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May 2017

PatentsOrganic Chemistry Catalyst

Trends in Organic Chemistry Catalyst in

IP

▪A Patent Intelligence study

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Catalyst code (B01J2...) AND organic chemistry code (C07)

OR

Organic chemistry catalyst code (C07C25...)

OR

Polymerization catalyst code (C08F4)

NOT CN patents

AND

From 1995 to now

PATENT SEARCH STRATEGY FOR ORGANIC CHEMISTRY CATALYSTS

SEARCH STRATEGY

46,166 patent families

148,502 patent families

128,242 patent families

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NORMALIZED PATENT ACTIVITY

PATENT STATISTICS

Global patent database-CN in

Organic Chemistry Catalyst-CN in

Organic Chemistry Catalyst-CN out

Global patent database-CN out

Conclusion: after a sharp decline in early 2000s, the patent activity in organic chemistry catalysts is a little bit more dynamic than the global patent database when CN patents are excluded.Chinese patents are excluded because they bias patent statistics (low quality and too many patents)

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Why?

Analyzing geographic R&D trends is more relevant through applicant citizenship (country of origin).

GEOGRAPHIC ANALYSIS: APPLICANT CITIZENSHIP

PATENT STATISTICS

Conclusion:Patent activity of Chinese applicants is booming since early 2000’s while the activity of JP applicants droped dramatically. Significant rise for Korean applicants and Saudi applicants.

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GEOGRAPHIC ANALYSIS: EUROPEAN APPLICANTS

PATENT STATISTICS

Conclusion:Since years 2000’s, the patent activity in the field of organic chemistry catalyt is rising for Russian, Austrian, and Polishapplicants.

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TOP 20 APPLICANTS IN ORGANIC CHEMISTRY CATALYST

PATENT STATISTICS

Conclusion:Most of the big applicants experienced a significant drop in IP in early 2000’s. Since the 2010’s, some are recovering a significant activity, like BASF, Sumitomo, Exxonmobil, and Dow.

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Applicants with top growing patent activity over the period 2010-2015.

Growth is calculated with a regression formula.

MOST DYNAMIC APPLICANTS

PATENT STATISTICS

Applicant 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Evonik 13 19 22 34 32 40 45 54 31 21 32 23 14 21 9 5 10 10 12 27 32

SABIC 2 1 1 12 11 10 6 11 16 8 20 20 13 13 10 14 36 43 73

LG chemical ltd 2 1 3 7 8 2 9 8 17 14 22 36 41 24 31 38 36 23 41 88

CNRS 1 2 4 2 3 4 2 14 11 3 15 14 16 9 18 9 15 22 18

Chevron Phillips chemical 2 3 7 5 19 10 10 7 17 14 7 15 17 17 20

Shell 32 31 33 13 14 19 35 14 20 33 23 20 25 31 21 27 32 27 47 45 47

Exxonmobil 130 86 79 74 72 65 74 103 93 76 69 63 73 58 69 43 61 74 71 93 69

Toho titanium co ltd 10 9 8 9 14 1 13 7 2 1 2 8 10 1 4 14 16 3

IFP energies nouvelles 29 26 25 28 33 34 25 9 17 11 13 13 10 15 24 19 21 16 30 26 28

BASF 88 112 150 153 163 125 113 150 117 139 74 47 101 74 56 42 50 92 91 107 49

Borealis 8 16 19 17 25 17 11 10 14 9 2 3 14 13 14 24 21 21 22 23 34

China petrochemical corp 1 3 5 5 2 6 9 9 2 5 5 5 5 2 2 5 18 17 8 10 10

Conclusion:Newcomers are SABIC, CNRS, LG chemicals, and China petrochemicals. For most other players, the increased activity follows a significant drop during the 2000’s.

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Number of patent families per top IPC codes

TOP IPC CODES

PATENT STATISTICS

Conclusion:Top domains are polymerization catalyst, organometallic catalyst, and olefin polymerization

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Definition

When a patent code starts to be present in a patent pool, it may mean that catalysts are being used in new applications, or that other technologies start to be used within a catalytic process or to produce catalyst.

NEW (PATENT) CODE CLUSTERS

NEW CODE CLUSTERS

Number of different IPC codes in the pool about organic chemistry catalysts

Period 1900 to 1994 =

1,843 different IPC

codes

Period 1900-2009 =

2,150 different IPC

codes

Period 1900-2017 =

2,243 different IPC

codes

307 new code

clusters

93 new code

clusters

Conclusion: new code clusters can be seen as footprint of technological trends or spreading towards new applicationsNote: not to be confused with CPC code Combination sets

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Reasoning: use of combinatorial chemistry and computational chemistry to research new catalyst or ligands, egfor chiral catalysis or supramolecular catalysis

SCREENING CHEMICAL LIBRAIRIES, EG IN SILICO SCREENING

NEW CODE CLUSTERS

SOURCE: 2000, UNIV SOUTHERN CALIFORNIA, WO0024510A1Combinatorial chemistry approach to chiral catalyst engineering and screening: rational design and serendipity

Exploration of catalyst reaction with computational chemistry Supramolecular catalysis

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Reasoning: using Quantitative Structure Activity Relationships models to desing novel catalyst, eg with deep machine learning techniques.

CHEMOINFORMATICS

NEW CODE CLUSTERS

SOURCE: 2015, CHEVRON PHILLIPS CHEMICAL CO, US2015178475A1

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Reasoning: bimodal polymerization provide both strength and stiffness of high MW polymers HDPE, whilst retaining the high-stress-crack resistance and processability of lower MW polymers

BIMODAL POLYMERIZATION

NEW CODE CLUSTERS

SOURCE: 2002, ATOFINA RES,SOLVAY, EP1201713A1

Properties of bimodal High Density Polyethylene:

• higher stiffness (higher density),

• higher chemical resistance,

• higher impact,

• low die swell (Barus effect),

• low degradation,

• no bad odor.

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Reasoning: at nanoscale, not only the surface area is higher, but they are unique quantum effects that can dramatically change the catalytic characteristics such as activity, selectivity, and stability.

NANOCATALYST

NEW CODE CLUSTERS

SOURCE: 2013, UNIV WITWATERSRAND JHB, WO2013042048A1

Metallic gold is quite inefficient as catalyst. However, goldnanoparticles exhibit suprising catalytic activity, but limited by stabilityissue

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Reasoning: mining certain rare elements is not unlimited. In the future, we may extract those metal from other sources like urban mining or metal-accumulating plants.

NON-CONVENTIONAL CATALYST SOURCE

NEW CODE CLUSTERS

SOURCE: 2014, CNRS, EP2769765A1

Extraction of metals through metal accumulatingplants followed by calcination and extraction

Urban mining: recovery of precious metalfrom consumer electronic wastes

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Reasoning: wood-based bioethanol is green, but on average 30 wt% of woody material is lignin. We must find technologies to valorize lignin waste and catalytic depolymerization is key.

LIGNIN DEPOLYMERIZATION

NEW CODE CLUSTERS

SOURCE: 2016, ALLIANCE SUSTAINABLE ENERGY, US2016052949A1

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▪ Patent activity in organic chemistry catalyst is dynamic compared to the global patent database

▪ Newly active countries in IP are China, Russia, Saudi Arabia, and Poland

▪ Petrochemistry is highly represesented in IP about organic chemistry catalysts

▪ Advanced catalysts for polyolefins are one of the main reasons for taking over engineering polymers

▪ Computational chemistry already used in catalysis science, but may benefit from new Machine Learning

techniques like QSAR

▪ Nanocatalysts likely to be disruptive in different catalyst applications

▪ Scarcity of certain rare elements is a threat/opportunity for organic chemistry catalyst

▪ Big need for catalytic systems for biomass valorization

CONCLUSION

CONCLUSION

“We want to draw your attention to the fact that we drafted the examples within this document with all applicable diligence and care but, given the nature of this complicated matter, it is impossible to guarantee the completeness and exactness of the provided information.”

JEF VANDENBERGHEManaging Partner

+ 32 496 94 51 43 – j@creax.com

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