Deciphering Structural Information from the Multiexcitonic Spectra of a Quantum Dot
Vladan Mlinar & Alex Zunger
National Renewable Energy Laboratory
Golden, Colorado USA
QDs: Structure - Spectra relationship
Methods for structural characterization
• TEM based methods
• X-ray diffraction
• X-STM
Single-dot spectroscopy
QDs: Structure - Spectra relationship
(M. Bozkurt, J. M. Ulloa, & P. M. Koenraad)
Methods for structural characterization
• TEM based methods
• X-ray diffraction
• X-STM
Single-dot spectroscopy
• No atomic resolution
• All of the methods require assumption
about composition profile and/or shape!
QDs: Structure - Spectra relationship
(M. Bozkurt, J. M. Ulloa, & P. M. Koenraad)
Methods for structural characterization
• TEM based methods
• X-ray diffraction
• X-STM
Single-dot spectroscopy
• No atomic resolution
• All of the methods require assumption
about composition profile and/or shape!
(M. Ediger &
R. J. Warburton)
QDs: Structure - Spectra relationship
(M. Bozkurt, J. M. Ulloa, & P. M. Koenraad)
Methods for structural characterization
• TEM based methods
• X-ray diffraction
• X-STM
Single-dot spectroscopy
• No atomic resolution
• All of the methods require assumption
about composition profile and/or shape!
• Controllable number of electrons and holes
• μeV resolution
(M. Ediger &
R. J. Warburton)
Typically, Structure is used to predict Spectra
• Since for quantum dots we do not know the structure:
Assume
or
measure
structure
Measured
emission
spectra
Calculate
resulting
spectra
Structure
Typically, Structure is used to predict Spectra
• Since for quantum dots we do not know the structure:
Is this possible?
Assume
or
measure
structure
Measured
emission
spectra
Calculate
resulting
spectra
Structure
Question: What is the structural information encoded in the multiexcitonic spectra of a QD?
?
Spectral Barcoding vs. DNA Barcoding:
Barc
oder
Barc
odin
g
Organism is identified as belonging to a particular species
Sci. Am. p. 82-88 (October 2008)
Spectral Barcoding vs. DNA Barcoding:
Barc
oder
Barc
odin
g
Organism is identified as belonging to a particular species
Sci. Am. p. 82-88 (October 2008)
Spectral Barcoding vs. DNA Barcoding:
Barc
oder
Barc
odin
g
Organism is identified as belonging to a particular species
QD is identified as belonging to a group of QDs with common structural motifs.
?
Vladan Mlinar and Alex Zunger, PRB 80, 035328 (2009).
How does the Spectral Barcoding work?
Spectral barode:
Vladan Mlinar and Alex Zunger, PRB 80, 035328 (2009).
How does the Spectral Barcoding work?
Artificial Intelligence QD library
Deterministic links between
structures and spectral marker(Distilling rules from library)
Spectral barode:
Spectral barcoding
procedure
Vladan Mlinar and Alex Zunger, PRB 80, 035328 (2009).
How does the Spectral Barcoding work?
Artificial Intelligence QD library
Deterministic links between
structures and spectral marker(Distilling rules from library)
Structure
Structural Motifs:
• h = 2 – 3nm
• Xav(In) = 75-80%
RESULT: a set
of QD structural
motifs!
Spectral barode:
Spectral barcoding
procedure
Vladan Mlinar and Alex Zunger, PRB 80, 035328 (2009).
Spectral Barcoding: Data-mining of the library
Structure
QD structure is discretized into a set of Ns=5 structural motifs, each taking up one of
Nv possible values:
Motifs: Shape b (nm) h (nm) XIn (%) profile
Trun.Cone 12 2.0 50 Homog.
Trun. Pyr. 18 3.0 60 Linear
Lens 20 3.5 70
Elong.
Lens [110]
23 4.0 80
Elong.
Lens [110]
25 5.0 90
Elong.
Lens [100]
30 6.0 100
Spectral Barcoding: Data-mining of the library
Structure
QD structure is discretized into a set of Ns=5 structural motifs, each taking up one of
Nv possible values:
Motifs: Shape b (nm) h (nm) XIn (%) profile
Trun.Cone 12 2.0 50 Homog.
Trun. Pyr. 18 3.0 60 Linear
Lens 20 3.5 70
Elong.
Lens [110]
23 4.0 80
Elong.
Lens [110]
25 5.0 90
Elong.
Lens [100]
30 6.0 100
Bayesian Data Reduction Algorithm:
• Training: Testing how each structural motif and its corresponding values influences the
barcode
• Result: Identifies the set of structural motifs that are responsible for a given spectral
barcode sequence.
Spectral Barcoding: Consistency test!
Vladan Mlinar and Alex Zunger,
PRB 80, 035328 (2009).
Spectral Barcoding: Consistency test!
Vladan Mlinar and Alex Zunger,
PRB 80, 035328 (2009).
Spectral Barcoding: Consistency test!
Vladan Mlinar and Alex Zunger,
PRB 80, 035328 (2009).
Spectral Barcoding: Consistency test!
Validation!
Vladan Mlinar and Alex Zunger,
PRB 80, 035328 (2009).
Question: How does the deduced structure relates to the “real structure”?
Spectral Barcoding: Why is it important?
Quantum Dot
growth
Structural Characterization by X-STM
Single-dot Spectroscopy
Antonio Badolato
(ETH Zurich, Switzerland)
Theory
Collaboration with
three experimental
groups!
Many body
pseudopotential
calculations
Calculated spectra
Spectral Barcoding: Why is it important?
Quantum Dot
growth
Structural Characterization by X-STM
Single-dot Spectroscopy
Antonio Badolato
(ETH Zurich, Switzerland)
M. Bozkurt, J. M. Ulloa, & P. M. Koenraad
(TU Eindhoven, The Netherlands)
Theory
Collaboration with
three experimental
groups!
Many body
pseudopotential
calculations
Calculated spectra
Spectral Barcoding: Why is it important?
Quantum Dot
growth
Structural Characterization by X-STM
Single-dot Spectroscopy
Antonio Badolato
(ETH Zurich, Switzerland)
M. Bozkurt, J. M. Ulloa, & P. M. Koenraad
(TU Eindhoven, The Netherlands)
Theory
M. Ediger & R. J. Warburton
(Heriot-Watt University, UK)
Collaboration with
three experimental
groups!
Many body
pseudopotential
calculations
Calculated spectra
Spectral Barcoding: Why is it important?
XS-2 < XT
-2 < X-1 < XX0 < X0 sequence
in measured spectra from each and
every QD studied in the ensemble is
kept.
Quantum Dot
growth
Structural Characterization by X-STM
Single-dot Spectroscopy
Antonio Badolato
(ETH Zurich, Switzerland)
M. Bozkurt, J. M. Ulloa, & P. M. Koenraad
(TU Eindhoven, The Netherlands)
Theory
M. Ediger & R. J. Warburton
(Heriot-Watt University, UK)
Collaboration with
three experimental
groups!
Many body
pseudopotential
calculations
Calculated spectra
Spectral Barcoding: Why is it important?
XS-2 < XT
-2 < X-1 < XX0 < X0 sequence
in measured spectra from each and
every QD studied in the ensemble is
kept.
Quantum Dot
growth
Structural Characterization by X-STM
Single-dot Spectroscopy
Antonio Badolato
(ETH Zurich, Switzerland)
M. Bozkurt, J. M. Ulloa, & P. M. Koenraad
(TU Eindhoven, The Netherlands)
Theory
M. Ediger & R. J. Warburton
(Heriot-Watt University, UK)
Collaboration with
three experimental
groups!
Many body
pseudopotential
calculations
Calculated spectra
• Exciton energies
• XS-2 < XT
-2 < X-1 < XX0 < X0
sequence
?V. Mlinar, G. Bester, &
A. Zunger (NREL)
Vladan Mlinar et al., PRB 80, 165425 (2009).
XSTM→Theory→Spectroscopy Fails to Close Loop!
Structure
• Exciton Energies:
Calculated: 1.05 -1.12 eV
Measured: 1.08-1.09 eV
Vladan Mlinar et al., PRB 80, 165425 (2009).
XSTM→Theory→Spectroscopy Fails to Close Loop!
Structure
• Spectral Hard Rules:
All five XSTM deduced Model QDs
violate Spectroscopic Hard rules!
EXP. XS-2 < XT
-2 < X-1 < XX0 < X0
Model 1 XS-2 < X0 < XX0 < X-1 < XT
-2
Model 2 XS-2 < X0 < XX0 < XT
-2 < X-1
Model 3 X0 < XX0 < XS-2 < X-1 < XT
-2
Model 4 X0 < XS-2 < XX0 < X-1 < XT
-2
Model 5 XS-2 < XX0 < X0 < X-1 < XT
-2
Vladan Mlinar et al., PRB 80, 165425 (2009).
Structural motifs underlying Spectral Hard Rule:
Spectral barcoding
Procedure
INPUT:
Vladan Mlinar et al., PRB 80, 165425 (2009).
Structural motifs underlying Spectral Hard Rule:
Spectral barcoding
Procedure
INPUT:
OUTPUT:
Primary structural
Motifs
1. Height (h)
2. Base-length (b)
3. Average In
composition (XIn) Vladan Mlinar et al., PRB 80, 165425 (2009).
Spectroscopy→Theory→Structure closes the Loop!
Spectroscopy→Theory→Structure closes the Loop!
• More than one dot can be constructed!
• Spectral Hard Rules are satisfied by
the construction!Vladan Mlinar et al., PRB 80, 165425 (2009).
Conclusions:
Spectral Barcoding: Procedure for deciphering structural motifs from the multiexcitonic spectra
• We established missing structural basis for QD spectroscopy
• We offer spectroscopically-derived structural motifs that combined with
X-STM measurements give more realistic QD structure.
Thank you for your attention!
Vladan Mlinar et al., PRB 80, 165425 (2009).
Vladan Mlinar and Alex Zunger, PRB 80, 035328 (2009).
Basic Paradigm of Spectroscopy of Molecules
Structure
• To understand the spectra one must know the structure
(hence symmetry) of the molecule
• Structure-spectra relationship in molecules has historically been
facilitated by the accumulated knowledge on electronic and vibrational
spectral fingerprints of specific groups making up the molecules
• Deliberate design of molecules with given properties
Spectroscopic vs. Geometrical QD size:
Can we construct a model QD that has geometrical size as extracted from XSTM, but
spectroscopic size as deduced by spectral barcoding?
XSTM deduced Model QDs:
Model 1 Model 2
Model 5
Model 3 Model 4
• Truncated cone
• No wetting layer
• Truncated pyramid
• No wetting layer
• Truncated pyramid
• No wetting layer
• Ellipsoid
• No wetting layer
• Truncated cone
• Includes wetting layer