High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model

The high porosity and tunable chemical functionality of metal-organic frameworks (MOFs) make it a promising catalyst design platform. High-throughput screening of catalytic performance is feasible since the large MOF structure database is available. In this study, we report a machine learning model...

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Xehetasun bibliografikoak

Egile Nagusiak:	Xuefeng Bai, Yi Li, Yabo Xie, Qiancheng Chen, Xin Zhang, Jian-Rong Li
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	KeAi Communications Co., Ltd. 2025-01-01
Saila:	Green Energy & Environment
Gaiak:	Metal-organic frameworks High-throughput screening Machine learning Explainable model CO2 cycloaddition
Sarrera elektronikoa:	http://www.sciencedirect.com/science/article/pii/S2468025724000323
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