6533b7d8fe1ef96bd1269872
RESEARCH PRODUCT
Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy
J. PuransAndris AnspoksAnatoly I. FrenkelAnatoly I. FrenkelAlexei KuzminArturs CintinsJanis Timoshenkosubject
AusteniteWork (thermodynamics)Materials scienceGeneral Physics and Astronomy02 engineering and technology021001 nanoscience & nanotechnologyRadial distribution function01 natural sciencesSpectral lineX-ray absorption fine structureChemical physics0103 physical sciences:NATURAL SCIENCES:Physics [Research Subject Categories]010306 general physics0210 nano-technologySpectroscopyAbsorption (electromagnetic radiation)Curse of dimensionalitydescription
AIF acknowledge support by the US Department of Energy, Office of Basic Energy Sciences under Grant No. DE-FG02 03ER15476. AIF acknowledges support by the Laboratory Directed Research and Development Program through LDRD 18-047 of Brookhaven National Laboratory under U.S. Department of Energy Contract No. DE-SC0012704 for initiating his research in machine learning methods. The help of the beamline staff at ELETTRA (project 20160412) synchrotron radiation facility is acknowledged. RMC-EXAFS and MD-EXAFS simulations were performed on the LASC cluster-type computer at Institute of Solid State Physics of the University of Latvia.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-01 | Physical Review Letters |