Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations
This study integrates first-principles calculations, computational chemistry, system simulations, experiments, and machine learning to identify redox perovskite oxides for solar thermochemical hydrogen production. Using two random forest regressions and one classification model, the approach predict...
| Autores: | , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Alcalá (UAH) |
| Repositorio: | e_Buah Biblioteca Digital Universidad de Alcalá |
| Idioma: | inglés |
| OAI Identifier: | oai:ebuah.uah.es:10017/68217 |
| Acceso en línea: | http://hdl.handle.net/10017/68217 https://dx.doi.org/10.1038/s41524-025-01726-y |
| Access Level: | acceso abierto |
| Palabra clave: | Energías Renovables/Energías Alternativas Alternative energies |
| Sumario: | This study integrates first-principles calculations, computational chemistry, system simulations, experiments, and machine learning to identify redox perovskite oxides for solar thermochemical hydrogen production. Using two random forest regressions and one classification model, the approach predicts materials" stability and the enthalpy of oxygen vacancy formation (Deltaho), a critical property for selecting materials for thermochemical hydrogen production. B-site composition significantly influences Deltaho predictions. The methodology led to the discovery of Ba0.875Ca0.125Zr0.875Mn0.125O3 (BCZM), which reduces at temperatures up to 250 °C lower than CeO2 and is expected to outperform other perovskites in water splitting. However, CeO2 remains the benchmark for solar thermochemical hydrogen production. The combined use of machine learning and DFT calculations refined 4ho predictions and provided insights into experimental results. This framework not only enhances database creation for material screening but also establishes a novel approach for perovskite discovery for hydrogen production applications. |
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