Computational and Machine Learning Methods for CO<sub>2</sub> Capture Using Metal–Organic Frameworks-Reference-Cited by-同舟云学术

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Computational and Machine Learning Methods for CO₂ Capture Using Metal–Organic Frameworks

Published:2024-08-22 Issue:35 Volume:18 Page:23842-23875
ISSN:1936-0851
Container-title:ACS Nano
language:en
Short-container-title:ACS Nano

Author:

Mashhadimoslem Hossein¹,Abdol Mohammad Ali¹^ORCID,Karimi Peyman¹^ORCID,Zanganeh Kourosh²,Shafeen Ahmed²,Elkamel Ali¹³^ORCID,Kamkar Milad¹^ORCID

Affiliation:

1. Chemical Engineering Department, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada

2. Natural Resources Canada (NRCan), Canmet ENERGY-Ottawa (CE-O), 1 Haanel Dr., Ottawa, ON K1A 1M1 Canada

3. Department of Chemical Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates

Funder

Natural Resources Canada

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsnano.3c13001

Reference241 articles.

1. From Unmanned Systems to Autonomous Intelligent Systems

2. Machine learning for molecular and materials science

3. Artificial Intelligence (AI) for Sustainable Resource Management and Chemical Processes

4. Nanotechnology and artificial intelligence to enable sustainable and precision agriculture

5. High-performance medicine: the convergence of human and artificial intelligence

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