Advanced Powder Technology, Journal Year: 2024, Volume and Issue: 36(1), P. 104756 - 104756
Published: Dec. 26, 2024
Language: Английский
Advanced Powder Technology, Journal Year: 2024, Volume and Issue: 36(1), P. 104756 - 104756
Published: Dec. 26, 2024
Language: Английский
Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 111577 - 111577
Published: Jan. 1, 2025
Language: Английский
Citations
1Microchemical Journal, Journal Year: 2025, Volume and Issue: unknown, P. 112892 - 112892
Published: Jan. 1, 2025
Language: Английский
Citations
1Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: unknown, P. 115249 - 115249
Published: Dec. 1, 2024
Language: Английский
Citations
8Microchemical Journal, Journal Year: 2025, Volume and Issue: 209, P. 112646 - 112646
Published: Jan. 4, 2025
Language: Английский
Citations
0Colloids and Surfaces A Physicochemical and Engineering Aspects, Journal Year: 2025, Volume and Issue: unknown, P. 136750 - 136750
Published: March 1, 2025
Language: Английский
Citations
0Sensors and Actuators B Chemical, Journal Year: 2025, Volume and Issue: unknown, P. 137711 - 137711
Published: March 1, 2025
Language: Английский
Citations
0Inorganic Chemistry, Journal Year: 2025, Volume and Issue: unknown
Published: May 2, 2025
Metal-organic frameworks (MOFs) hold great potential for carbon monoxide (CO) adsorption owing to their large pore volume, diverse periodic network structures, and designability. Machine learning is anticipated provide optimization parameters designing high-efficiency MOFs adsorbents, avoiding time-consuming experiments. Here, we proposed an ensemble-learning strategy accounting multidimensional analysis of features rationally design geometries, structural properties, synthesis conditions toward high performance CO adsorption. The extreme gradient boosting model exhibited the best predictive (R2 > 0.95) under limited data set size. Porous characteristic was identified as a dominant factor in pristine MOFs. Prediction results illustrated that featuring one-dimensional, two-dimensional, microporous, isolated pores were optimal adsorption, with 0.4-0.6 cm3/g total volume. This enhanced capacity can be attributed shortened molecular diffusion pathways. relative significance followed: space groups geometry topology. configuration involved group R3m, binuclear paddle wheel geometry, scorpionate-like Regarding transition metal-modified MOFs, incorporated Cu(I) demonstrated strongest binding affinity CO, while Fe(II) Ni(II) could serve effective sites. work offers theoretical guidance efficient adsorbents
Language: Английский
Citations
0Ceramics International, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 1, 2024
Language: Английский
Citations
2Advanced Powder Technology, Journal Year: 2024, Volume and Issue: 36(1), P. 104756 - 104756
Published: Dec. 26, 2024
Language: Английский
Citations
2