A new partnership focused on using artificial intelligence for materials discovery has been launched. The Alliance for AI-Accelerated Materials Discovery (A3MD) has been formed by University of Toronto and McMaster University in Canada, LG Corp and French energy player Total S.A. for joint research and development (R&D) activity. A3MD, joined by world-class partners in academia and industry, is the world’s first alliance that is formed to discover materials using AI technology.

 

The alliance will be joined by Toronto University professors Ted Sargent and Alan-Aspuru-Guzik, and McMaster University Professor Drew Higgins – all world-famous scholars in the field of AI such as those involving materials informatics, computational chemistry, and large-scale experimental automation based on robot technology. Total, which has been active in carrying out AI solution development for energy data analysis, will also participate in the alliance as industry partner.

 

The alliance will also aim to develop green catalyst and next-generation optical materials by establishing various AI modeling and automation testing platforms.

 

For example, ethylene and other compounds found in petrochemical process can be produced in carbon dioxide from the atmosphere. The consortium will aim to develop a catalyst that induces chemical reaction by using machine learning and automation robotic system.

 

The Alliance for AI-Accelerated Materials Discovery (A3MD) aims to support a suite of projects to accelerate the materials discovery process in Canada, with applications from renewable energy to smartphones. 

 

“Materials discovery can be a time-consuming and expensive process – but with AI and robotic experimentation, the potential to discover new materials more efficiently is huge,” says Drew Higgins, a co-investigator of the new consortium and an assistant professor of chemical engineering at McMaster University. 

 

In partnership with industrial partners LG and TOTAL, one of the team’s priorities will be to develop and implement techniques to better understand how materials work under realistic operating conditions, also referred to as high–throughput operando characterization of materials. 

 

In part, the activities will leverage the advanced materials characterization facilities available at the Canadian Centre for Electron Microscopy at McMaster University. 

 

“The knowledge collected using this operando approach will be crucial in accelerating the process of translating new material designs from concept to application,” Higgins says. 

 

“It is a great privilege for the Faculty of Engineering to be part of the Alliance for AI-Accelerated Materials Discovery that brings together world leaders in AI, materials science and robotics to discover new materials and improve their performance for commercial use,” says Ishwar K. Puri, Dean of Engineering.  

 

In its first year, A3MD will put in place the infrastructure needed for high-throughput experimentation, including precision robotics. The team will also launch machine learning and data science bootcamps to engage a new generation of experts, including graduate students and post-doctoral fellows. 

 

In its second year, A3MD will expand its group of industry and academic partners who bring additional expertise and offer new avenues to commercialize newly developed technologies.