Prediction of ELNES and Quantification of Structural Properties Using Artificial Neural Network
Source abstract
Abstract
Shin Kiyohara, Masashi Tsubaki, Teruyasu Mizoguchi; Prediction of ELNES and Quantification of Structural Properties Using Artificial Neural Network, Micros
Only a short abstract or summary was supplied by the source.
Source: openalex_inverted_index · Quality: short
Research context
OpenAlex topics: Machine Learning in Materials Science · Hydrogen embrittlement and corrosion behaviors in metals · X-ray Diffraction in Crystallography
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References (8)
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1. [6] Kiyohara, S. and Mizoguchi, T. , in preparation.
2. [8] The authors acknowledge funding from JST-PRESTO (JPM-JPR16NB 16814592), MEXT, under grantnos. 18J11573, 17H06094, 19H00818 and 19H05787 as well as the special fund of the Institute of Industrial Science, University of Tokyo (Tenkai5504850104)
3. 10.1088/2515-7639/ab0b6810.1088/2515-7639/ab0b68 ↗
4. Mizoguchi · Microscopy · 2020 · 1
5. 10.1063/1.481232310.1063/1.4812323 ↗
6. 10.1038/s41524-019-0196-x10.1038/s41524-019-0196-x ↗
7. 10.1038/s41467-018-06972-x10.1038/s41467-018-06972-x ↗
8. [3] Kiyohara, S. , submitted.