Validation of non‐negative matrix factorization for rapid assessment of large sets of atomic pair distribution function data

The use of the non‐negative matrix factorization (NMF) technique is validated for automatically extracting physically relevant components from atomic pair distribution function (PDF) data from time‐series data such as in situ experiments. The use of two matrix‐factorization techniques, principal com...

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Vydané v:Journal of applied crystallography Ročník 54; číslo 3; s. 768 - 775
Hlavní autori: Liu, Chia-Hao, Wright, Christopher J., Gu, Ran, Bandi, Sasaank, Wustrow, Allison, Todd, Paul K., O'Nolan, Daniel, Beauvais, Michelle L., Neilson, James R., Chupas, Peter J., Chapman, Karena W., Billinge, Simon J. L.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.06.2021
Blackwell Publishing Ltd
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ISSN:1600-5767, 0021-8898, 1600-5767
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Shrnutí:The use of the non‐negative matrix factorization (NMF) technique is validated for automatically extracting physically relevant components from atomic pair distribution function (PDF) data from time‐series data such as in situ experiments. The use of two matrix‐factorization techniques, principal component analysis and NMF, on PDF data is compared in the context of a chemical synthesis reaction taking place in a synchrotron beam, applying the approach to synthetic data where the correct composition is known and on measured PDFs from previously published experimental data. The NMF approach yields mathematical components that are very close to the PDFs of the chemical components of the system and a time evolution of the weights that closely follows the ground truth. Finally, it is discussed how this would appear in a streaming context if the analysis were being carried out at the beamline as the experiment progressed. The use of the non‐negative matrix‐factorization technique is validated for automatically extracting physically relevant signals from atomic pair distribution function data in the context of in situ measurement with a newly developed software infrastructure.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
USDOE Office of Science (SC), Basic Energy Sciences (BES)
SC0019212; AC02-06CH11357
ISSN:1600-5767
0021-8898
1600-5767
DOI:10.1107/S160057672100265X