Título:
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Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks
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Autor/a:
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Pablo-García, Sergio; Morandi, Santiago; Vargas-Hernández, Rodrigo A.; Jorner, Kjell; Ivković, Žarko; López, Núria; Aspuru-Guzik, Alán
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Abstract:
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Modeling in heterogeneous catalysis requires the extensive evaluation of the energy of molecules adsorbed on surfaces. This is done via density functional theory but for large organic molecules it requires enormous computational time, compromising the viability of the approach. Here we present GAME-Net, a graph neural network to quickly evaluate the adsorption energy. GAME-Net is trained on a well-balanced chemically diverse dataset with C1–4 molecules with functional groups including N, O, S and C6–10 aromatic rings. The model yields a mean absolute error of 0.18 eV on the test set and is 6 orders of magnitude faster than density functional theory. Applied to biomass and plastics (up to 30 heteroatoms), adsorption energies are predicted with a mean absolute error of 0.016 eV per atom. The framework represents a tool for the fast screening of catalytic materials, particularly for systems that cannot be simulated by traditional methods. |
Fecha de creación:
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01-05-2023 |
Materias (CDU):
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00 - Ciència i coneixement. Investigació. Cultura. Humanitats |
Materia(s):
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Química |
Derechos:
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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Páginas:
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10 p. |
Tipo de documento:
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Artículo Artículo - Versión publicada |
DOI:
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10.1038/s43588-023-00437-y
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Editor:
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Springer Nature
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Compartir:
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