excited state associated with the HOMO (highest occupied
48
molecular orbital) - LUMO (lowest unoccupied molecular orbital) excitation, is normally
characterized by having low energy and high intensity.
Possible Excited States
Ground States
σ
π
η
π*
σ*
(σ→σ*)
(π→π*)
(η→π*) (η→π*)
Inci
dent
Ra
diat
ion
Figure 2.16. Representation of the different electronic
transitions generated during the absorption process
under UV-Visible irradiation.
Molecular groups with conjugate insaturations produce a high effect in the
molecular absorption, increasing the λmax and the intensity of the peaks on the
absorption spectrum. The presence of chromophores (color-bearing molecular features)
which are functional groups not conjugated to other groups (i.e. nitro, azo, azo-amine,
carbonyl, etc) and auxochromes, such as OH, NH2, CH3 and NO2, have been suggested
to be responsible for important changes in the absorption spectrum. Other relevant
factors that can affect the absorption properties of a UV-Visible spectrum are the
presence of steric effects and the solvent used during the analysis.
The equation of Beer-Lambert correlates the absorption of a substance with the
concentration:
εcλA
49
Where ε is the molar absortivity, c is the concentration and λ is the wavelength. This
equation has the disadvantage that is true only for monochromatic light and if the
physical and chemical properties of the substance do not change with the change in
concentration.
Finally, during the analysis of a sample using a UV-vis spectrophotometer, the
pass of monochromatic light through the cell and the intensity of the transmitted light
depend both on the pathlength of the cell and the concentration. Transmittance is
defined as:
τclT
100log
I
IlogA;II 10
0
100
To characterize the absorption properties of our samples and to study the
catalytic degradation of the organic compounds we have used a UV-vis CARY 3 Varian
spectrophotometer.
2.10. Fluorescence Spectroscopy
The Fluorescence Spectroscopy is an important technique that has been used to
determine the degradation process of the organic compounds under different catalytic
processes studied along this research. This technique is complementary to the UV-vis
absorption technique.
This spectroscopy is based on the study of the different transitions between the
first excited singlet state and the ground state. Molecules in the ground state can be
excited by absorption of an appropriate wavelength photon, reaching different excited
states (S1*, S2*, etc). Two different mechanisms can be observed during desexcitation
process: i) molecules in higher excited states (i.e. S2*, S3*, etc) experience a rapid non
radiative internal conversion from these excited states to the S1*, and ii) molecules in the
first excited singlet state (S1*) experience a radiative desexcitation to the ground state,
namely fluorescence. Therefore, the fluorescence is a mechanism to relax an excited
50
molecule or atom to reach the ground state by emitting a photon. Nevertheless, there
are different alternatives to the light emission consisting in several radiationless
deactivation pathways from the S1* state. Among these deactivation processes are the
intramolecular internal conversion (S1* →S0), the intersystem crossing (S1* →Tn), as well
as the collisional quenching or resonance energy transfer, the most relevant [Albers et
al. 2003].
Frequently, the fluorescence bands are composed by bands at longer
wavelengths than the excitation wavelength. This process is known as Stokes
displacement but when no change in the wavelength occurs, the process is known as
fluorescence resonance. If the energy of absorbent during the absorption process,
represented in the excitation spectrum, is similar to the energy released during the
fluorescence process, both spectra are mirror images of each other. In this case, both
spectra are largely overlapping and the resonance line corresponds to the wavelength at
which these spectra cross each other. The fluorescence of a compound is affected by
the quantum yield, which depends on temperature, solvent polarity, molecular structure,
pH and concentration.
In this research, the samples have been characterized by fluorescence
spectroscopy to determine the possible degradation of the organic compound according
with the intensity of the maximum fluorescence emission. The fluorescence
spectroscopy analysis was performed at room temperature on a Varian Cary Eclipse,
using quartz cells of pathlength 1 cm (Figure 2.17).
51
Exclusion
Monochromator Sample
Emission
Monochromator
Detector
Polychromatic
UV-Vis Source
90
b)
a)
Figure 2.17. Image of the fluorescence
spectrophotometer Varian Cary Eclipse (a) and a
diagram of a fluorescence spectrometer (Adapted from
Albers et al. 2003).
52
Chapter Three
Synthesis Procedures
3.1. Synthesis of Titanium Oxide Nanowires
TiO2 nanowires (TiO2 NWs) have been synthesized by a novel catalyst-free
hydrothermal procedure. Uniform and size controllable TiO2 NWs have been obtained
by crystallization of the precursor in acid solution at high pressure and temperature. For
a typical synthesis, 75 mL of concentrated hydrochloric acid (Fisher Scientific, 35%) and
75 mL of DDW (Milli Q) were mixed in a 200 mL Erlenmeyer flask. After the solution has
cooled down to room temperature, 5 mL of the titanium precursor (titanium tetrachloride,
Aldrich Chemical) is added by dripping under agitation at room temperature. The
mixture was magnetically stirred until all solid particles were dissolved and the material
had a uniform color (approximately 10 min). After that, the solution was placed in 30 ml
Teflon-lined stainless steel autoclaves. Next, flat glass substrates of ca. 15 x 15 mm
(previously cleaned with isopropyl alcohol in an ultrasound bath for 5 min) were
introduced inside the autoclaves, in contact with the acid solution. Autoclaves were
maintained at 150ºC by 4 hours. After that, the autoclaves were left to cool down to
room temperature. The resulting TiO2 NWs grown on the surface of the glass substrates
were washed at least 5 times with DDW and dried overnight at 60 °C. After drying, the
TiO2 NWs were separated from the glass substrates and homogeneously pulverized to
facilitate the use in the catalytic tests. Finally, samples were transferred and stored in
sealed vials at room temperature.
53
3.2. Synthesis of Zinc Oxide
The synthesis procedure used for obtaining zinc oxide nanoparticles is based on
the procedure described by (Behnajady et al. 2011). In a typical synthesis, 0.2 mol of
Zn(CH3COO)2 (Aldrich, 98+% ACS Reagent) and 0.2 mol of NaOH (Fisher Scientific,
97+% ACS Reagent) were previously dissolved in a few milliliters of water and
subsequently added to a 200 mL Erlenmeyer flask. After that, 100 mL of ethanol (Acros
Organic, 95%) were added to the mixture. The solution was magnetically stirred at room
temperature for approximately 2 hr. The synthesized ZnO nanoparticles were separated
from the solution by centrifugation (7000 rpm) for 10 min, washed five times with
ultrapure water. Next, the powder was dried overnight at 60˚C and maintained in sealed
containers before characterization.
3.3. Synthesis of Titanium Oxide@Multiwalled Carbon Nanotubes
The synthesis of the multiwalled carbon nanotubes covered with titanium oxide in
rutile phase consists principally of two steps. The first one is the modification of the
carbon nanotubes to created actives sites (OH- groups) on the surface of the material.
The second one is the synthesis of the titanium oxide and the incorporation of the
material in the actives sites previously generated on the surface of the carbon
nanotubes.
3.3.1. Carbon Nanotubes Modification
Commercial multiwalled carbon nanotubes, MWNTs Cheap-tubes (95wt%) with
30 – 50 nm OD were modified to be used as support. In a typical synthesis, 5 g of
MWNTs were refluxed in concentrated nitric acid at 100 ºC for 24 hrs. After that, the
nanotubes were separated by centrifugation (6000 rpm, 10 min) and washed repeatedly
with DDW (Milli Q) until the pH rise to neutral. The nanotubes were dried at 60 °C and
maintained in sealed containers.
54
3.3.2. Synthesis and Incorporation of the Titanium Oxide on the MWCNT
The synthesis procedure mainly consists of the incorporation of a titanium oxide
precursor to an acid solution and the subsequent use of high pressure and temperature.
The synthesis of the TiO2 nanoparticles is produced on the surface of the modified
nanotubes. This growth is initiated exclusively on the OH groups generated during the
acid treatment of the carbon nanotubes, producing small particles whose dimensionality
will depends on the amount of titanium oxide precursor introduced into the reaction
mixture. In a fume hood, 75 mL of concentrated hydrochloric acid (Fisher Scientific,
35%) and 75 mL of DDW (Milli Q) are mixed and magnetically stirred in an Erlenmeyer
flask. When the reaction mixture cool down, 5 mL of the titanium oxide precursor
(titanium tetrachloride, Aldrich Chemical) were carefully added by dropwise. The mixture
was magnetically stirred until any solid particle was observed (approximately 10 min).
To synthesize TiO2 nanoparticles on the MWNTs surface, 0.5 g of the chemically
modified MWNTs were added to this reaction mixture and the solution was magnetically
stirred for 30 min. Next, this solution was transferred to 30 ml Teflon-lined autoclaves.
The autoclaves were closed and introduced in an oven for 4 hours at 150 °C. After
cooling down, the synthesized material, namely TiO2@MWNTs, was washed with DDW
(Milli Q) for at least 5 times and finally washed with ethanol. The product was dried
overnight at 60 °C.
3.4. Synthesis of Capped Magnetite Nanoparticles
Linoleic acid capped magnetite nanoparticles were obtained by following a
method previously published in our research group. Magnetite nanoparticles were
obtained by hydrothermal reaction of (NH4)2Fe(SO4)2 6H2O (Fisher Scientific, ACS
Certified) in the presence of KOH in water solution. Ammonium iron sulphate (6 mmol)
was dissolved in 150 mL of distilled water (Milli Q) and this solution was added to 40
mmol of KOH (Aldrich, 99.99%) in 25 mL of distilled water. Next, ammonium
55
peroxodisulfate (5 mmol) dissolved in 25 mL of water was added to a mixture formed by
toluene (Fisher Scientific, ACS Certified) and isopropyl alcohol (Acros Chemical, 99.8%,
HPLC) (4:1, v/v) with 3 mL of linoleic acid (Fisher Scientific, NF/FCC). This solution was
added to the reaction mixture. The reaction was carried out under reflux for 8 hours.
Then, the reaction mixture was cooled to room temperature and the organic phase
containing the solubilized Fe3O4 nanoparticles was separated. Fe3O4 nanoparticles were
precipitated with ethanol followed by centrifugation. The magnetite nanoparticles were
cleaned with nitric acid (Fisher Scientific) (1 M) and subsequently washed with distilled
water an ethanol, and dried overnight at 50 ºC.
3.5. Synthesis of Iron Oxide Nanowires
Highly crystalline iron oxide nanowires were synthesized by a simple catalyst-
free growth procedure. For the synthesis of the iron oxide nanowires a Chemical Vapor
Deposition (CVD) system was used (Figure 3.01). The pure iron substrates
(Goodfellow, 99.999%) were thermally treated inside a quart tube furnace at
temperatures ranging from 400 to 600 °C in a controlled atmosphere (vacuum and
oxidative/reductive atmosphere). A thermal rampage (400 to 600 °C) was used for the
synthesis (Bonilla et al. 2011).
56
a) b)
c)
Figure 3.01. Image of the CVD system (a and b) and scheme of the CVD
system and thermal treatment (c) used for the synthesis of Fe2O3
nanowires (Adapted from Bonilla et al. 2011).
57
Chapter Four
Material Characterization
The full characterization of the catalysts used for the different reactions
(photocatalysis, sono-Fenton and photo-Fenton) is described in this section, including
the synthesized and commercial catalysts. As shown in earlier chapters, a variety of
analytical techniques have been used for the characterization of the materials, including
FE-SEM, XRD, TG and Raman. The analysis by magnetometry was only applied to
samples with iron in different oxidation states.
4.1. Photocatalysis
4.1.1. Titanium Oxide (TiO2, Rutile Phase)
The use of titanium oxide as a photocatalyst is very common because it is
nontoxic, photostable and has a high oxidant power, but its activity is limited to the UV
region of the spectrum (Velegraki and Mantzavinus 2008; Yu et al. 2009). According to
Hernandez-Enriquez et al. (2008), the specific area of the titanium oxide is related with
the quantity of acid used during the synthesis procedure. According to Hernandez-
Enriquez et al. (2008) the efficiency of the titanium oxide in the photocatalytic reactions
is due to both the specific area of the material and stability of the crystalline phase.
The titanium oxide (rutile phase) is a commercial catalyst (Alfa Aesar, 97%). The
rutile phase has a tetragonal structure with six oxygen atoms around octahedral
arrangement (Garriga I Cabo 2007; Bae et al. 2009). The specific surface area, as
determined by the BET method, was 41 m2 g-1. According with the information obtained
from FE-SEM micrographs (50 000x and 20 kV), the particles of rutile were smaller than
1 μm (Figure 4.01) and apparently do not show porosity.
58
Figure 4.01. FE-SEM image of the titanium oxide
(rutile phase) at a magnification of 50 000x.
The TG analysis confirmed the information of the SEM. In TiO2 (Rutile) only 11%
of weight lost was observed (Figure 4.02). The weight lost is a two-steps process, the
first step is due the absorbed water and the second step could be attributed to the
removal of the hydroxyl groups of the titanium oxide (Niederberger et al. 2002).
0 100 200 300 400
90
92
94
96
98
100
We
igh
t L
oss (
%)
Temperature (oC)
TiO2-Rutile
Weight Loss-11%
Figure 4.02. TGA scan of titanium oxide (rutile
phase).
59
In the Raman spectrum (Figure 4.03) two characteristics peaks of titanium oxide
were present (at 450.83 and 608.83 cm-1) corresponding to the rutile phase (Jackson
2004).
200 400 600 800 1000 1200
Inte
nsity (
a.u
.)
Raman Shift (cm-1)
TiO2-Rutile608.83450.83
Figure 4.03.Raman spectrum of TiO2 sample
(rutile phase).
This catalyst was also characterized by XPS. A very intense peak at 530.01 eV
was observed in the XPS spectrum of the rutile sample (Figure 4.04) (Fundamental XPS
Data 1999). This peak has been associated with the oxygen atoms in the lattice (Liu et
al. 2008) of the TiO2. Figure 4.05 shows an intense band at 457.26 eV that has been
unambiguously ascribed to Ti2p(1/2) corresponding to Ti4+ ions of the crystalline lattice.
This catalyst was also characterized by XRD. The diffractograms obtained for
this sample (rutile phase) show reflections at 27 °, 36 °, 41 °, 44 ° and 57 ° (Figure
4.06b) (Hernandez Enriquez et al. 2008).
60
534 533 532 531 530 529 528 527 526
O1s TiO2-Rutile
CP
S
Binding Energy (eV)
530.01
(O1s)
Figure 4.04. XPS spectrum corresponding to
the O1s region of the TiO2 catalyst (rutile
phase).
475 470 465 460 455 450
CP
S
Binding Energy (eV)
457.26
(2p1/2
)
463.12
(2p3/2
)
Figure 4.05. XPS spectrum corresponding to the
Ti2p region of the TiO2 catalyst (rutile phase).
61
0 10 20 30 40 50 60 70
Inte
nsity (
cp
s)
2 Theta (Degree)
TiO2NWs
TiO2@MWCNTs
TiO2-Rutile
TiO2-Anatase
(a)
(b)
(c)
(d)
(101)
(004)
(200)(105)
(211)(116)
(110)(101)
(111)
(211)
(220)
(002)
(210)
Figure 4.06. XRD diffraction patterns for TiO2-Anatase (a), TiO2-Rutile (b),
TiO2NWS (c) and TiO2@MWCNTs (d).
4.1.2. Titanium Oxide (TiO2, Anatase Phase)
The titanium oxide (anatase phase) is a commercial catalyst. Some drawbacks
of the titanium oxide include the strong absorption capacity of the pollutant or the
intermediate on the actives sites and the fact that the optimal irradiation for anatase is
shorter than 387 nm (Ma et al. 2007; Rahmani et al. 2008). The anatase phase has a
tetragonal structure; six oxygen atoms around one titanium atom in an octahedral
structure (Bae et al. 2009, Garriga I Cabo 2007) with a band gap energy of 3.2 eV
(Rahmani et al. 2008). Anatase is characterized by having a high photoactivity, optimum
band gap, and additionally, this catalyst is easy to synthesize (Vinu and Madras 2009).
The specific surface area (Sarea), as determined using the BET method, was 48
m2 g-1. The FE-SEM images of the anatase catalyst (Figure 4.07) shows the small size
of the particles (less than 1 μm) and the presence of small aggregates. Smaller particles
or the presence of additional porous structure could not be observed. According with the
62
TG analysis, the aggregates of the anatase particles could loss approximately the 27.8%
of their weight (Figure 4.08). This weight lost could be due to the water removal,
possibly water molecules absorbed on the particle surface.
Figure 4.07. FE-SEM image of the titanium
oxide (anatase phase) at a magnification of
50 000x.
0 100 200 300 400 500
70
75
80
85
90
95
100
We
igh
t L
oss (
%)
Temperature (oC)
TiO2- Anatase
Weight Loss 27.84%
Figure 4.08. TGA scan of titanium oxide
(anatase phase).
The nondestructive technique of Raman was applied to elucidate the
characteristics of the materials (Zhou et al. 2006). In the Raman spectra (Figure 4.09) is
63
clearly identified the most characteristics peaks of the anatase phase (393.36, 512.59
and 638.05 cm-1) revealing that no other phases were present (Jackson 2004).
0 200 400 600 800 1000 1200
Inte
nsi
ty (
a.u
.)
Raman Shift (cm-1)
TiO2-Anatase
638.05
512.59393.36
Figure 4.09. Raman spectrum of titanium
oxide catalyst (anatase phase).
Anatase was also characterized by XPS. At 457.52 eV was observed the most
characteristic peak of this catalyst that was ascribed to Ti2p(3/2) (Figure 4.10). The peak
observed at 463.26 eV was ascribed to Ti2p(1/2) (Fundamental XPS Data 1999). The
Figure 4.11 shows the XPS spectrum corresponding to the O1s. As can be seen there,
this peak appears at 528.80 eV and has been ascribed to the oxygen atoms in the lattice
(Liu et al. 2008) of anatase (Fundamental XPS Data 1999).
64
CP
S
Binding Energy (eV)
Ti2p TiO2-Anatase
470 465 460 455
457.52
(2sp1/2
)
463.26
(2p3/2)
450
Figure 4.10. XPS spectrum of Ti2p
peak on titanium oxide (anatase phase).
534 532 530 528 526
O1s TiO2-Anatase
CP
S
Binding Energy (eV)
529.99
(O1s)
Figure 4.11. XPS spectrum of TiO2
showing the O1s transition (anatase
phase).
The XRD pattern (Figure 4.06) of anatase was characterized by having different
peaks at 30.93°, 36.44°, 42.77°, 53.73°, 56.72° and 62.65°, corresponding to (101),
(004), (200), (105), (211) and (116) reflections, respectively (Chowdhury et al. 2005).
According to Hernandez Enriquez et al. (2008) the diffraction peaks that characterize the
tetragonal phase of anatase are: 25 °, 37 °, 48 °, 54 °, 55 °, 62 °, 71 ° and 75 °.
65
4.1.3. Titanium Oxide Nanowires
The titanium oxide nanowires (TiO2NWs) were synthesized according with the
procedure described in Chapter 3 - Material Synthesis. Figure 4.12 shows different
images obtained by FE-SEM of this catalyst. The wires are composed by smaller wires
of nanometric dimensions (Figure 4.12). The specific surface area (Sarea), as determined
by the BET method, was 480 m2 g-1. This value is unexpectedly high and could have
relevant effects on the catalytic properties of this material.
Figure 4.12. FE-SEM images of the as-synthesized
TiO2NWs at different magnification: 5000x (a), 10 000x (b),
25 000x (c) and 150 000x (d).
Figure 4.13 shows the TG analysis of the as-synthesized TiO2NWs. Only a
weight loss of 5.65% was observed during the heating process, indicating the compact
and non-porous structure of the nanowires.
66
0 50 100 150 200 250 300 350 400
90
100
We
igh
t L
oss (
%)
Temperature (oC)
TiO2NWs
Weight Loss 5.65%
Figure 4.13. TGA analysis of the as-
synthesized TiO2NWs.
Raman spectrum of TiO2NWs (Figure 4.14), is characterized by having two
peaks at 440.83 cm-1 and 604.73 cm-1, respectively, that have been ascribed to titanium
oxide as rutile phase (Jackson 2004).
TiO2NWs were also characterized by XPS. The obtained XPS spectra were
similar to those previously obtained for TiO2 as rutile or anatase phase. The peaks
observed at 457.39 eV and 462.98 eV were associated to the Ti2p(3/2) and Ti2p(1/2)
transitions, respectively (Figure 4.15) (Fundamental XPS Data 1999). The XPS peak
corresponding to O1s was observed at 529.80 eV and it was assigned to the oxygen
atoms in the lattice (Figure 4.16) (Liu et al. 2008) (Fundamental XPS Data 1999). As can
be seen there, this peak is not symmetric and could be deconvolved in two components.
An additional peak could appear at ca. 532 eV and could be ascribed to the presence of
CO2 and other species adsorbed on the surface of the TiO2NWs.
67
200 400 600 800 1000 1200
Inte
nsi
ty (
a.u
.)
Raman Shift (cm-1)
TiO2NWs
440.83
604.73
Figure 4.14. Raman spectrum of the as-
synthesized TiO2NWs.
CP
S
Binding Energy (eV)
TiO2NWs
457.39
(2p1/2
)
462.98
(2p3/2
)
450455460465
Figure 4.15. XPS spectrum of Ti2p region of
the as-synthesized TiO2NWs.
68
540 538 536 534 532 530 528 526 524C
PS
Binding Energy (eV)
O1s TiO2NWs529.80
(O1s)
Figure 4.16. XPS spectrum of O1s region
of the as-synthesized TiO2NWs.
XRD diffraction pattern of the titanium oxide nanowires synthesized and used as
catalyst is shown in Figure 4.06. As can be seen there, the rutile phase with reflections
at 27 °, 36 °, 41 °, 44 ° and 57 ° is the only crystalline phase observed in this catalyst
(Hernandez Enriquez et al. 2008; Cotto et al. 2011). The narrow sharps peaks indicate
the crystalline structure of the nanowires (Li and Liu 2010).
4.1.4. Titanium Oxide @Multiwalled Carbon Nanotubes
The principal forms are: vitreous carbon, carbines, fullerenes and nanotubes
(Ansón-Casaos 2005). In this research, the multiwalled carbon nanotubes were coated
with particles of titanium oxide in rutile phase (TiO2@MWCNTs) (Figure 4.17). The
synthesis of this material has been carried out according to the experimental procedure
described in Chapter 3 – Materials Synthesis. Other forms to prepare the TiO2@CNTs
include different techniques as, for instance, the electrospray deposition (Doi et al.
2009). The starting material, namely MWCNTs, is forming small clusters or aggregates
whose dimensions can be reduced by treating in ultrasound baths (Bal 2010). After
functionalization treatments of the CNTs the authors observed reduction in the average
length, sidewall disordering and extensive debundling (Wang et al. 2006). The use of
69
MWCNTs as supporting catalyst structure is relevant because some investigations
reveal the flow of photogenerated electrons from the conduction band of the TiO2 to the
carbon nanotubes (Garriga I Cabo 2007).
TiO2@MWCNTs were characterized by FE-SEM (Figure 4.17). As can be seen
there, there are aggregates and clusters of carbon nanotubes coated by TiO2.
Additionally, the presence of small aggregates composed exclusively of TiO2, as
determined by EDX analysis, can also be observed (arrows in Figure 4.17).
Figure 4.17. FE-SEM image of the as-synthesized
TiO2@MWCNTs at a magnification of 5000x. Arrows
correspond to the presence of small clusters of TiO2, as
determined by EDX analysis.
The specific surface area of this hybrid material (Sarea), determined by the BET
method, was 620 m2 g-1. This high surface area implies that this material could have
interesting applications in different catalytic processes. The TG analysis of this material
shows that approximately the 25.27% of weight is lost during the thermal process
(Figure 4.18). This high weight loss indicates that this is a porous material, as it was
70
stated from the BET analysis. The interior of the porous structure can contain adsorbed
water or any other chemical substance as a residual of the synthesis.
0 100 200 300 400 500 600
65
70
75
80
85
90
95
100
We
igh
t L
oss
(%
)
Temperature (oC)
TiO2@MWCNT
Weight Loss 25.27%
Figure 4.18. TGA analysis of the as-
synthesized TiO2@MWCNTs.
Raman spectroscopy plays an important role in the research on carbon
nanotubes because the signals observed in the spectra clearly depend on different
structural parameters, including the diameter and the metallic or semiconductor
character of the nanotubes (Anson Casaos 2005). Raman spectrum obtained from this
hybrid material (TiO2@MWCNTs) (see Figure 4.19) confirmed the presence of TiO2
(rutile phase) on the surface of the multiwalled carbon nanotubes. The two peaks at
444.32 and 603.69 cm-1 are characteristics of the rutile phase (Jackson 2004). The
presence of several peaks ranging from ca. 100 to 300 cm-1 indicates the presence of
carbon nanotubes. According to Anson Casaos (2005), Raman spectra of carbon
nanotubes are characterized by having different peaks at very low Raman shifts (radial
breathing mode or RBMs, at around 150 cm-1), and other modes including the tangential
mode, TMs or G band (approx. 1600 cm-1), D band (approx. 1300cm-1) and the G band
(around 2600cm-1), that are not shown in Figure 4.19.
71
200 400 600 800 1000 1200
Inte
nsity (
a.u
.)
Raman Shift (cm-1)
TiO2@MWCNTs
603.69
444.32
Figure 4.19. Raman spectrum of the as-
synthesized TiO2@MWCNTs.
TiO2@MWCNTs was also characterized by XPS. The Figure 4.20 shows the
XPS spectrum corresponding to the C1s region. As can be seen there, C1s transition
shows only a peak at 284.79 eV that has been ascribed to the C1s of the MWNTs (sp2-
hybridized carbon). The presence of adsorbed carbon (CO2 or hydrocarbons) was
practically undetected. The Figure 4.21 shows the XPS spectrum corresponding to the
Ti2p regions. The Ti2p transition is characterized by having the main peak at 457.43 eV
and a secondary peak at ca. 463.04 eV that have been ascribed as Ti2p(3/2) and Ti2p(1/2),
respectively, being in agreement with the expected peak positions for the rutile phase.
The Figure 4.28 shows the XPS spectrum corresponding to the O1s region. As can be
seen there, only a peak at ca. 532.39 eV is observed, being assigned to the oxygen at
the TiO2 lattice (Zhou et al. 2006). Figure 4.22 demostrated the presence of other O1s
atoms, possible attached to the carbon portion of the MWCNTs.
72
294 292 290 288 286 284 282 280
CP
SBinding Energy (eV)
C1s TiO2@MWCNTs
284.79
(C1s)
Figure 4.20. XPS spectrum corresponding to the
C1s region of the as-synthesized TiO2@MWCNTs
catalyst.
CP
S
Binding Energy (eV)
TiO2@MWCNTs
457.43
(Ti2p1/2
)
463.04
(Ti2p3/2
)
470 465 460 455 450
Figure 4.21. XPS spectrum corresponding to the
Ti2p region of the as-synthesized
TiO2@MWCNTs catalyst.
73
536 534 532 530 528 526C
PS
Binding Energy (eV)
O1s TiO2@MWCNTs
530.05
(O1s)
Figure 4.22. XPS spectrum corresponding to
the O1s region of the as-synthesized
TiO2@MWCNTs catalyst.
This catalyst has been characterized by XRD (Figure 4.06). The presence of a
broad peak ranging from 20° to 35° can make difficult the identification of the peaks
(Figure 4.06). Some of the characteristics peaks that identify the rutile phase and their
lattice planes were observed in this sample (Hernandez Enriquez et al. 2008; Cotto et al.
2011).
4.1.5. Zinc Oxide
Zinc oxide was synthesized according with the experimental procedure described
previously in the Chapter 3-Material Synthesis. ZnO nanoparticles have been
extensively used as catalysts and in a wide range of applications including: gas sensors,
cosmetics, as anti-virus agents, in the development of piezoelectric transducers, solar
cells and transparent electrodes, etc. (Hong et al. 2009; Sridevi and Rajendra 2009).
The ZnO nanoparticles used in cosmetics could be harmful to people because they can
generate OH radicals, which can affect the cells (Hong et al. 2009). Different synthesis
methods including sol-gel, hydrothermal, homogeneous precipitation, mechanical milling,
74
organometallic synthesis, thermal evaporation, etc. have been used for the synthesis of
this nanomaterial (Hong et al. 2009; Sridevi and Rajendra 2009). Other additional
methods for the synthesis of ZnO are the precipitation and calcination of different
precursors (Hong et al. 2009). ZnO is an important semiconductor, as the TiO2 (Hong et
al. 2009), having a wide band gap of 3.37 eV (Sridevi and Rajendra 2009). ZnO
nanoparticles were characterized by FE-SEM (Figure 4.23). As can be seen there, ZnO
nanoparticles are characterized by having irregular forms and dimensions ranging from
several hundred nanometers to no more than one-micrometer length.
Figure 4.23. FE-SEM images of the as-synthesized ZnO particles at
different magnification: 25 000x (a), 50 000x (b).
According with the TG curve (Figure 4.24), the weight-loss was approximately
25.27% and possibly corresponds to the loss of water and the removal of surplus
reagents. The specific surface area (Sarea), as determined by the BET method, was 68
m2 g-1.
75
100 200 300
70
80
90
100
We
igh
t L
oss
(%
)Temperature (
oC)
ZnO
Weight Loss 25.27%
Figure 4.24. TG curve of the as-synthesized
ZnO particles.
Raman spectrum of the as-synthesized ZnO particles (Figure 4.25) shows two
relevant peaks at 326.15 cm-1 and 436.72 cm-1. Both peaks are characteristic of the
ZnO catalyst (Jackson 2004).
200 400 600 800 1000 1200
Inte
nsi
ty (
a.u
.)
Raman Shift (cm-1)
ZnO
436.72
326.15
Figure 4.25. Raman spectrum of the as-
synthesized ZnO particles.
76
Figure 4.26 shows the XRD diffraction pattern of the as synthesized ZnO
catalyst. The most characteristic crystallographic lattice planes are present in the
diffragtogram (Hong et al. 2009; Sridevi and Rajendran 2009) and correspond to
reflections of the hexagonal phase (Sridevi and Rajendran 2009).
0 10 20 30 40 50 60 70 80 90
0
500
1000
1500
2000
2500
3000
Inte
nsity (
cp
s)
2 Theta (Degree)
ZnO-as synthesized
(100)
(002)
(101)
(103)(110)
Figure 4.26. XRD diffraction pattern of the as-
synthesized ZnO particles.
4.2. Fenton Catalysts
4.2.1. Iron Oxide Nanowires (Fe2O3NWs)
Iron Oxide Nanowires (Fe2O3NWs) were synthesized according with the
procedure previously described (Chapter 3-Material Synthesis). FE-SEM images of the
as-prepared samples are shown in Figure 4.27. The iron oxide nanowires are
characterized by being formed by filaments very long and extremely thin. Nevertheless,
the Fe2O3NWs become coarser under increasing the temperature (above 600 ºC),
indicating the temperature effect on the morphologies of these nanostructures. The BET
method reveals an unexpectedly high specific surface area (Sarea) of 180 m2 g-1.
77
Figure 4.27. FE-SEM images of the as-synthesized iron oxide nanowires
(Fe2O3NWs) at different magnification: 1000x (a), 2000x (b) and 5000x (c).
TG analysis revealed only a weight loss of 3.62% at 520 ºC (Figure 4.28),
indicating that iron nanowires do not possess porosity able to absorb a measurable
quantity of water and other solvents.
0 100 200 300 400 500 600
90
92
94
96
98
100
We
igh
t L
oss
(%
)
Temperature (oC)
Fe2O
3NWs
Weight Loss 3.62%
Figure 4.28. TG curve of raw Fe2O3NWs.
78
Iron oxide nanowires were also characterized by XPS. Figure 4.29 shows the
XPS spectrum of the Fe2p region. As can be seen there, two relevant peaks at 711.02
eV and 724.74 eV have been assigned to the Fe2p(3/2) and Fe2p(1/2) transitions,
respectively. Binding energies observed for the Fe2p region are in agreement with the
presence of Fe3+ atoms of the oxide (Garriga I Cabo 2007). Figure 4.30 corresponds to
the O1s XPS region. As can be seen there, a main peak at 529.80 eV was measured,
being assigned to the oxygen atoms of the iron oxide. On the other hand, an additional
peak appears in this region. At ca. 532 eV a very low intense peak is observed and
possibly could be due to the presence of structural defects on the nanowire surface
(Fundamental XPS Data 1999).
740 730 720 710 700
Fe2p Fe2O
3NWs
CP
S
Binding Energy (eV)
711.02
(2p3)724.74
(2p1)
Figure 4.29. XPS spectrum corresponding
to the Fe2p region of the as-synthesized
Fe2O3NWs.
Raman spectrum of Fe2O3NWs was also analyzed during this research (Figure
4.31). As can be seen there, two main peaks at low Raman shift (ca. 210 and 276 cm-1)
have been measured. Both peaks were ascribed to Fe-O vibrations (Chandra et al.
2010).
79
540 538 536 534 532 530 528 526 524C
PS
Binding Energy (eV)
O1s TiO2NWs529.80
(O1s)
Figure 4.30. XPS spectrum corresponding
to the O1s region of the as-synthesized
Fe2O3NWs.
200 400 600 800 1000 1200
Inte
nsity (
a.u
.)
Raman Shift (cm-1)
Fe2O
3NWs
Figure 4.31. Raman spectrum of as-
synthesized Fe2O3NWs.
80
Magnetic properties of as-synthesized Fe2O3NWs were also analyzed. Figure
4.32 shows the hysteresis loop of the iron nanowires. The coercivity value obtained for
this material was 20.485 G, with saturation magnetization (Ms) of 22.376 emu g-1,
indicating a high ferromagnetic behavior (Wu et al. 2010).
-30000 -20000 -10000 0 10000 20000 30000
-30
-20
-10
0
10
20
30
Mo
me
nt/M
ass(e
mu
/g)
Field(G)
nanowires Fe
Coercivity (Hci):20.485 G
Magnetization (Ms): 22.376 emu/g
Figure 4.32. Magnetic susceptibility of as-
synthesized Fe2O3NWs, measured at room
temperature.
This material was also characterized by XRD. Two XRD diffraction patterns are
observed in Figure 4.42, corresponding to the reflections measured when this material is
synthesized in oxidative atmosphere (flowing oxygen) at 600 ºC (Figure 4.33a) and
700 ºC (Figure 4.33b). As can be seen there, some small differences can be observed
as a function of the synthesis temperature, demonstrating possible changes in the
structure (phase), crystallinity and density of the materials (Bonilla et al. 2011). Iron
oxide as hematite phase (α-Fe2O3) was not observed, due to the lack of peaks
corresponding to reflections (210) and (211), that are always present in this
crystallographic phase (Daou et al. 2006).
81
40 60
a
2Theta (Degree)
b
220400
422
511
440320 300
110
221
Figure 4.33. XRD diffraction patterns of
Fe2O3NWs synthesized at 600 °C (a) and
700 °C (b) at atmospheric pressure and in
flowing oxygen.
4.2.2. Capped Magnetite Nanoparticles (Fe3O4)
The hematite, magnetite and maghemite are different crystallographic phases of
iron oxides with different types of magnetic transitions (Wu et al, 2010). The magnetite
is an iron oxide in an invert spinel , composed by Fe2+ and Fe3+ and is relevant because
it can be used in a vast range of different applications, including biomedical uses,
catalysis, fine chemistry, development of batteries, magnetic recorders, etc. (Daou et al.
2006). Several important questions in the magnetite synthesis are the cationic
distribution and vacancies in the structure, the stoichiometry variation during the reaction
and spin canting (Daou et al. 2006). During a typical synthesis procedure the Fe2+ and
Fe3+ ions are present in the solution, reacting with the base and the final intermediates
and producing the magnetite phase, according to the following reactions (Nyiro-Kosa et
al. 2009):
Fe2+ + 2OH- → Fe(OH)2
82
Fe3+ + 3OH- → FeO(OH) + H2O
Fe(OH)2 + 2FeO(OH) → Fe3O4 + 2H2O
During the last few years, the synthesis of different materials based in magnetites
has experienced an important increase. One example is the use of magnetite over
graphene oxide to bind heavy metal pollutants as arsenic, with relevant applications in
water remediation processes (Chandra et al. 2010). Many synthesis procedures, with
different reagents as ferric chloride, ferrous chloride and ferric sulfate have been
established for the synthesis of magnetites with different sizes (from nanoparticles with
very low diameters to micro and macroparticles) under different pH conditions,
temperature and reaction times (Nyiro-Kosa et al. 2009). Some of the most common
synthesis methods for obtaining magnetites include the synthesis by coprecipitation
using ferric and ferrous compounds and different hydrothermal approaches (Daou et al.
2006; Daou et al. 2007; Wu et al. 2010). The magnetic materials are synthesized in
many structural forms, as nanoclusters, nanoparticles, hollow nanoparticles, nanorings,
nanocapsules, and nanowires (Wu et al. 2010). The magnetite (Fe3O4) and maghemite
(γ-Fe2O3) have many technological applications; the hematite (α-Fe2O3) is used as
catalyst, pigment and gas sensor (Wu et al. 2010) and emerges as a relevant material in
the nanotechnology.
The capped magnetite nanoparticles (Fe3O4) were synthesized according with
the experimental procedure described previously (Chapter 3 - Material Synthesis). The
specific surface area (Sarea) of this material, determined using the BET method, was 97
m2 g-1. FE-SEM images of this material are shown in Figure 4.34. At very low
magnification (30x) the material is characterized by forming large aggregates (Figure
4.34a). At larger magnifications (2 000x), it is possible to distinguish very small particles
forming these aggregates (Figure 4.34b). The Figure 4.34c shows a TEM image of the
capped magnetites previously disaggregated in ethanol by using a soft ultrasound
83
treatment for 15 min. As can be seen there, these particles have sizes of no more than
5 nm-diameter.
Figure 4.34. FE-SEM images of the as-synthesized capped
magnetite nanoparticles (Fe3O4) at different magnification 30x
(a) and 2000x (b). TEM image of the capped magnetite
nanoparticles (Fe3O4) previously disaggregated in ethanol (c).
Capped magnetite nanoparticles (Fe3O4) were also characterized by XPS. The
Figure 4.35 shows the XPS spectrum of the Fe2p region. As can be seen there, two
peaks arising from the Fe2p splitting are observed. Both peaks have been
unambiguously assigned to Fe2p(3/2) (724.1 eV) and Fe2p(1/2) (710.9 eV), and their
binding energies correspond to iron in magnetite phase. Figure 4.36 shows the XPS
spectrum corresponding to the O1s region. As can be seen there, only a peak at ca.
531.1 eV has been measured, corresponding to oxygen in the lattice of the magnetite
phase.
Raman spectrum of the as-synthesized capped magnetite nanoparticles is shown
in Figure 4.37. Several peaks ranging from ca. 200 to 400 cm-1, and an intense peak at
84
ca. 980 cm-1 were measured and assigned to typical Fe-O vibrations corresponding to
the magnetite phase (Marquez et al. 2012).
740 730 720 710 700 690
2.00E+013
4.00E+013
6.00E+013
8.00E+013
1.00E+014
1.20E+014
O1sFe3O4
Binding Energy (eV)
CP
S
Fe3O4
Fe2p (3/2)
Fe2p
(1/2)
Figure 4.35. XPS spectrum corresponding to the
Fe2p region, of the as-synthesized capped
magnetite nanoparticles (Fe3O4).
540 538 536 534 532 530 528 526 524
CP
S
Binding Energy (eV)
O1s
Figure 4.36. XPS spectrum corresponding to
the O1s region, of the as-synthesized capped
magnetite nanoparticles (Fe3O4).
85
200 400 600 800 1000 1200
Inte
nsity
(a.
u.)
Raman Shift (cm-1)
Fe3O
4
Figure 4.37. Raman spectrum of as-
synthesized capped magnetite
nanoparticles.
Figure 4.38 shows the magnetometry study of the synthesized magnetites as a
function of the reaction temperature. The saturation magnetization (Ms) values
experienced important variations depending on the synthesis temperature.
0 -20000 -10000 0 10000 20000 0
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
Mo
me
nt/M
ass
(em
u/g
)
Field(G)
70C
80C
90C
100C
110C
Figure 4.38. Temperature effect on the
magnetic properties of the magnetites at
different temperatures.
86
The lack of coercivity demonstrated the paramagnetic properties of the magnetite
particles (Marquez et al. 2012). The sample with higher paramagnetic properties is that
synthesized at 100 °C.
4.2.3. Ferrous Chloride (FeCl2)
Ferrous chloride (FeCl2, Fisher Scientific, 99%) was used during this
investigation as catalyst. During the TG analysis, the FeCl2 loss approximately the
16.14% of its weight (Figure 4.39). Only one step was observed in the TG curve and
this weight loss could be attributed to the removal of water molecules adsorbed on the
surface of this reagent (Niederberger et al. 2002). The specific surface area (Sarea), as
measured by using the BET method, was 55 m2 g-1.
0 100 200 300 400 500
82
84
86
88
90
92
94
96
98
100
We
igh
t L
oss (
%)
Temperature (oC)
FeCl2
Weight Loss 16.14%
Figure 4.39. TG curve of the ferrous
chloride.
This reagent was also characterized by XPS. Figure 4.40 shows the XPS region
corresponding to Cl2p. As can be seen there, a peak at 198.18 eV, assigned to Cl-, was
observed (Handbook of the Elements 1999). The Fe2p XPS region was also analyzed.
As can be seen in Figure 4.41, two peaks at ca. 710.9 eV and 724.8 eV were measured,
being ascribed to Fe2p(3/2) and Fe2p(1/2) transitions, respectively (Fundamental XPS Data
87
1999). Figure 4.42 shows the XRD diffraction pattern of the FeCl2 catalyst. All measured
reflections are in agreement with those expected for this compound.
204 202 200 198 196 194 192
FeCl2
CP
S
Binding Energy (eV)
198.18
(2p3)Cl
Figure 4.40. XPS spectrum corresponding to
the Cl2p region of FeCl2 catalyst.
730 725 720 715 710
Fe FeCl2
CP
S
Binding Energy (eV)
710.93
(2p1/2
)
724.66
(2p3/2
)
Figure 4.41. XPS spectrum corresponding to
the Fe2p region of FeCl2 catalyst.
88
0 10 20 30 40 50 60 70 80 90
-500
0
500
1000
1500
2000
2500
3000
3500
4000
Inte
nsity (
cp
s)
2 Theta (Degree)
FeCl2
Figure 4.42. XRD diffraction pattern of the FeCl2
catalyst.
4.2.4. Copper Oxide (CuO)
Cupric oxide (CuO) (JT Baker, Baker Analyzed Reagent) was used during the
investigation as one of the Fenton catalysts. The FE-SEM images of this compound
(Figure 4.43) revealed the presence of clusters or aggregations, showing particles with
irregular forms and particle sizes ranging from lesser than 1 micrometer to more than 3-4
micrometers. A weight loss of ca. 25.27% (ranging from RT to 575 oC) was observed
during the TG analysis of the sample (Figure 4.44), that could be attributed to the
removal of water molecules adsorbed on the material (Niederberger et al. 2002). The
specific surface area (Sarea), as determined using the BET method, was 32 m2 g-1
indicating that this compound does not have relevant porous structure (as was also
observed by FE-SEM).
89
Figure 4.43. FE-SEM images of CuO at different magnification: 5000x
(a) and 25 000x (b).
0 100 200 300 400 500 600
60
65
70
75
80
85
90
95
100
We
igh
t L
oss (
%)
Temperature (oC)
CuO
Weight Loss 25.27%
Figure 4.44. TG curve of the cupric oxide
catalyst.
The XRD diffraction pattern of the CuO catalyst is shown in Figure 4.45. The
most intense peaks, ascribed to the characteristic reflections of crystalline CuO, were
observed at 35.52°, 38.55°, 48.18° and 61.57° (Yang et al. 2010).
90
0 10 20 30 40 50 60 70 80 90
0
2000
4000
6000
8000
10000
12000
Inte
nsity (
cp
s)
2 Theta (Degree)
CuO
48.18o
38.55o
35.52o
61.57o
Figure 4.45. XRD diffraction pattern of the
CuO catalyst.
91
Chapter Five
Results and Discussion
5.1. Defining the Experimental Parameters
At the beginning of the investigation it was necessary to determine the optimal
parameters for the degradation processes. The parameters studied were the
concentration of the catalyst, the pH and the temperature of the solution. The selected
dye and catalyst that were used to establish the optimal parameters were Rhodamine B
and titanium oxide in anatase phase, respectively.
5.1.1. Effects of the Concentration
For the study of the effects of the concentration of catalyst in the photochemical
degradation process, different concentrations of the catalyst (anatase) were added to a
reaction mixture containing Rhodamine B (RhB, 10-5 M). The photocatalytic process
was carried out using the procedure established previously. The Figure 5.01 shows the
effects of the catalyst concentration on the degradation process. As expected, a
maximum photodegradation was observed in a low concentration range of the catalyst
(0.6 – 0.9 gL-1). Under these reaction conditions near the 100% of degradation was
produced. At higher concentration of catalyst, the photocatalytic process was inefficient
due possibly to the poor dispersion of the catalyst in the solution that increased the
turbidity, reducing the contact between the catalyst and the reaction mixture. Previous
studies (Velegraki and Mantvinos 2008) revealed that no significant changes in the
photodegradation process were observed when the catalyst was increased from 0.6 gL-1
to 0.8 gL-1. Nevertheless, when the concentration of the catalyst increases to 1.0 gL-1 or
more, a slight decrease in the photocatalytic conversion is observed.
92
The results could be explained according the results of Lodha et al. (2008). The
authors (Lodha et al. 2008) concluded that when the concentration of the dye
increases, more molecules of the dye are present in the reaction system and this high
concentration increases the opacity of the solution avoiding the pass of light through the
water column and decreasing the degradation rate.
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
60
80
100
% P
ho
to-d
eg
rad
atio
n (
at T
= 6
0 m
in)
Concentration of catalyst (gL-1)
Rh-B + Anatase
Figure 5.01. Effects of the concentration of
anatase on the photodegradation process of
RhB.
Another relevant test was carried out to determine the relevance of the catalyst
and the hydrogen peroxide in the degradation process, because it was necessary to
know if the degradation process can proceed without the presence of catalyst or the
hydrogen peroxide. The Figure 5.02 shows the results of this test; both reagents
(catalyst and hydrogen peroxide) were necessary for the process. Previous studies
corroborated these results (Huang et al. 2010a). In the absence of the catalyst, no
degradation process (photocatalysis, sonocatalysis and sonophotocatalysis) was
observed (Minero et al. 2005; Vinu and Madras 2009). In the Fenton reactions,
Massomboon et al. (2009) demonstrated that if an excess of the iron catalyst is added
93
to the reaction mixture, a decrease in the degradation process was observed because
the iron can react with the hydroxyl radicals formed during the process. A synergistic
effect was also observed between the photocatalysis and sonocatalysis increasing the
degradation effect because the sonocatalysis avoids any possible aggregation of the
catalyst, increasing the surface area and the efficiency of the irradiation on the sample
degradation (Vinu and Madras 2009). Su et al. (2010) studied the degradation of CV
using Mn2O3 as catalyst. The authors demonstrated the importance of the hydrogen
peroxide in the degradation; a specific concentration is required for the reaction and
higher concentrations do not seem to increase the dye degradation. The hydrogen
peroxide is responsible for the generation of hydroxyl radicals in presence of the
catalyst, being these radicals the species that initiate the degradation process
(Masomboon et al. 2009).
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
Without Catalyst
Figure 5.02. Effects of the catalyst and
hydrogen peroxide on the
photodegradation process of RhB.
An optimum concentration of the dye is also necessary for an effective process
because this parameter can be related with the dispersion of the catalyst particles
(Wang et al. 2010) (Figure 5.02). A small decrease in the concentration of the dye was
94
also observed when the reaction is carried out without the catalyst in presence of light
(Asiri et al. 2011).
5.1.2. Effects of the pH
The study of the effects of the pH of the solution on the photochemical
degradation process was also analyzed. The pH of the solution was changed from acid
to basic without changing the concentration of the catalyst (anatase) and the dye (RhB,
10-5 M). The Figure 5.03 shows the effects of the pH on the degradation process. The
optimal pH ranged from 7 – 8, obtaining approximately the 100% of degradation of the
dye. At acid and basic pH ranges, the reaction is clearly less efficient, decreasing the
percent of photodegradation. Some investigators (Devipriya and Yesodharan 2010),
suggest that in acidic solutions the low reactivity observed in specific catalysts (i.e.
ZnO) should be due to photocorrosion of the catalyst induced by the pH.
4 5 6 7 8 9 10
60
80
100
% P
ho
to-d
eg
rad
atio
n (
at T
= 6
0 m
in)
pH
Rh-B + Anatase
Figure 5.03. The effects of the pH of the
reaction mixture on the photodegradation
process of RhB.
The pH significantly affect the reaction because the concentration of the·OH
groups changes (Lodha et al. 2008) the activity of the catalyst (Huang et al. 2010).
According to Hong et al. (2009) the photodegradation process follows a kinetic of first
95
order. The optimal pH is pH=7.0 and the photodegradation is favored at temperatures
higher than room temperature, but if the temperature increases above 40-45 °C the
degradation is partially stopped. Hong et al. (2009) observed that the concentration of
the catalyst has a maximum value to be efficient during the degradation process. The
optimal reaction conditions require a concentration of MO dye of 20ppm, a reaction time
of 20 hours, 1.5g L-1 of catalyst, a reaction mixture at pH=7.0 and a temperature of 30
°C. Hong et al. (2009) studied the photodegradation process of MO using ZnO
nanoparticles and polystyrene-capped ZnO nanoparticles. The authors (Hong et al.
2009) concluded that the ZnO was more efficient than the capped catalyst because
their hydrophilic behavior permits the adsorption of more MO molecules from the
solution and these molecules can easily be in contact with the air close to the surface of
the catalyst and the flow of electron-holes from the catalyst to the surface.
In the case of the Fenton reactions, the pH is also important for the degradation
reaction rate. At lower pH the possible formation of (Fe(II)(H2O))2+ species and the low
production of OH·are responsible for the decrease of the efficiency of this reaction
(Massomboon et al. 2009).
5.1.3. Effects of Temperature
Effect of the temperature of the solution on the photochemical degradation was
also analyzed. Concentrations of the catalyst and the RhB dye were previously
determined. Figure 5.04 shows the effects of the temperature on the degradation
process. Optimal degradation process was observed in a small range of temperatures
(25-30 °C).
96
5 10 15 20 25 30 35 40 45 50
40
60
80
100
% P
ho
to-d
eg
rad
atio
n (
at T
= 6
0 m
in)
Temperature (ºC)
Rh-B + Anatase
Figure 5.04. The effects of the temperature
of the solution on the photodegradation
process of RhB.
5.2. Photochemical degradation
Many substances commonly used are ecotoxic. The aromatic compounds
constitute an important source of environmental pollution reaching the atmosphere and
groundwaters because there are widely used as intermediates in the production of
pesticides, synthetic polymers, dyes, etc. (Huang et al. 2010a). These substances in
the environment are a concern because they possess carcinogenic, teratogenic and
toxic characteristics (specially the azo dyes), decrease the light penetration through the
water column, affect aesthetically and appreciably alter the gas solubility (Karadag et al.
2006; Vanhulle et al. 2008; Huang et al. 2010) damaging the environment
(Dafnopatidou et al. 2007).
In the last decades, new applications for the use of nanoparticles in
homogeneous and heterogeneous catalytic reactions were developed because these
materials show a high efficiency and a high surface-to-volume ratio along with high
surface energy (Pattapu et al. 2008) and will be part of the new green chemistry
technologies (Cao et al. 2010). Similarly to the biological process of photosynthesis in
which the chlorophyll (photosystem II) acts as a photoabsorbent substance, the
97
photocatalyst is responsible for the generation of electron-hole pairs when the light has
higher energy than the band gap of the photocatalyst, being a part of the chemical
reaction (Hong et al. 2009).
The photocatalyst (Hong et al. 2009) is one of the components of the
photodegradation process, and the different reactions involved using these components
are grouped in a variety of processes named Advanced Oxidation Processes or AOPs.
As mentioned previously, the AOPs use different chemical methods to generate
intermediate species, as the hydroxyl radicals for the oxidation of substances. The
most common method for the generation of the OH radicals includes the use of
hydrogen peroxide, ozone and UV irradiation (Hadj Salah et al. 2004).
The oxidation processes are non-selective. In the case of the photochemical
degradation, the energy source to drive the reaction is the UV or Visible light. During
the photodegradation processes, a catalyst should be used to absorb the photons of the
light. These catalysts are normally semiconductors, having a band gap lower or equal to
the energy of the photons used during the reaction. The photochemical process
generated by using these photocatalysts transforms the pollutants in CO2, H2O and
inorganic acids without generation of secondary compounds that could be toxic (Asiri et
al. 2011).
The interest in these processes is increasing, because different studies have
demonstrated that these processes are efficient in the degradation of organic
compounds and generate very low concentration of by-products during the degradation
reaction (Hernandez Enriquez et al. 2008). The heterogeneous photocatalysis is
described by Hernandez Enrique et al. (2008) as the degradation of a contaminant
using catalysts which normally are oxides of semiconductors, ultraviolet or solar
irradiation to generate radicals as O2·-, HO2· and OH· that finally are the responsible for
the oxidation of the pollutants. The possible functional groups on the surface of the
98
titanium oxide in aqueous solution may be TiOH2+, TiOH and TiO- (Devipriya and
Yesodharan 2010).
The band gap energy of a photocatalyst could be estimated by the following
equation:
0
gλ
hcE
Where Eg is the band gap energy, h is the Planck’s constant, c is the light velocity and
0λ is the absorption wavelength (Lo et al. 2004; Yu et al. 2009). Yu et al. (2009)
mentioned;
“Generally, the rate of the photocatalytic reaction is proportional
to n
αΦ)(I where αI is the photon number absorbed by the
photocatalyst per second and Φ is the efficiency of the band gap
transition.”
When the photocatalyst is exposed to low light intensity during the reaction, the
exponential value of n=1 and if the catalyst is exposed to high light intensity n=1/2 (Yu
et al. 2009). According with Ruan and Zhang (2009):
“the UV –driven photocatalytic activity of the sample is much
higher than the visible light –driven photocatalytic activity”
because the shorter wavelength produces a higher increase of the quantum yield.
In the photocatalytic process the generation of superoxide radicals and other
oxygen radical species is caused by the transfer of an electron to an oxygen molecule
when the dye is in the excited state (Yu et al. 2009). Other studies (Ma et al. 2007)
demonstrated that the degradation reaction is mediated by a radical mechanism
because during a comparative analysis between a control group and a radical
scavenger-containing group a difference with statistical significance was observed. An
99
example for the degradation of an organic compound is the photodegradation of 2-
Mercaptobenzothiazole (Li et al. 2006).
Another technique used for the degradation of organic pollutants is the
photoelectrocatalytic process (Xu et al. 2009) in which capped electrodes are
necessary to avoid the reduction of the cathode by the hydrogen peroxide formed
during the reaction.
O2 + 2H+ + 2e- → H2O2
The biological processes have some disadvantages. Biological decolorization process
by K rosea is effective only under anaerobic conditions because the oxygen competes
with the dye during the reaction and inhibits the process (Parshetti et al. 2006).
According to Liu et al. (2008) the surface area is not the only factor that controls
the process; the crystal structure is relevant for the catalytic process. Hadj Salah
(2004) determined that the structure, diameter of the particle, size of the crystallite and
the electronic properties are relevant to determine the catalytic activity. Another author
(Liu et al. 2008) mentioned as important the size of the particle and the capability to
remove the catalyst after the catalytic degradation process.
As mentioned previously the relationship between the dye and the catalyst is
relevant. Taking into account the adsorption equilibrium between the dye and the
catalyst, the equilibrium is given by (Karadag et al. 2006; Mahanta et al. 2008):
W
)VC(Ceq e0
Where qe is the amount of dye adsorbed at the equilibrium; C0 and Ce are the initial
concentration and concentration at equilibrium, respectively; V is the volume of the
solution and W is the mass of the catalyst used during the reaction (Mahanta et al.
2008).
100
Another important issue is the characteristic of the catalyst. According to Ma et
al. (2007) the microstructure and morphology has a great influence in the selectivity of
the catalyst to degrade a dye. Also, no synergistic or inhibited effect is observed when
a mixture of TiO2 and ZnO is used for photodegradation of phenols (Devipriya and
Yesodharan 2010).
5.2.1. Description of the Photocatalytic System
The experimental setup used for the photocatalytic reaction during this
investigation was adapted from a similar method described by Hernandez Enriquez et
al. (2008). A cylindrical reactor (semi-batch type) with continuous stirring was located in
the center of two double tubular lamps, which were the irradiation source. The
experimental setup (Figure 5.05) was composed by two annular white bulb lights with a
total irradiation power of 60 watts. A vessel of 1 L was used during the irradiation of the
sample. The sample was mechanically stirred with a paddler to maintain a
homogeneous mixture during the irradiation of the sample. Before the irradiation, the
catalyst was suspended in the solution and kept in dark with stirring for at less 30 min
(Hong et al. 2009) to reach the adsorption-desorption equilibrium (Zhou et al. 2010).
All the system was covered to avoid any other irradiation on the sample; only
the light of the bulbs could reach the sample. Every 10 minutes a sample of 10 mL was
taken to obtain the UV and fluorescence spectra and to determine the TOC
concentration. The concentration of the dye and the catalyst were 10-5 M and 0.6 gL-1
respectively (Velegraki and Mantvinos 2008; Asiri et al. 2011).
101
Figure 5.05. Experimental setup used during
this research, without irradiation (a) and
during the irradiation (b)
Different organic pollutants (dyes and organic compounds) with different
structures were used during the investigation. The organic pollutants used were
Methylene Blue (MB), Rhodamine B (RhB), Methyl Orange (MO), Crystal Violet (CV),
Methyl Violet (MV) and p-aminobenzoic acid (pABA) (Figure 5.06). Some basic
information is available in Table 5.1.
Figure 5.06. Dye solutions used during the investigation.
From left to right; Methylene Blue, Methyl Orange,
Crystal Violet, Rhodamine B and Methyl Violet.
102
The sample solutions with the dyes and the organic compound (pABA) had a
concentration of 10-5 M (Velegraki and Mantvinos 2008; Asiri et al. 2011). The
concentration of the catalysts was 0.6 gL-1 in 300 mL of the solution. At the beginning,
the spectrum of the organic contaminants were obtained. An example is shown in
Figure 5.07, corresponding to MB. After the filtration of the catalyst, it was necessary to
determine the maximum wavelength (λmax) of the contaminant.
500 600 700
Ab
sorb
an
ce
Wavelenght (nm)
Figure 5.07. Methylene blue Visible
absorption spectrum.
Fluorescence, UV-visible absorption and TOC were determined for each
sample. A decrease in the intensity of the absorption and fluorescence spectra was
observed for all compounds along the degradation process. Figure 5.08 shows the
fluorescence and the absorption spectra of MB in presence of rutile at different reaction
times, showing the degradation process. Figure 5.08c and Figure 5.08d clearly show
how the area of the curves decrease during the reaction time. Additionally, a smooth
displacement of the maximum absorption peak could be observed.
103
Table 5.1. Basic information of the studied organic compounds (adapted from Ma et al.
2007).
Dye
Chemical Structure
Molecular Weight
(g mol-1)
Amax (nm)
(Observed)
Methylene
Blue
S+
N
NCH3
CH3
NCH3
CH3Cl-
373.88 g mole-1
658
Rhodamine
B
O N+
CH3
CH3
N
CH3
CH3
COOH
479.02 g mole-1 553
Methyl
Orange
N N NCH3
CH3
SONa3
327.34 g mole-1 465 Ma et
al. (2007)
Crystal Violet N+ CH3CH3
CH3
CH3CH3
CH3
408.00 g mole-1 583
Methyl Violet N
+
NHN CH3CH3
CH3
CH3
CH3Cl-
393.96 g mole-1 580
p-ABA O OH
NH2
137.14 g mole-1 280 nm
(Schmidt
et al. 1997
104
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Ab
sorb
an
ce
Time (min)
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
a) b)
700
0
50
100
150
200
250
300
350
400
450
500
Inte
nsity (
a.u
.)
Wavelenght (nm)
Fluorescence
1
2
3
45
6
1: t=0
2: t=10m
3: t=20m
4: t=30m
5: t=45m
6: t=60m
c) d)
500 600 700
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1: t=0
2: t=10m
3: t=20m
4: t=30m
5: t=45m
6: t=60m
Ab
sorb
an
ce
Wavelenght (nm)
Absorbance
1
2
3
4
5
6
Figure 5.08. Visible absorbance (a) and fluorescence (b) spectra
of MB in presence of rutile, irradiated with white light (60W) at
different reaction times and the corresponding representation of the
areas (c and d). The inset of c corresponds to the original (left) and
degraded (right) solutions.
These behaviors could be observed due the formation of intermediates during
the degradation process (Sun et al. 2009). The possible intermediates have absorption
peaks at different wavelength than the original organic compounds; for this reason
different absorption peaks were observed during the degradation process. Some
possible intermediates were detected by Sun et al. (2009) during the photodegradation
process of RhB with the CaSb2O5(OH)2 catalyst (Figure 5.09).
105
O N+ CH3
CH3
NCH3
CH3
COOH
O N+ CH3
CH3
NCH3
H
COOH
O N+ CH3
CH3
N
CH3
HOOC
O N+
COOH
N
HOOC
COOH
H H
O N+
CH3
N
HOOC
H
H
.
O N+
COOH
NHOOC
COOH
H H
.OH
CarboxylationDeethylation
Carboxylation
DeethylationCarboxylation
Deethylation
Hydroxylation
CO2, H2O, Low Molecular Weight Byproducts
.OH
Figure 5.09. Possible degradation intermediates of RhB during the photocatalytic
processs (Adapted from Sun et al. 2009).
106
To determine the photocatalytic degradation percent, the following equation was
used (Parshetti et al. 2006; Dafnopatidou et al. 2007; Ma et al. 2007; Shimizu et al.
2007; Mahanta et al. 2008; Hong et al. 2009):
100%A
AAPDP%
0
0
Where A0 is the absorbance at t=0 min and A is the absorbance at t=60 min. Table 5.2
shows the percent of degradation obtained after the photocatalytic reaction between
each model organic compound with the different catalysts used in this research.
According with the data presented in Table 5.2 the titanium oxide nanowires has the
highest degradation rate, reaching values between 93.13% and 98.51%. Wang et al.
(2010) observed that pure TiO2NWs reflect near the 95% of the visible light irradiated to
the catalyst; most of the light absorbed is UV-light (Wang et al. 2010). Using the
nanowires to degrade the pABA compound, the 90.20% of degradation was reached.
For the degradation of pABA the most efficient catalyst was the rutile catalyst (94.40%
of degradation).
The low efficiency of the ZnO catalyst could be due to the possible
photodecomposition of the catalyst in the solution during the photoreaction. The
photocatalytic activity has an inverse correlation between the photolysis of the catalyst
and the photodegradation of the dye (Kislov et al. 2009). The lowest degradation rate
was obtained using the TiO2@MWNT (from 72.88% to 84.87%) (Figure 5.10). The
degradation of aromatic pollutants by ·OH species is accomplished by an electrophilic
mechanism (Huang et al. 2010).
107
Table 5.2. Degradation percent of dye solutions during the Photocatalytic Process.
Organic
Contaminant
Catalyst
Anatase Rutile TiO2@MWNT TiO2NWs ZnO
MB 90.24% 88.17%
72.88% 93.13% 79.49%
RhB 92.72% 94.37% 74.54% 96.44% 84.45%
MO 93.55% 89.83% 74.12% 93.55% 88.59%
CV 88.17% 92.72% 84.45% 96.85% 79.49%
MV 91.07% 94.37% 84.87% 98.51% 90.24%
p-ABA 94.00% 94.40% 77.40% 90.20% 82.40%
MB RhB MO CV MV p-ABA70
75
80
85
90
95
100
De
gra
da
tio
n (
%)
Pollutant
Anatase
Rutile
TiO2MWCNTs
TiO2NWs
ZnO
Figure 5.10. Graphic of the percent of degradation
of the different organic compounds by the
photocatalytic process.
108
The synthesis of different reaction intermediates during the degradation process
occurs. It is possible to think that many degradation reactions occur simultaneously in
the same reaction mixture, and for this reason to define a reaction rate for all the
different processes is extremely difficult. Therefore, the degradation process is defined
as a pseudo-kinetic reaction (Pey 2008). For the photocatalytic process carried out
during this research, the best type of kinetic reaction adapted is the pseudo-first order
reaction (Figure 5.11). The equation used to determine the reaction rate is based on
the definition of the model. The first kinetic model is defined as (Wang et al. 2006a;
Asiri et al. 2011):
ktC)Cln( 0
where C0 and C are the initial concentration and the concentration at any time,
respectively. The semilogarithmic plots of the concentrations vs time give straight lines
in which the slope represent the value of k (rate reaction) (Figure 5.11).
0 10 20 30 40 50 60
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0365x
R² = 0.997
Ln
(C
/C0)
Time (min)
MB/Rutile/Photocatalysis
Figure 5.11. Regression curve of the
Methylene Blue (MB) with rutile under
photochemical process.
109
The Table 5.3 shows the data of the kinetic reaction rate for the model organic
compounds and the catalyst used during the degradation processes. The mean
velocity for the reaction is approximately 10-2 min. The values of R2 were between 0.99
and 0.71. The difference between these values can be justified as due to the
adsorption-desorption process of the dye by the catalyst during the degradation
process.
Table 5.3. Kinetic reaction rates and R2 values for the degradation reaction of the
organic compounds during the photocatalytic process.
Organic
Contaminant
Catalyst
Anatase Rutile TiO2@MWNT TiO2NWs ZnO
MB
4.24 x 10-2
R2= 0.9724
3.65 x 10-2
R2=0.9970
2.75 x 10-2
R2= 0.8004
4.95 x 10-2
R2= 0.9625
3.19 x 10-2
R2= 0.8872
RhB 4.88 x 10-2
R2= 0.9589
5.47 x 10-2
R2= 0.9429
2.76 x 10-2
R2= 0.7102
5.78 x 10-2
R2= 0.9939
3.33 x 10-2
R2= 0.9633
MO 4.53 x 10-2
R2= 0.9984
3.87 x 10-2
R2= 0.9981
2.75 x 10-2
R2= 0.8472
5.23 x 10-2
R2= 0.9446
3.45 x 10-2
R2= 0.9825
CV 3.55 x 10-2
R2= 0.9926
4.52 x 10-2
R2= 0.9797
3.95 x 10-2
R2= 0.8313
6.19 x 10-2
R2= 0.9824
3.19 x 10-2
R2= 0.8728
MV 4.70 x 10-2
R2= 0.9246
5.16 x 10-2
R2= 0.9806
3.53 x 10-2
R2= 0.9362
7.31 x 10-2
R2= 0.9807
4.17 x 10-2
R2= 0.9674
p-ABA 4.26 x 10-2
R2= 0.9725
4.52 x 10-2
R2= 0.9842
2.90 x 10-2
R2= 0.8802
4.37 x 10-2
R2= 0.9424
2.95 x 10-2
R2= 0.9812
110
Liu et al. (2008) suggest that the degradation rate of the titanium oxide is related
to the band gap energy: “at higher band gap energy, the higher ultraviolet energy that
can be absorbed to active the photocatalyst” enhancing the oxidation process. The
difference in reaction time between the commercial and the synthesized material could
be explained by the difference in absorption capacity, wavelength and the energy of the
prohibited bands determined by both materials (Hernandez Enriquez et al. 2008).
The ZnO has a lower degradation rate when this catalyst is compared with the
TiO2 catalysts (rutile, anatase and nanowires). Common semiconductors for
degradation of contaminants are TiO2, ZnO, CdS, etc. (Lo et al. 2004), but some of
them (as ZnO and CdS) has poor stability (Hernandez-Alonso et al. 2009).
The titanium oxide has an amphoteric property, and positive or negative charges
can be generated on the surface (Velegraki and Mantzavinos 2008). Changes in the
pH during the degradation process could be observed and this phenomenon could be
caused by a change in the charge on the surface of the catalyst. The charge on the
TiO2 surface is positive when the pH is 1 and the charge is negative at pH>9 (Asiri et al.
2011). Also it is important to know that some by-products formed during the reaction
have an acid pH that can alter the surface charge (Velegraki and Mantzavinos 2008).
The specific surface area affects the reaction activity (Lo et al. 2004). Velegraki
and Mantzavinos (2008) suggest that the reduction in the reaction rates could be due to
the decrease of the active sites on the surface of the catalyst (titanium oxide) and the
possible development of multilayers formed by the organic compound on the surface of
the catalyst, avoiding the direct contact between the molecules of the compound and
the catalyst.
On the surface of the catalyst the semiconductor is excited by a photon of light
and an electron-hole pair is generated.
111
VBCB22 heTiOhνTiO
The valence band hole has a high oxidative potential producing the oxidation of
the dye and hydroxyl radical from the water molecule. Consecutive reactions allow the
oxidation of the dye and the complete photodegradation.
dyedyehVB Oxidation of the dye
OHHOHh 2VB
OHOHh .VB
dyeOH photodegradation of the dye
The conduction band electron liberated from the surface produces radicals of the
oxygen molecule in the solution 22CB OOe . The oxygen radicals react with the
hydrogen peroxide producing hydroxyl radical and ions. At the same time regenerate
the O2 to continue with the reaction 2222 OOHOHOHO (Velegraki and
Mantzavinos 2008; Asiri et al. 2011). Other authors mention the presence of four
processes during the heterogeneous photocatalysis using TiO2 (Figure 5.12) (Wang et
al. 2006a).
According to Asiri et al. (2011), the presence of “anchor” groups on the surface
of the catalyst facilitates the anchorage of groups available in the dye, increasing the
degradation processes. In a typical heterogeneous catalytic reaction, the decay
observed in the RhB dye concentration was part of the adsorption-desorption process
prior to reach the equilibrium (Figure 5.13) (Yu et al. 2009).
112
CBVB ehhvTiO2
))(()( OHVITiOHVITihVB
))(())( OHIIITiOHVITieCB
)()( IIITiVITieCB
heateh CBVB
OHVITiOHVITieCB )())((
OHVITiOHIIITihVB )())((
)(Re)(Re))(( dOHVITidOHVITi
)()())(( OxOHVITiOxOHIIITi
Charge-carrier generation
Charge-carrier traping
Charge-carrier recombination
Interfacial charge transfer
Figure 5.12. Possible processes involved in the degradation reaction
using TiO2 as catalyst.
113
0 10 20 30 40 50 60
0.3
0.4
0.5
0.6
0.7
Ab
sorb
an
ce
Wavelength (nm)
Figure 5.13. Spectrum corresponding to
the degradation of Rhodamine B by
TiO2@MWCNTs under photochemical
proces demonstrating the adsorption-
desorption equilibrium.
According to Wang et al. (2010a) the initial high concentration of the MB dye is
caused by the adsorption of the dye by the nanowires. In the Pt@TiO2NWs a decrease
in the adsorption is observed when it is compared with the pure TiO2NWs and the
authors suggest that the Pt particles occupy the adsorption sites of the MB dye on the
surface of the catalyst (Wang et al. 2010a).
During the photocatalytic degradation (under visible light) of these types of
compounds, two photooxidation mechanisms are common: the N-deethylation and the
cleavage of the chromophore structure. The cleavage of the chromophore
predominates over the other mechanisms (Yu et al. 2009). According to Yu et al.
(2009), the active species or the photogenerated hole attack the central carbon to
decolorize the dye. After that, the degradation continues with any N-deethylation
intermediates and other smaller molecules until the mineralization process is finished
114
with the formation of CO2 and H2O. Yu et al. (2009) determined that 97% of an RhB
solution was completely bleached in three hours using NaBiO3 as catalyst.
According to Vinu and Madras (2009), N-demethylation and N-dealkylation are
the mechanisms involved in the synthesis of intermediates during the degradation of the
triphenyl methane dyes (i.e. RhB). For RhB, the characteristic absorption peak at 554
nm decreases during the photocatalytic degradation and a concomitant hypsochromic
peak appears at 534 nm. These shifts are part of the formation and transformation of
the N-deethylated intermediates and imply that the chromophores of the RhB molecules
are cleavaged (Yu et al. 2009). Yu et al. (2009) identify four different N-deethylated
intermediates; N,N-diethyl-N’-ethylrhodamine (DER), N,N-diethylrhodamine (DR), N-
ethylrhodamine (ER), rhodamine (R) and other small molecular intermediates (18
compounds) as ethane-1,2-diol, benzoic acid, glutaric acid and dibutyl phthalate.
During the degradation process, a competition between the DR and EER (two peaks at
m/z=387 appear) occurs, but the DR domain over EER (Yu et al. 2009). The change of
550 nm to 508 nm was correlated with the hypsochromic shift; the intermediates of
degradation of the N-ethyl occurred at shorter wavelength due to their auxochromic
properties (Yu et al. 2009).
An oxidative cleavage in the carbons near the azo bond forms the primary
products of degradation of a dye, which has an azo bond (Vinus and Madras 2009) as
in MO. The four principal by-products are depicted in Figure 5.14. Four possible by-
products could be principally generated during the photodegradation process, along
with other low molecular weight compounds (He et al. 2009; Hong et al. 2009).
During the degradation of the MO using CaSb2O5(OH)2 as photocatalyst, Sun et
al. (2009) determined other possible intermediates (Figure 5.15). Possibilities of
different intermediates can occur due to the influence of the catalyst, specially the
active sites of the catalyst, used during the reaction.
115
Wang et al. (2010) observed a shift from 655nm to 613nm (to the blue region of
the spectrum) during the degradation process, suggesting the N-demethylation of the
MB dye. According to the authors (Wang et al. 2010) the methyl groups of the dyes are
removed one by one of the chromophore, modifying gradually the wavelength of the
peak. The complete mineralization of the MB is described by the following reaction
(Panizza et al. 2006):
HCl3HNOSOHO6H16COSClNHC 3422231816
OH51
But when an electrochemical process for the degradation of the MB dye is used the
chlorine atom mediates the oxidation reaction (Panizza et al. 2006).
Figure 5.14. Four principal by-products of the MO degradation process.
116
CO2, H2O, Low Molecular Weight Byproducts
.OH
N N N
CH3
CH3
O3
-S
N N N
CH3
O3
-S
H
N N N
CH3
O3
-S
H
OH
O-OC N N N
CH3
CH3
N
CH3
H
(C2H5)5O-OC
Demethylation Demethylation
Hydroxylation
Opening-Ring
Hydroxylation
Carboxylation
Openning-Ring
Figure 5.15. Possible intermediates of degradation of MO during the
photocatalytic degradation (Adapted from Sun et al. 2009).
117
5.3. Sono-Fenton Process
5.3.1. Description of the Sono-Fenton System
A similar method described by Hernández Enriquez et al. (2008) was used
during this research. A reactor (semi-batch type) was incorporated in the center of an
ultrasound bath. Similarly to the photochemical process, the homogeneous sample
(catalyst and dye solution) was kept in the dark under stirring for at least 30 min (Hong
et al. 2009) to reach the adsorption-desorption equilibrium (Zhou et al. 2010).
All the system was covered to avoid any other irradiation source on the sample;
only the energy of the sound waves could reach the sample. Every 10 minutes an
aliquot sample of 10 mL was taken to determine the UV and fluorescence spectrum and
to measure the TOC concentration. The concentration of the dye solutions was 10-5 M
and the concentration of the catalyst was 0.6 gL-1 (Velegraki and Mantvinos 2008; Asiri
et al. 2011). Different organic pollutants (dyes and organic compounds) with different
structures were used during the investigation. The organic pollutants used were
Methylene Blue (MB), Rhodamine B (RhB), Methyl Orange (MO), Crystal Violet (CV),
Methyl Violet (MV) and p-aminobenzoic acid (pABA).
The sonochemical process is similar to the photochemical process because
different radicals are produced and, after that, the radicals react in a cascade of
reactions to degrade the organic compounds. Vinu and Madras (2009) observed an
order in the degradation processes with a synergistic effect as follows: UV +US > UV
only > US only. According to Seymour and Gupta (1997) the process occurs when:
“the heat from cavity implosion decompose water into extremely reactive
hydrogen atoms (H·) and hydroxyl radicals (OH·). During the quick
cooling phase, hydrogen atoms and hydroxyl radicals recombine to form
hydrogen peroxide (H2O2) and molecular hydrogen (H2)…”.
118
The process is summarized in the following diagram (Figure 5.16). That reaction
encourages the decomposition of the organic pollutants and the reduction or oxidation
of the inorganic pollutants. Development of supercritical areas is relevant for the
reaction rate. Fluorescence, absorption and TOC were determined for each sample. A
decrease in the intensity of the absorption and fluorescence was observed for all the
analyzed compounds along the reaction time. Figure 5.17 shows the fluorescence and
absorption spectra. The absorbance and fluorescence curves clearly show the
degradation process observed when RhB is treated in a sono-Fenton degradation
process (Figure 5.17a and Figure 5.17b). Figure 5.17c and Figure 5.17d clearly show
how the area of the curve decreases along the reaction time.
Figure 5.16. Schematic diagram of the sonochemical
generation of the degradation radicals (Adapted from
Minero et al. 2005; Dafnopatidou et al. 2007).
119
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.2
0.3
0.4
0.5
0.6
0.7
Ab
so
rba
nce
Time (min)0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
0
Time (min)
a) b)
c) d)
Figure 5.17. Degradation curves of RhB; UV-vis absorbance (a), TOC
(b), fluorescence (c) and dye solutions before (left) and after (right) the
sono-Fenton degradation process (d).
The Table 5.4 shows the percent of degradation (based on the decrease in TOC
concentration). The determination of the degradation percent was similar to the
process used during the photocatalytic process.
According with the data presented in Table 5.4, the FeCl2 has the highest
degradation rate, reaching values between 70.82% to 96.85%. For the degradation of
p-ABA, the most efficient catalyst was the FeCl2 catalyst (95.20% of degradation). The
high efficiency of the FeCl2 as catalyst could be due to the high solubility of this catalyst
with respect to the other catalysts used in this study. The catalyst with the lowest
degradation rate was CuO, with a degradation percent ranging from 48.08% to 70.80%.
The order of efficiency was: FeCl2 > Fe2O3NWs > Fe3O4Comp > CuO (Figure 5.18).
120
Table 5.4. Degradation percent of dye solutions during the Sono-Fenton Process.
Model Organic
Contaminant
Catalyst (Sono-Fenton)
CuO Fe2O3NWs Fe3O4Mag FeCl2
MB
67.51%
84.87%
81.97%
94.37%
RhB 65.86% 79.49% 71.23% 90.24%
MO 65.03% 83.21% 73.71% 96.85%
CV 48.08% 64.20% 58.00% 70.82%
MV 65.44% 84.87% 74.12% 94.37%
p-ABA 70.80% 77.80% 68.70% 95.20%
MB RhB MO CV MV p-ABA45
50
55
60
65
70
75
80
85
90
95
100
Degra
da
tion (
%)
Pollutants
CuO
FeNWs
FeComp
FeCl2
Figure 5.18. Graphic of percent of degradation of
the organic compounds by the Sono-Fenton
process.
121
According to the authors (Vinus and Madras 2009) the model of
sonophotocatalytic degradation of a sulfonated azo dye is a pseudo-first order reaction.
This degradation is also considered as a Dual-Pathway Model in which the
sonocatalytic and photocatalytic processes are included in four different pathways as:
the absorption-desorption equilibrium, the generation of charge-carriers, generation of
electron-hole pairs and the radical formation (Vinu and Madras 2009). Equation used to
determine the reaction rate is based on the definition of the model. First kinetic model
is defined as (Wang et al. 2006; Asiri et al. 2011):
ktC)Cln( 0
where C0 and C are initial concentration and concentration at different times,
respectively. Semilogarithmic plots of the concentrations vs time gave straight lines in
which the slopes represent the value of k (reaction rate) (Figure 5.19).
0 10 20 30 40 50 60
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
y = -0.0293x
R² = 0.9812
Ln
(C
/C0)
Time (min)
MB/Fe3O4/Sono-Fenton
Figure 5.19. Regression curve of the Methylene
Blue (MB) with Fe3O4 under sono-Fenton
process.
122
The Table 5.5 shows the data corresponding to the kinetic reaction rates of the
model organic compounds and the different catalysts used during the degradation
processes. The mean velocity for the reaction is approximately 10-2 min. The values of
R2 range from 0.98 and 0.77. The difference between these values should be caused
by the adsorption-desorption process of the dye by the catalyst during the degradation
process.
Table 5.5 Kinetic reaction rates and R2 values for the degradation reaction of the
organic compounds during the sono-Fenton process.
Model
Organic
Contaminant
Catalyst (Sono-Fenton)
CuO Fe2O3NWs Fe3O4Mag FeCl2
MB
2.20 x 10-2
R2= 0.8621
3.35 x 10-2
R2=0.9650
2.93 x 10-2
R2= 0.9812
5.25 x 10-2
R2= 0.9455
RhB 2.05 x 10-2
R2= 0.8350
2.97 x 10-2
R2=0.9241
2.41 x 10-2
R2= 0.7979
4.48 x 10-2
R2= 0.9068
MO 2.09 x 10-2
R2= 0.8622
3.19 x 10-2
R2=0.9510
2.45 x 10-2
R2= 0.9214
5.32 x 10-2
R2= 0.9784
CV 1.30 x 10-2
R2= 0.7797
2.03 x 10-2
R2=0.8348
1.71 x 10-2
R2= 0.8172
2.53 x 10-2
R2= 0.8399
MV 1.89 x 10-2
R2= 0.8764
3.21 x 10-2
R2=0.9771
2.46 x 10-2
R2= 0.9445
5.05 x 10-2
R2= 0.9880
p-ABA 2.24 x 10-2
R2= 0.9757
2.81 x 10-2
R2=0.8745
2.12 x 10-2
R2= 0.9387
5.37 x 10-2
R2= 0.9794
123
According to Vinu and Madras (2009), the degradation reaction of a dye by a
hydroxyl radical generated by UV irradiation of ultrasonic is as follows:
TiO2(OH·)ads – Dads + TiO2 – Dads(orD) → intermediates (P) → CO2 + H2O
Dafnopatidou et al. (2007) describe the molecular environment during the ultrasound
degradation.
H2O + ultrasound → ·OH + ·H
2·OH → H2O2
Dyestuff + ·OH → products
According to Dafnopatidou et al. (2007), after the decolorization process by sonolysis, a
water effluent could be reused because it complies with the environmental regulations.
Authors (Wang et al. 2003) studied the exponential decrease of the methyl violet
with the sonication time, showing that the reaction process had a first order degradation
reaction with a reaction rate coefficient of 1.35 x 10-2 min-1 at 20 + 1 °C. Besides, they
showed that the degradation process decreased, when the temperature of the solution
increased to 80 °C because the cavitation bubbles decrease in the solution.
According to Wang et al. (2003), during the aqueous sonochemical process
three regions could be observed: the first one is the gas phase (formation of small
bubbles) in which high temperature and pressure are produced; the second one is an
interfacial zone between the cavitation bubble and the aqueous phase, in which the
temperature is lower than in the gas phase; and the third one is the bulk solution in
which the reaction takes place (Figure 5.20). The pH of the solution influences the
degradation of the dyes; for instance, at lower pH (pH 2 to 4) increases the degradation
rate (Wang et al. 2003).
124
Cavity
Interface
Bulk (Liquid Media)
Figure 5.20. Scheme of the different areas
of interest during the sonochemical
process (Adapted from Seymour and
Gupta 1997).
5.4. Photo-Fenton Process
5.4.1. Description of the Photo-Fenton System
A similar method described by Hernández Enríquez et al. (2008) was used
during the photo-Fenton process. The photo-Fenton process used during this research
is quite similar to the photochemical process; the difference between them is the use of
an iron catalyst (with the exception of the CuO). A cylindrical reactor (semi-batch type)
with continuous stirring was located in the center of two double tubular lamps which are
the irradiation source. The system (Figure 5.01) was composed by two annular white
bulb lights, with a total power of 60 watts. A vessel of 1 L was used during the
irradiation of the sample. The sample was mechanically stirred with a paddler to
maintain a homogeneous mixture during the irradiation of the sample. Before the
irradiation, the particles (catalyst and dye) were suspended in the solution and kept in
125
the dark under stirring for at least 30 min (Hong et al. 2009), to reach the adsorption-
desorption equilibrium (Zhou et al. 2010).
The experimental system was covered to avoid any other irradiation source in
the sample; only the light of the bulbs could reach the sample. Every 10 minutes an
aliquot sample of 10 mL was taken to determine the UV and fluorescence spectrum and
to measure the TOC concentration. As in the other catalytic reactions, the
concentration of the dye was 10-5 M and the concentration of the catalyst was 0.6 gL-1
(Velegraki and Mantvinos 2008; Asiri et al. 2011).
Different organic pollutants (dyes and organic compounds) with different
structures were used during the investigation. The organic pollutants used were
Methylene Blue (MB), Rhodamine B (RhB), Methyl Orange (MO), Crystal Violet (CV),
Methyl Violet (MV) and p-aminobenzoic acid (pABA)
According to Lodha et al. (2008), the photo-Fenton process is a new method for
the degradation of contaminants as dyes. This process is described as a classical
photochemical reaction, which involves the presence of the iron ion, hydrogen peroxide
and the visible or UV radiation.
One of the disadvantages of the Fenton process is the cease of the reaction
when the Fe2+ is consumed but if the process is carried out in the presence of light the
Fenton process is cyclic, and the reaction continues, because the Fe2+ is regenerated
from Fe3+ in the presence of light (Lodha et al. 2008). The Fe2+ reacts with the H2O2,
decomposing the peroxide in ·OH radical OH- and oxidize the iron ion forming Fe3+.
The ferric ion decomposes the water molecule, forming ·OH radical and the iron ion is
reduced to Fe2+ (Lodha et al. 2008). Some authors (Garrriga I Cabo 2007; Lodha et al.
2008) indicate that in the Fenton reactions some ferryl complex and hydrocomplexes of
iron could be involved resulting in the formation of Fe2+ and ·OH radicals.
126
Fluorescence, absorption and TOC were determined for each sample. A
decrease in the intensity of the absorption and fluorescence signals was observed for
all the systems along the reaction time. Figure 5.21 shows the fluorescence and UV-vis
absorption spectra of MO. Absorbance and fluorescence curves clearly show the
degradation process observed when MO is treated with FeCl2 (Figure 5.21a and Figure
5.21b). Figure 5.21c and Figure 5.21d show how the areas of the curves decrease
along the reaction time.
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Ab
so
rba
nce
Time (min)0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
0
Time (min)
a) b)
c) d)
Figure 5.21. Degradation curves of MO; UV-vis absorbance (a), TOC
(b), fluorescence (c) and dye solution before (left) and after (right) the
photo-Fenton process (d).
The Table 5.6 shows the percent of degradation (based on the decrease in TOC
concentration) of the organic pollutants. The determination of the degradation percent
was similar to the process used during the sonochemical process;
127
According with the results on the Table 5.6, the most efficient catalyst was the
FeCl2, which was a commercial material. The degradation percent using FeCl2 ranged
from 79.49% to 98.10%. The less efficient catalyst was the CuO with degradation
percents from 50.15 to 58.00 %. The order of efficiency was: FeCl2 > Fe2O3NWs >
Fe3O4Comp > CuO, similar to the sono-Fenton process (Figure 5.22).
Table 5.6. Degradation percent of dye solution during the Photo-Fenton Process
Model Organic
Contaminant
Catalyst (Photo-Fenton)
CuO Fe2O3NWs Fe3O4Mag FeCl2
MB
57.18%
86.11%
73.30%
92.31%
RhB 53.87% 79.49% 65.44% 86.93%
MO 57.59% 84.45% 65.44% 93.94%
CV 50.15% 58.00% 50.15% 79.49%
MV 55.55% 78.25% 65.03% 89.41%
p-ABA 58.00% 86.10% 69.20% 98.10%
Similarly to the photochemical and sono-Fenton process, the first kinetic model
was used to determine the reaction rate for the photo-Fenton process. The equation is
defined as (Wang et al. 2006; Asiri et al. 2011):
ktC)Cln( 0
The semilogarithmic plots of the concentrations vs time were used to determine the
reaction rate (Figure 5.23). The Table 5.7 shows the k values for the degradation
reaction of the dyes during the photo-Fenton process.
128
MB RhB MO CV MV p-ABA
50
55
60
65
70
75
80
85
90
95
100
De
gra
da
tion
(%
)
Pollutants
CuO
FeNWs
FeComp
FeCl2
Figure 5.22. Graphic of degradation percent of the
organic compounds by the Photo-Fenton process.
0 10 20 30 40 50 60
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0365x
R² = 0.9582
Ln
(C
/C0)
Time (min)
MB/Fe3O4/Photo-Fenton
Figure 5.23. Regression curve of the Methylene Blue
(MB) with Fe3O4 during the photo-Fenton degradation
process.
The Table 5.7 shows the data of the kinetic reaction rates for the model organic
compounds and the catalysts used during the degradation processes. The mean
velocity for the reaction is approximately 10-2 min. The values of R2 ranged from 0.99 to
129
0.51. The difference between these values could be due to the adsorption-desorption
processes of the dye by the catalyst during the degradation process and the
agglomeration of the catalyst during the reaction.
Table 5.7. Kinetic reaction rates and R2 values for the degradation reaction of the
organic compounds during the photo-Fenton process.
Model Organic
Contaminant
Catalyst (Photo-Fenton)
CuO Fe2O3NWs Fe3O4Mag FeCl2
MB
1.66 x 10-2
R2= 0.7264
3.65 x 10-2
R2=0.9582
2.37 x 10-2
R2= 0.9150
4.67 x 10-2
R2= 0.9241
RhB 1.52 x 10-2
R2= 0.5138
3.43 x 10-2
R2=0.7527
2.02 x 10-2
R2= 0.7936
4.17 x 10-2
R2= 0.6288
MO 1.53 x 10-2
R2= 0.8749
3.78 x 10-2
R2=0.8905
2.01 x 10-2
R2= 0.8983
5.28 x 10-2
R2= 0.9428
CV 1.16 x 10-2
R2= 0.9655
1.69 x 10-2
R2=0.7964
1.34 x 10-2
R2= 0.8548
3.09 x 10-2
R2= 0.8473
MV 1.46 x 10-2
R2= 0.9181
2.64 x 10-2
R2=0.9712
1.86 x 10-2
R2= 0.8993
3.96 x 10-2
R2= 0.9854
p-ABA 1.72 x 10-2
R2= 0.8045
3.45 x 10-2
R2=0.9784
2.09 x 10-2
R2= 0.9808
6.63 x 10-2
R2= 0.9941
5.5. Statistical analysis
A Multiple Factorial Design was used for the statistical analysis of the results of
the three degradation mechanisms: Photocatalysis, Sono-Fenton and Photo-Fenton
130
processes. The photochemical process was analyzed independently from the Sono-
Fenton and Photo-Fenton, because different catalysts were used during this process. A
complex matrix 2x4x6 was generated using the Minitab 14 program. The 48 responses
were analyzed. According with the results obtained, no significant differences were
observed between the sono-Fenton and photo-Fenton processes.
A comparison between the results of the degradation processes between the
photocatalytic and photo-Fenton was carried out. A few differences were observed
when both processes were compared (Figure 5.24). TiO2NWs was the most effective
catalyst for the photocatalytic process and the FeCl2 was the catalyst with higher
degradation activity for the sono and photo-Fenton processes.
MB RhB MO CV MV p-ABA
0
20
40
60
80
100
% D
eg
rad
atio
n
Dye
Anatase
Rutile
TiO2MWCNTs
TiO2NWs
ZnO
CuO
FeNWs
FeComp
FeCl2
Figure 5.24. Graphic of comparison between the
Photocatalytic process and the Photo-Fenton process.
Figure 5.25 represents the sono-Fenton and photocatalytic process for MB, RhB
and MO. A similar pattern between photocatalysis and sono-Fenton was observed.
The percentual difference between the three studied processes (photocatalysis, photo-
131
Fenton and Sono-Fenton) was minimal. In CV, some differences between the sono-
Fenton and photo-Fenton processes were observed.
MB RhB MO
0
20
40
60
80
100
De
gra
da
tio
n (
%)
Dyes
Anatase
Rutile
TiO2@MWCNTs
TiO2NWs
ZnO
CuO
Fe2O
3NWs
Fe3O
4Mag
FeCl2
Figure 5.25. Graphic of comparison between the
Photocatalytic process and the Sono-Fenton process for
MB, RhB and MO.
132
Chapter Six
Conclusion
After the analysis of the data obtained during this investigation we can conclude
that the goal of this investigation was achieved. During the present research, different
catalysts (TiO2 nanowires, TiO2@MWNTs, ZnO nanoparticles, Fe2O3 nanowires and
magnetite nanoparticles) were synthesized and fully characterized by different
techniques as FE-SEM, TGA, specific surface area (BET), XRD, Raman spectroscopy,
XPS and magnetic susceptibility. Commercial and synthesized catalysts were used in
different processes with the aim to reduce the amount of model compounds (organic
dyes) in water, by using different heterogeneous catalytic processes (photocatalysis,
sono-Fenton and photo-Fenton). As model pollutants, we selected different dyes or
organic compounds that are considered as hazardous contaminants, normally used by
the chemical industry (Methylene Blue, Rhodamine B, Methyl Orange, Gential Violet and
Methyl Violet and p-aminobenzoic acid).
In all cases, the catalysts used in the present research were able to degrade the
pollutants. For the photocatalytic process, the most effective catalyst was the TiO2NWs
(approximately 94.78% of degradation) and the less effective was the TiO2@MWCNTs
(with approximately 78.04% of degradation). During the photo-Fenton and sono-Fenton
processes the same catalysts were used, to demonstrate if any of the processes was
more effective than the other. However, no significant differences were observed
between photo-Fenton and sono-Fenton processes when the same catalysts were
studied and compared. A slightly decrease in the degradation percent was observed for
CV pollutant. For the sono-Fenton and photo-Fenton processes, the more efficient
catalyst was, in both cases, FeCl2 (with approximately 90.31% and 90.03% of
133
degradation, respectively) and the less effective was CuO (approx. 63.79% and 55.39%
of degradation, respectively).
Hence, it is deduced that the catalytic reactions studied in this research can be
efficiently used for the degradation and decolorization of organic pollutants. The catalytic
processes can be suitably and cost effectively employed for the removal of pollutants
from wastewaters in a short period of time. We can predict that, with high probability,
these catalytic processes can be implemented as appropriate chemical procedures for
pollutant removal from water or even from soil.
134
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Zhou W, Liu H, Wang J, Liu D, Du G, Cui J. 2010. Ag2O/TiO2 Nanobelts Heterostructure
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151
Appendix One
Dyes Solutions
Figure A1.01 shows the different dye solutions (10-5 M) before being exposed to
the photo-Fenton process using FeCl2 as Fenton catalyst and the same solution after the
photo-Fenton reaction.
Solutions of the dyes used during the investigation. From
left to right: methylene blue, methyl orange, crystal violet,
rhodamine B and methyl violet, before and after the
catalytic process, respectively.
152
Appendix Two
Photocatalytic Process
In the Appendix Two, the absorbance and fluorescence spectra, and graphics of the
TOC data obtained during the photocatalytic process are shown for each pair of organic
pollutant – photocatalyst.
500 600 700
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75 1: t=0
2: t=10m
3: t=20m
4: t=30m
5: t=45m
6: t=60m
Inte
nsity
(a.u
.)
Wavelenght (nm)
Absorption
1
2
3
4
5
6
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Abs
orba
nce
Time (min)
0 10 20 30 40 50 60
Flu
ores
cenc
e
Time (min)
a) b)
700
0
50
100
150
200
250
300
350
400
450
500
Inte
nsi
ty (
a.u
.)
Wavelenght (nm)
Fluorescence
1
2
3
45
6
1: t=0
2: t=10m
3: t=20m
4: t=30m
5: t=45m
6: t=60m
c) d)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without catalyst
0 10 20 30 40 50 60
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0365x
R² = 0.997
Ln
(C
/C0)
Time (min)
MB/Rutile/Photocatalysise) f)
Figure A2.01. UV-vis absorption (a and c), fluorescence (b and d), TOC (e) and
kinetic reaction rate (f) of the photocatalytic degradation process of Methylene Blue
with TiO2 (Rutile phase) as catalyst.
153
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without Catalyst
0 10 20 30 40 50 60
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0424x
R² = 0.9724Ln(C
/C0)
Time
MB\Anatase\Photocatalysis
a) b)
c) d)
Figure A2.02. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methylene Blue
with TiO2 (Anatase phase) as catalyst.
154
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Wavelength (nm)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
Ln
C/C
o
Time (min)
Without Catalyst
0 10 20 30 40 50 60
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0495x
R² = 0.9625
Ln
(C\C
0)
Time (min)
MB\TiO2NWs\Photocatalysis
d)
b)
c)
a)
Figure A2.03. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methylene Blue
with TiO2NWs as catalyst.
155
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without Catalyst
0 10 20 30 40 50 60
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0275x
R² = 0.8004Ln
(C/C
0)
Time (min)
MB\TiO2MWCNTs\Photocatalysis
a) b)
c) d)
Figure A2.04. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methylene Blue
with TiO2@MWCNTs as catalyst.
156
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
0.6
Ab
so
rba
nce
Wavelength (nm)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without Catalyst
0 10 20 30 40 50 60
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0319x
R² = 0.8872
Ln
(C/C
0)
Time (min)
MB\ZnO\Photocatalyst
a)b)
c) d)
Figure A2.05. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methylene
Blue with ZnO as catalyst.
157
Figure A2.06. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Rhodamine B
with TiO2 (Rutile phase) as catalyst.
158
Figure A2.07. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Rhodamine B
with TiO2 (Anatase phase) as catalyst.
159
Figure A2.08. UV-vis absorption (a), fluorescence (b), TOC (c) and
kinetic reaction rate (d) of the photocatalytic degradation process of
Rhodamine B with TiO2 NWs as catalyst.
160
Figure A2.09. UV-vis absorption (a), fluorescence (b), TOC (c) and
kinetic reaction rate (d) of the photocatalytic degradation process of
Rhodamine B with TiO2@MWCNTs as catalyst.
161
Figure A2.10. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Rhodamine B
with ZnO as catalyst.
162
Figure A2.11. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methyl Orange
with TiO2 (Rutile phase) as catalyst.
163
Figure A2.12. UV-vis absorption (a), fluorescence (b), TOC (c) and
kinetic reaction rate (d) of the photocatalytic degradation process of
Methyl Orange with TiO2 (Anatase phase) as catalyst.
164
Figure A2.13. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methyl Orange
with TiO2NWs as catalyst.
165
Figure A2.14. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methyl
Orange with TiO2MWCNTs as catalyst.
166
Figure A2.15. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Methyl Orange with ZnO as
catalyst.
167
Figure A2.16. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Crystal Violet with
TiO2 (Rutile phase) as catalyst.
168
0 10 20 30 40 50 60
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0355x
R² = 0.9926
Ln
(C/C
0)
Time (min)
CV\Anatase\Photocatalysis
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without Catalyst
a)
c) d)
b)
Figure A2.17. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Crystal Violet with TiO2 (Anatase
phase) as catalyst.
169
Figure A2.18. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Crystal Violet with TiO2 NWs as
catalyst.
170
Figure A2.19. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Crystal Violet with
TiO2@MWCNTs as catalyst.
171
Figure A2.20. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Crystal Violet with ZnO as
catalyst.
172
Figure A2.21. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methyl Violet with
TiO2 (Rutile phase) as catalyst.
173
Figure A2.22. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Methyl Violet with TiO2
(Anatase phase) as catalyst.
174
Figure A2.23. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the photocatalytic degradation process of Methyl Violet with
TiO2NWs as catalyst.
175
Figure A2.24. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Methyl Violet with
TiO2MWCNTs as catalyst.
176
Figure A2.25. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the photocatalytic degradation process of Methyl Violet with ZnO as
catalyst.
177
Figure A2.26. Curves of the TOC (a) and kinetic
reaction rate (b) of the photocatalytic degradation
process of the p-ABA using TiO2 (Rutile phase) as
catalyst.
178
Figure A2.27. Curves of the TOC (a) and kinetic
reaction rate (b) of the photocatalytic degradation
process of the p-ABA using TiO2 (Anatase phase) as
catalyst as catalyst.
179
Figure A2.28. Curves of the TOC (a) and kinetic
reaction rate (b) of the photocatalytic degradation
process of the p-ABA using TiO2NWs as catalyst.
180
Figure A2.29. Curves of the TOC (a) and kinetic
reaction rate (b) of the photocatalytic degradation
process of the p-ABA using TiO2@MWCNTs as
catalyst.
181
Figure A2.30. Curves of the TOC (a) and kinetic
reaction rate (b) of the photocatalytic degradation
process of the p-ABA using ZnO as catalyst.
182
Appendix Three
Sono-Fenton Process
In the Appendix Three, the absorbance and fluorescence spectra, and graphics of the
TOC data obtained during the sono-Fenton process are shown for each pair of organic
pollutant – photocatalyst.
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
sorb
an
ce
Time (min)
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without H2O
2
Without Catalyst
0 10 20 30 40 50 60
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.022x
R² = 0.8621
Ln
(C/C
0)
Time (min)
MB\CuO\Sono-Fenton
a)
c) d)
b)
Figure A3.01. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic rate
reaction (d) of the Sono-Fenton degradation process of Methylene blue with CuO
as catalyst.
183
0 10 20 30 40 50 60
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0335x
R² = 0.965
Ln
(C/C
0)
Time (min)
MB\Fe2O3NWs\Sono-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
sorb
an
ce
Wavelength (nm)
0 10 20 30 40 50 600.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
Without H2O
2
Without Catalyst
a) b)
c) d)
Figure A3.02. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Methylene blue with Fe2O3NWs
as catalyst.
184
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
0 10 20 30 40 50 60
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0293x
R² = 0.9812L
n(C
/C0)
Time (min)
MB\Fe3O
4Magnetite\Sono-Fenton
a)
c) d)
b)
Figure A3.03. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methylene blue with
Fe3O4 (Magnetite) as catalyst.
185
0 10 20 30 40 50 60
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0525x
R² = 0.9455L
n(C
/C0)
Time (min)
MB\FeCl2\Sono-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A3.04. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methylene blue with
FeCl2 as catalyst.
186
Figure A3.05. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Rhodamine B with
CuO as catalyst.
187
Figure A3.06. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Rhodamine B with
Fe2O3NWs as catalyst.
188
Figure A3.07. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Rhodamine B with
Fe3O4 (Magnetite) as catalyst.
189
Figure A3.08. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Rhodamine B with
FeCl2 as catalyst.
190
Figure A3.09. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methyl Orange
with CuO as catalyst.
191
Figure A3.10. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methyl Orange with
Fe2O3NWs as catalyst.
192
Figure A3.11. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Methyl Orange with Fe3O4
(Magnetite) as catalyst.
193
Figure A3.12. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methyl Orange
with FeCl2 as catalyst.
194
0 10 20 30 40 50 60
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
y = -0.013x
R² = 0.7797
Ln
(C/C
0)
Time (min)
CV\CuO\Sono-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
a)
c) d)
b)
Figure A3.13. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Crystal Violet with
CuO as catalyst.
195
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0203x
R² = 0.8348
Ln
(C/C
0)
Time (min)
CV\Fe2O
3NWs\Sono-Fenton
a)
c) d)
b)
Figure A3.14. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Crystal Violet with Fe2O3NWS
as catalyst.
196
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0171x
R² = 0.8172Ln
(C/C
0)
Time (min)
CV\Fe3O
4Magnetite\Sono-Fenton
a)
c) d)
b)
Figure A3.15. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Crystal Violet with
Fe3O4 (Magnetite) as catalyst.
197
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0253x
R² = 0.8399Ln
(C/C
0)
Time (min)
CV\FeCl2\Sono-Fenton
a)
c) d)
b)
Figure A3.16. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Crystal Violet with FeCl2 as
catalyst.
198
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without catalyst
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0189x
R² = 0.8764L
n(C
/C0)
Time (min)
MV\CuO\Sono-Fenton
a)
c) d)
b)
Figure A3.17. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Sono-Fenton degradation process of Methyl Violet with
CuO as catalyst.
199
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0321x
R² = 0.9771
Ln
(C/C
0)
Time (min)
MV\Fe2O
3NWs\Sono-Fentonc)
a)
d)
b)
Figure A3.18. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Methyl Violet with Fe2O3NWS
as catalyst.
200
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0246x
R² = 0.9445
Ln
(C/C
0)
Time (min)
MV\Fe3O
4Magnetite\Sono-Fenton
a)
c) d)
b)
Figure A3.19. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Methyl Violet with Fe3O4
(Magnetite) as catalyst.
201
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
sorb
an
ce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
Without H2O
2
C/C
o
Time (min)
TOC: C/Co
Without Catalyst
0 10 20 30 40 50 60
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0505x
R² = 0.988
Ln
(C/C
0)
Time (min)
MV\FeCl2\Sono-Fenton
a)
c) d)
b)
Figure A3.20. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Sono-Fenton degradation process of Methyl Violet with FeCl2 as
catalyst.
202
Figure A3.21. Curves of the TOC (a) and kinetic
reaction rate (b) of the Sono-Fenton degradation
process of the p-ABA with CuO as catalyst.
203
Figure A3.22. Curves of the TOC (a) and kinetic
reaction rate (b) of the Sono-Fenton degradation
process of the p-ABA with Fe2O3NWs as catalyst.
204
Figure A3.23. Curves of the TOC (a) and kinetic
reaction rate (b) of the Sono-Fenton degradation
process of the p-ABA with Fe3O4 (Magnetite) as
catalyst.
205
Figure A3.24. Curves of the TOC (a) and kinetic
reaction rate (b) of the Sono-Fenton degradation
process of the p-ABA with FeCl2 as catalyst.
206
Appendix Four
Photo-Fenton Process
In the Appendix Four, the absorbance and fluorescence spectra, and graphics of the
TOC data obtained during the photo-Fenton process are shown for each pair of organic
pollutant – photocatalyst.
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without H2O
2
Without Catalyst
0 10 20 30 40 50 60
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0166x
R² = 0.7264Ln
(C/C
0)
Time (min)
MB\CuO\Photo-Fenton
a)
c) d)
b)
Figure A4.01. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methylene Blue with
CuO as catalyst.
207
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Wavelength (nm)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co vs Irradiation time
Without H2O
2
Without Catalyst
0 10 20 30 40 50 60
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0365x
R² = 0.9582
Ln
(C/C
0)
Time (min)
MB\Fe2O
3NWs\Photo-Fenton
a)
d)c)
b)
Figure A4.02. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methylene Blue with
Fe2O3NWS as catalyst.
208
0 10 20 30 40 50 60
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0237x
R² = 0.915L
n(C
/C0)
Time (min)
MB\Fe3O
4Magnetite\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A4.03. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methylene Blue with
Fe3O4 (Magnetite) as catalyst.
209
0 10 20 30 40 50 60
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0467x
R² = 0.9241
Ln
(C/C
0)
Time (min)
MB\FeCl2\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A4.04. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methylene Blue with
FeCl2 as catalyst.
210
Figure A4.05. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Rhodamine B with
CuO as catalyst.
211
Figure A4.06. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Rhodamine B with
Fe2O3NWs as catalyst.
212
Figure A4.07. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Rhodamine B with
Fe3O4 (Magnetite) as catalyst.
213
Figure A4.08. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Rhodamine B with
FeCl2 as catalyst.
214
Figure A4.09. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Orange with
CuO as catalyst.
215
Figure A4.10. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Orange with
Fe2O3NWs as catalyst.
216
Figure A4.11. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Orange with
Fe3O4 (Magnetite) as catalyst.
217
Figure A4.12. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Orange with
FeCl2 as catalyst.
218
0 10 20 30 40 50 60
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
y = -0.0116x
R² = 0.9655
Ln
(C/C
0)
Time (min)
CV\CuO\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2 Without Catalyst
a)
c) d)
b)
Figure A4.13. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Photo-Fenton degradation process of Crystal Violet with CuO as
catalyst.
219
0 10 20 30 40 50 60
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0169x
R² = 0.7964L
n(C
/C0)
Time (min)
CV\Fe2O
3NWs\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A4.14. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Crystal Violet with
Fe2O3NWs as catalyst.
220
0 10 20 30 40 50 60
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
y = -0.0134x
R² = 0.8548Ln
(C/C
0)
Time (min)
CV\Fe3O
4Magnetite\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2Without Catalyst
a)
c) d)
b)
Figure A4.15. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Crystal Violet with
Fe3O4 (Magnetite) as catalyst.
221
0 10 20 30 40 50 60
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0309x
R² = 0.8473
Ln
(C/C
0)
Time (min)
CV\FeCl2\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c)
b)
d)
Figure A4.16. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Crystal Violet with
FeCl2 as catalyst.
222
0 10 20 30 40 50 60
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0146x
R² = 0.9181
Ln
(C/C
0)
Time (min)
MV\CuO\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co Without H2O
2 Without Catalyst
a)
c) d)
b)
Figure A4.17. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Photo-Fenton degradation process of Methyl Violet with CuO as
catalyst.
223
0 10 20 30 40 50 60
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
y = -0.0264x
R² = 0.9712
Ln
(C/C
0)
Time (min)
MV\Fe2O
3NWs\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A4.18. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Violet with
Fe2O3NWs as catalyst.
224
0 10 20 30 40 50 60
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
y = -0.0186x
R² = 0.8993
Ln
(C/C
0)
Time (min)
MV\Fe3O
4Magnetite\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c)
b)
d)
Figure A4.19. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic reaction
rate (d) of the Photo-Fenton degradation process of Methyl Violet with Fe3O4
(Magnetite) as catalyst.
225
0 10 20 30 40 50 60
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
y = -0.0396x
R² = 0.9854
Ln
(C/C
0)
Time (min)
MV\FeCl2\Photo-Fenton
0 10 20 30 40 50 60
Flu
ore
sce
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ab
so
rba
nce
Time (min)
0 10 20 30 40 50 60
0.0
0.2
0.4
0.6
0.8
1.0
C/C
o
Time (min)
TOC: C/Co
Without H2O
2
Without Catalyst
a)
c) d)
b)
Figure A4.20. UV-vis absorption (a), fluorescence (b), TOC (c) and kinetic
reaction rate (d) of the Photo-Fenton degradation process of Methyl Violet with
FeCl2 as catalyst.
226
Figure A4.21. Curves of the TOC (a) and kinetic
reaction rate (b) of the Photo-Fenton degradation
process of the p-ABA with CuO as catalyst.
227
Figure A4.22. Curves of the TOC (a) and kinetic
reaction rate (b) of the Photo-Fenton degradation
process of the p-ABA with Fe2O3NWs as catalyst.
228
Figure A4.23. Curves of the TOC (a) and kinetic
reaction rate (b) of the Photo-Fenton degradation
process of the p-ABA with Fe3O4 (Magnetite) as
catalyst.
229
Figure A4.24. Curves of the TOC (a) and kinetic
reaction rate (b) of the Photo-Fenton degradation
process of the p-ABA with FeCl2 as catalyst.
