Butler, K.
, Choudhary, K.
, Csanyi, G.
, Ganose, A.
, Kalinin, S.
and Morgan, D.
(2024),
Setting standards for data driven materials science, npj Computational Materials (Accessed September 16, 2026)
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Setting standards for data driven materials science
Published
Author(s)
Keith Butler, , Gabor Csanyi, Alex Ganose, Sergei Kalinin, Dane Morgan
Abstract
A young Steve Jobs once called computers 'bicycles for the mind' – he was referring to the dramatic decrease in the energetic cost of transportation that could be obtained with the bicycle, which breaks all scaling laws for how efficiently an animal can achieve motion. The creativity of new approaches to old materials science problems facilitated by the dramatic uptake of machine learning (ML) is a testament to this notion. The dramatic uptake of ML in our subject has been facilitated by exceptional efforts to provide open datasets, e.g. NIST-JARVIS, NOMAD, Materials Project, Aflow, OQMD and many others, as well as the extremely high quality of openly available software packages such as scikit-learn, PyTorch, JAX, Quantum Espresso, LAMMPS. These resources, along with continued extraordinary developments in hardware, are helping a wide-range of researchers integrate ML into their work.Citation
npj Computational Materials
Pub Type
Journals
Citation
Issues
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Created October 1, 2024, Updated November 15, 2024