AI3SD Video: Quantifying crystal similarity

Cumby, James (2021) AI3SD Video: Quantifying crystal similarity. Kanza, Samantha, Frey, Jeremy G. and Hooper, Victoria (eds.) Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom. 06 Jul - 24 Aug 2021. (doi:10.5258/SOTON/P0142).

Record type: Conference or Workshop Item (Other)

Abstract

This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the eleventh talk in the ML4MC series and formed part of the session "Mentor Talks".

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Ml4MC-JamesCumby-100821 - Version of Record

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Published date: 10 August 2021

Additional Information: James is a lecturer in inorganic chemistry, with a focus on discovering new solid state materials with useful properties such as magnetism, ionic or electronic conductivity, and negative thermal expansion. His research combines experimental syntheses and characterisation with computational methods such as machine learning and electronic structure calculations; atomic structure (both periodic and short-ranging) underpins all of this work. James obtained his PhD in solid state chemistry from the University of Birmingham, and before his current position worked as a postdoctoral researcher at the University of Edinburgh.

Venue - Dates: Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom, 2021-07-06 - 2021-08-24

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