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Tutorial: Mapping the space of materials and molecules

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If you have a question about this talk, please contact Bingqing Cheng .

Datasets in physics, chemistry and materials have become larger and larger. A typical dataset contains thousands to millions of atomistic structures, along with many physical properties.

In this tutorial, we will introduce a data-driven and automated workflow for visualizing and analyzing such structural datasets. We will first discuss about the underlying priciples, and then perform live demos using a command line tool, ASAP (https://github.com/BingqingCheng/ASAP). Finall we will showcase chemiscope.org and an interactive visualiser that works with ABCD (https://github.com/libAtoms/abcd).

This talk is part of the Machine learning in Physics, Chemistry and Materials discussion group (MLDG) series.

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