LG forms global alliance to discover high-performance materials with AI

2020.09.14 10:32:50 | 2020.09.14 10:33:21

[Photo provided by LG Group]À̹ÌÁö È®´ë

[Photo provided by LG Group]

LG Group, South Korea¡¯s fourth largest conglomerate, has formed a global alliance to discover high-performance, next-generation chemical materials, using artificial intelligence (AI) and robot technologies.

LG Science Park, the business group¡¯s research and testing hub, said on Sunday that it has created The Alliance for AI-Accelerated Materials Discovery (A3MD) with University of Toronto and McMaster University in Canada and French energy player Total S.A. last week 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 company said.

As founding member, LG Group will seek to build global network for joint R&D with AI scholars in the materials sector and secure up-front AI technology for new materials development.

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 members of the alliance will promote joint projects by holding non-face-to-face video conferences and share analysis results such as data and algorithms. They plan to expand partnership by holding AI education programs, expert forums, and corporate internship programs.

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.

By Hwang Soon-min and Lee Eun-joo

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