Effect of adsorbent loading on NaNiRu-DFMs' CO2 capture and methanation: finding optimal Naloading using Bayesian optimisation guided experiments
Designing dual function materials (DFMs) entails an optimisation of CO2 adsorption and catalytic conversion activity, often requiring a large number of experimental parametric studies screening various types and loadings of adsorbent and catalyst components. In this study, we used a Gaussian process...
| Autores: | , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/178855 |
| Acesso em linha: | https://hdl.handle.net/11441/178855 https://doi.org/10.1039/d5im00019j |
| Access Level: | acceso abierto |
| Palavra-chave: | DFM ICCC Methanation Gaussian process Bayesian optimisation |
| Resumo: | Designing dual function materials (DFMs) entails an optimisation of CO2 adsorption and catalytic conversion activity, often requiring a large number of experimental parametric studies screening various types and loadings of adsorbent and catalyst components. In this study, we used a Gaussian process model optimised with Bayesian optimisation (BO) to find the DFM composition leading to the highest methanation activity. We focused on optimising Na (adsorbent) loading in a DFM where Na loading was varied from 2.5–15% by weight. The results from the experimental tests indicated that the sample with the highest Na-loading (15 wt%) possessed the highest CO2 desorption during CO2-TPD, however, it was not the best DFM, as it did not show the highest methane production. By testing Bayesian optimisation recommended experiments we identified 7.9 wt% Na as the optimal Na loading, which showed the highest methane production for a cycle (398.6 μmol gDFM−1) at 400 °C. This forms a case study for how BO can help accelerate materials discovery for DFMs. |
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