Iterative Approach of Experiment–Machine Learning for Efficient Optimization of Environmental Catalysts: An Example of NO(x) Selective Reduction Catalysts

[Image: see text] An iterative approach between machine learning (ML) and laboratory experiments was developed to accelerate the design and synthesis of environmental catalysts (ECs) using selective catalytic reduction (SCR) of nitrogen oxides (NO(x)) as an example. The main steps in the approach in...

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Detalles Bibliográficos
Autores principales: Chen, Yulong, Feng, Jia, Wang, Xin, Zhang, Cheng, Ke, Dongfang, Zhu, Huiyan, Wang, Shuai, Suo, Hongri, Liu, Chongxuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666265/
https://www.ncbi.nlm.nih.gov/pubmed/37393584
http://dx.doi.org/10.1021/acs.est.3c00293

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666265/
https://www.ncbi.nlm.nih.gov/pubmed/37393584
http://dx.doi.org/10.1021/acs.est.3c00293

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