Your browser doesn't support javascript.
loading
Integrating Multiscale Simulation with Machine Learning to Screen and Design FIL@COFs for Ethane-Selective Separation.
Cao, Xiaohao; Han, Qi; Han, Rongmei; Zhang, Shitong; Wang, Min; Zhang, Zhengqing; Zhong, Chongli.
Afiliación
  • Cao X; State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, P. R. China.
  • Han Q; School of Material Science and Engineering, Tiangong University, Tianjin 300387, P. R. China.
  • Han R; State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, P. R. China.
  • Zhang S; School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, P. R. China.
  • Wang M; State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, P. R. China.
  • Zhang Z; School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, P. R. China.
  • Zhong C; State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, P. R. China.
ACS Appl Mater Interfaces ; 16(21): 27360-27367, 2024 May 29.
Article en En | MEDLINE | ID: mdl-38755957
ABSTRACT
Efficient and economical separation of C2H6/C2H4 is an imperative and extremely challenging process in the petrochemical industry. The C2H6-selective adsorbents with high working capacity and high selectivity are highly desirable from a practical application standpoint. In this study, we constructed a database of fluorinated ionic liquid@covalent organic frameworks (FIL@COFs) and screened out the high-performing FIL@COFs for C2H6-selective separation. Utilizing the optimal machine learning (ML) algorithm (XGBoost) and hyperparameters, we further revealed the key factors influencing the separation performance. The multiscale simulation not only validated the prediction accuracy of ML but also demonstrated that adjusting the largest cavity diameter of COFs with FILs could yield FIL@COFs with high performance for C2H6-selective separation. Our work provides essential guidance for designing new FIL@COF adsorbents for value-added gas purification.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Appl Mater Interfaces Asunto de la revista: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Appl Mater Interfaces Asunto de la revista: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos