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Harnessing AI and Robotics for Materials Discovery

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If you have a question about this talk, please contact Tameem Adel.

The Leverhulme Research Centre for Functional Materials Design aims to drive a design revolution for functional materials at the atomic scale by fusing chemical knowledge with state-of-the-art computer science and automation in an interdisciplinary team. The global importance of this vision exceeds computer-aided design for large-scale engineering structures, which has transformed modern society. The Centre will help to bridge the current design gap by fusing leading-edge synthesis concepts from the physical sciences with ideas from the forefront of computer science, alongside experts in robotics, engineering, management and social science. This discipline mix will transform our ability to design and synthesize new materials, which has far reaching implications for society. Instead of targeting specific materials or their applications, our goal is to change the way that we approach the design problem. This needs new tools, long-term thinking, and the right working environment.

In this lecture, I will outline the following areas of activity: • The use of crystal structure prediction and ‘energy-structure-function maps’ (Nature 2017) for the a priori design of functional materials, and new ideas for machine learning properties from these maps. • The use of robotic platforms for discovering catalysts for clean hydrogen production and new ideas for developing autonomous discovery protocols driven by AI. • Our programme in mobile robots and the development of cobots that are intended to work either autonomously or cooperatively in research labs alongside human researchers (below).

This talk is part of the Cambridge Big Data series.

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