Machine learning and high-throughput computational screening of hydrophobic metal–organic frameworks for capture of formaldehyde from air

Xueying Yuan; Xiaomei Deng; Chengzhi Cai; Zenan Shi; Hong Liang; Shuhua Li; Zhiwei Qiao

doi:10.1016/j.gee.2020.06.024

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Machine learning and high-throughput computational screening of hydrophobic metal–organic frameworks for capture of formaldehyde from air

Xueying Yuan Xiaomei Deng Chengzhi Cai Zenan Shi Hong Liang Shuhua Li Zhiwei Qiao

Year: 2020 Journal: Green Energy & Environment Vol: 6 (5)Pages: 759-770 Publisher: KeAi

DOI: 10.1016/j.gee.2020.06.024

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Keywords:

Adsorption Formaldehyde Metal-organic framework Support vector machine Random forest Univariate Metric (unit) Selectivity Extreme learning machine Computer science Materials science Artificial neural network Biological system Machine learning Artificial intelligence Chemistry Multivariate statistics Physical chemistry Organic chemistry Engineering

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Metal-Organic Frameworks: Synthesis and Applications

Physical Sciences → Chemistry → Inorganic Chemistry

Covalent Organic Framework Applications

Physical Sciences → Materials Science → Materials Chemistry

Catalytic Processes in Materials Science

Physical Sciences → Materials Science → Materials Chemistry

Machine learning and high-throughput computational screening of hydrophobic metal–organic frameworks for capture of formaldehyde from air

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