Data-driven materials discovery The Royal Society

Data-driven materials discovery The Royal Society

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Data-driven materials discovery The Royal Society
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Join us for the 2020 Clifford Paterson Lecture, delivered by Professor Jacqui Cole.

#crystallography #chemistry #energy #materials #ai

Join the discussion: https://app.sli.do/event/ovdxfNLv5bS1gHViyN9P14

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Professor Jacqueline Cole received the 2020 Clifford Paterson Medal and Lecture for the development of photocrystallography and the discovery of new high-performance non-linear optical materials and light-harvesting dyes using molecular design rules. After a two-year delay due to the global pandemic, Professor Cole now has the opportunity to deliver the award lecture.

Professor Cole will describe how to combine the predictive power of artificial intelligence with data science and algorithms to discover new materials for the energy sector. A design-to-device material discovery pipeline will be demonstrated. Large-scale data mining workflows are developed to successfully predict new chemicals that have a targeted functionality.

Nevertheless, the success of such a data-driven approach to materials discovery is dependent on having the right data source to mine. It also requires algorithms that appropriately encode structure-function relationships into data mining workflows that progressively shortlist data for the prediction of a lead material for experimental validation. The lecture shows how appropriate data are obtained, algorithms are designed and used in predictions, and how these predictions are confirmed by experiments.

The Royal Society is a Fellowship of many of the world's leading scientists and is the oldest scientific academy still in existence.

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