Classification of local chemical environments from x-ray absorption spectra using supervised machine learning-Reference-Cited by-同舟云学术

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Classification of local chemical environments from x-ray absorption spectra using supervised machine learning

Published:2019-03-13 Issue:3 Volume:3 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Carbone Matthew R.,Yoo Shinjae,Topsakal Mehmet,Lu Deyu

Funder

U.S. Department of Energy

Brookhaven National Laboratory

Laboratory Directed Research and Development

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.3.033604/fulltext

Reference66 articles.

1. Oxygen ordering and the orthorhombic-to-tetragonal phase transition inYBa2Cu3O7−x

2. Femtosecond Structural Dynamics inVO2during an Ultrafast Solid-Solid Phase Transition

3. Battery materials for ultrafast charging and discharging

4. Design of Semiconducting TetrahedralMn1−xZnxOAlloys and Their Application to Solar Water Splitting

5. Accelerating the discovery of materials for clean energy in the era of smart automation

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