Matches in SemOpenAlex for { <https://semopenalex.org/work/W4225904192> ?p ?o ?g. }
- W4225904192 abstract "Abstract X-ray absorption spectroscopy (XAS) is a well-established method for in-depth characterization of electronic structure. In practice hundreds of energy-points should be sampled during the measurements, and most of them are redundant. Additionally, it is also tedious to estimate reasonable parameters in the atomic Hamiltonians for mechanistic understanding. We implement an Adversarial Bayesian optimization (ABO) algorithm comprising two coupled BOs to automatically fit the many-body model Hamiltonians and to sample effectively based on active learning (AL). Taking NiO as an example, we find that less than 30 sampling points are sufficient to recover the complete XAS with the corresponding crystal field and charge transfer models, which can be selected based on intuitive hypothesis learning. Further applications on the experimental XAS spectra reveal that less than 80 sampling points give reasonable XAS and reliable atomic model parameters. Our ABO algorithm has a great potential for future applications on automated physics-driven XAS analysis and AL sampling." @default.
- W4225904192 created "2022-05-05" @default.
- W4225904192 creator A5012429429 @default.
- W4225904192 creator A5041276010 @default.
- W4225904192 creator A5049290197 @default.
- W4225904192 creator A5054838883 @default.
- W4225904192 creator A5056525023 @default.
- W4225904192 creator A5060392299 @default.
- W4225904192 creator A5068651346 @default.
- W4225904192 date "2023-03-30" @default.
- W4225904192 modified "2023-09-30" @default.
- W4225904192 title "Autonomous atomic Hamiltonian construction and active sampling of X-ray absorption spectroscopy by adversarial Bayesian optimization" @default.
- W4225904192 cites W1480330138 @default.
- W4225904192 cites W1549228047 @default.
- W4225904192 cites W1964753476 @default.
- W4225904192 cites W1971643633 @default.
- W4225904192 cites W2001369661 @default.
- W4225904192 cites W2013761935 @default.
- W4225904192 cites W2016367977 @default.
- W4225904192 cites W2024011040 @default.
- W4225904192 cites W2039081246 @default.
- W4225904192 cites W2044854403 @default.
- W4225904192 cites W2047555473 @default.
- W4225904192 cites W2050339132 @default.
- W4225904192 cites W2054622832 @default.
- W4225904192 cites W2064821379 @default.
- W4225904192 cites W2072736313 @default.
- W4225904192 cites W2085248010 @default.
- W4225904192 cites W2087672863 @default.
- W4225904192 cites W2091735324 @default.
- W4225904192 cites W2096465965 @default.
- W4225904192 cites W2103632014 @default.
- W4225904192 cites W2129781958 @default.
- W4225904192 cites W2169027522 @default.
- W4225904192 cites W2192203593 @default.
- W4225904192 cites W2484932966 @default.
- W4225904192 cites W2605966753 @default.
- W4225904192 cites W2784209861 @default.
- W4225904192 cites W2962692198 @default.
- W4225904192 cites W3014098762 @default.
- W4225904192 cites W3035572042 @default.
- W4225904192 cites W3049774692 @default.
- W4225904192 cites W3145299736 @default.
- W4225904192 cites W3183645185 @default.
- W4225904192 cites W3193408754 @default.
- W4225904192 cites W4211049957 @default.
- W4225904192 cites W4211177544 @default.
- W4225904192 cites W4211256316 @default.
- W4225904192 cites W4220831513 @default.
- W4225904192 cites W619106852 @default.
- W4225904192 cites W97187038 @default.
- W4225904192 doi "https://doi.org/10.1038/s41524-023-00994-w" @default.
- W4225904192 hasPublicationYear "2023" @default.
- W4225904192 type Work @default.
- W4225904192 citedByCount "0" @default.
- W4225904192 crossrefType "journal-article" @default.
- W4225904192 hasAuthorship W4225904192A5012429429 @default.
- W4225904192 hasAuthorship W4225904192A5041276010 @default.
- W4225904192 hasAuthorship W4225904192A5049290197 @default.
- W4225904192 hasAuthorship W4225904192A5054838883 @default.
- W4225904192 hasAuthorship W4225904192A5056525023 @default.
- W4225904192 hasAuthorship W4225904192A5060392299 @default.
- W4225904192 hasAuthorship W4225904192A5068651346 @default.
- W4225904192 hasBestOaLocation W42259041921 @default.
- W4225904192 hasConcept C11413529 @default.
- W4225904192 hasConcept C119824511 @default.
- W4225904192 hasConcept C120665830 @default.
- W4225904192 hasConcept C121332964 @default.
- W4225904192 hasConcept C121864883 @default.
- W4225904192 hasConcept C126255220 @default.
- W4225904192 hasConcept C130787639 @default.
- W4225904192 hasConcept C140779682 @default.
- W4225904192 hasConcept C154945302 @default.
- W4225904192 hasConcept C185592680 @default.
- W4225904192 hasConcept C2778049539 @default.
- W4225904192 hasConcept C32891209 @default.
- W4225904192 hasConcept C33923547 @default.
- W4225904192 hasConcept C41008148 @default.
- W4225904192 hasConcept C62284982 @default.
- W4225904192 hasConcept C62520636 @default.
- W4225904192 hasConcept C94915269 @default.
- W4225904192 hasConceptScore W4225904192C11413529 @default.
- W4225904192 hasConceptScore W4225904192C119824511 @default.
- W4225904192 hasConceptScore W4225904192C120665830 @default.
- W4225904192 hasConceptScore W4225904192C121332964 @default.
- W4225904192 hasConceptScore W4225904192C121864883 @default.
- W4225904192 hasConceptScore W4225904192C126255220 @default.
- W4225904192 hasConceptScore W4225904192C130787639 @default.
- W4225904192 hasConceptScore W4225904192C140779682 @default.
- W4225904192 hasConceptScore W4225904192C154945302 @default.
- W4225904192 hasConceptScore W4225904192C185592680 @default.
- W4225904192 hasConceptScore W4225904192C2778049539 @default.
- W4225904192 hasConceptScore W4225904192C32891209 @default.
- W4225904192 hasConceptScore W4225904192C33923547 @default.
- W4225904192 hasConceptScore W4225904192C41008148 @default.
- W4225904192 hasConceptScore W4225904192C62284982 @default.
- W4225904192 hasConceptScore W4225904192C62520636 @default.
- W4225904192 hasConceptScore W4225904192C94915269 @default.
- W4225904192 hasFunder F4320312210 @default.
- W4225904192 hasFunder F4320320879 @default.