A Bayesian framework for adsorption energy prediction on bimetallic alloy catalysts
Abstract For high-throughput screening of materials for heterogeneous catalysis, scaling relations provides an efficient scheme to estimate the chemisorption energies of hydrogenated species. However, conditioning on a single descriptor ignores the model uncertainty and leads to suboptimal predictio...
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Autores principales: | , , , |
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Formato: | article |
Lenguaje: | EN |
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Nature Portfolio
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/49cb2d1a410e45efa84ac22648868d1b |
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