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Grant: Collaborative Research and Development Grants

University of British Columbia

$170,261.00

Bringing Big Data to Clean Energy Materials Discovery

EF 2016-17

Résumé
The Berlinguette research program focuses on developing advanced materials for clean energy production and storage. Google research is seeking to revolutionize materials science by using machine learning techniques to help researchers solve major research questions in new ways inaccessible to humans alone. A limitation to both these research programs is the lack of a capability to rapidly generate detailed characterization data for wide ranges of novel materials.This collaborative research program seeks to develop a microfabricated platform technology for performing simultaneous high-throughput materials fabrication, characterization and screening. The resulting microfabricated devices will use a multiplexed architecture to address large numbers of thin film samples with in situ electrochemical, electrical and thermal measurements. Microscopic and spectroscopic characterization tools will also be employed. These tools will provide both practical and fundamental insights into the characteristics of the studied materials.The Berlinguette research group is a pioneer in photochemical film growth methods that result in highly active electrocatalytic films. For this reason thin film samples will be grown photochemically as well as by electrosynthesis and through vapor deposition techniques. Dispensing film growth precursors and electrolytes via a microarray printer will allow a high throughput of systematically varied compositions of both films and electrolytes to be investigated. In collaboration with Google Inc, we will develop and deploy state-of-the-art big data analysis methodologies to make optimal use of the high volume of data this platform will produce. These technologies will enable the Berlinguette group to elucidate fundamental composition- and structure-property relationships and thus identify commercially viable clean energy materials at an unrivalled pace.
Programme
Collaborative Research and Development Grants
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
502052-2016
Name nom
Berlinguette, Curtis
Department département
Chemistry
Organization id
2
Institution établissement
University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2016
Competition year année de concours
2016
Award amount
170261
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
141
Committee name en
University/Industry
Committee name fr
Universités/industrie
Area of application code
1208
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Materials sciences
Area of application fr
Sciences des matériaux
Research subject code
3401
Research subject group en
Physical chemistry
Research subject group fr
Chimie physique
Research subject en
Electrochemistry
Research subject fr
Électrochimie
Partie
1
Nb partie
3
Application title
Bringing Big Data to Clean Energy Materials Discovery
Keyword
NSERC
Application summary
The Berlinguette research program focuses on developing advanced materials for clean energy production and storage. Google research is seeking to revolutionize materials science by using machine learning techniques to help researchers solve major research questions in new ways inaccessible to humans alone. A limitation to both these research programs is the lack of a capability to rapidly generate detailed characterization data for wide ranges of novel materials.This collaborative research program seeks to develop a microfabricated platform technology for performing simultaneous high-throughput materials fabrication, characterization and screening. The resulting microfabricated devices will use a multiplexed architecture to address large numbers of thin film samples with in situ electrochemical, electrical and thermal measurements. Microscopic and spectroscopic characterization tools will also be employed. These tools will provide both practical and fundamental insights into the characteristics of the studied materials.The Berlinguette research group is a pioneer in photochemical film growth methods that result in highly active electrocatalytic films. For this reason thin film samples will be grown photochemically as well as by electrosynthesis and through vapor deposition techniques. Dispensing film growth precursors and electrolytes via a microarray printer will allow a high throughput of systematically varied compositions of both films and electrolytes to be investigated. In collaboration with Google Inc, we will develop and deploy state-of-the-art big data analysis methodologies to make optimal use of the high volume of data this platform will produce. These technologies will enable the Berlinguette group to elucidate fundamental composition- and structure-property relationships and thus identify commercially viable clean energy materials at an unrivalled pace.