18–20 Oct 2021
Europe/Paris timezone

AI Tools that Auto-generate Materials Databases for Building Data-science Platforms

Speaker

Jacqueline Cole (University of Cambridge and ISIS Neutron and Muon Facility)

Description

This presentation will introduce and exemplify the artificial intelligence tools that my group have been developing with ISIS. These use data-mining and machine-learning methods to build data-science platforms that aid materials characterisation and materials application methods. These include the incorporation of neutron scattering data. I will also show some examples of how these data-science platforms can lead to the data-driven prediction and discovery of new materials.

References to our AI tools
[1] Swain and Cole, J. Chem. Inf. Model. 2016, 56, 10, 1894–1904 www.chemdataextractor.org
[2] Mavracic, Court, Isazawa, Elliott, Cole, J. Chem. Inf. Model. 2021, 61, 9, 4280–4289 www.chemdataextractor2.org
[3] Yildirim, Cole, J. Chem. Inf. Model. 2021, 61, 3, 1136–1149 and Mukaddem, Beard, Yildirim, Cole, J. Chem. Inf. Model. 2020, 60, 5, 2492–2509 www.imagedataextractor.org
[4] Wilary and Cole, J. Chem. Inf. Model. 2021, https://doi.org/10.1021/acs.jcim.1c01017 www.reactiondataextractor.org

Primary author

Jacqueline Cole (University of Cambridge and ISIS Neutron and Muon Facility)

Presentation materials

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