Machine learning in crystallography and structural science

Research output: Contribution to journalEditorial

14 Scopus citations

Abstract

An overview of the virtual collection on machine learning (ML) in crystallography and structural science, as represented in Acta Crystallographica Sections A, B and D, IUCrJ and Journal of Synchrotron Radiation, is presented. Some terms and concepts related to artificial intelligence and machine learning are briefly introduced and described, and a short history of ML in structural science as it appeared in these IUCr journals is given to whet the appetite for the rest of the collection.

Original languageEnglish
Pages (from-to)139-145
Number of pages7
JournalActa Crystallographica Section A: Foundations and Advances
Volume80
Issue numberPt 2
DOIs
StatePublished - Jan 26 2024

Funding

SJLB acknowledges support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (DOE-BES) under contract No. DE-SC0024141. Work at Oak Ridge National Laboratory was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, US Department of Energy.

Keywords

  • IUCr Journals
  • artificial intelligence
  • deep learning
  • machine learning
  • neural networks

Fingerprint

Dive into the research topics of 'Machine learning in crystallography and structural science'. Together they form a unique fingerprint.

Cite this