Machine learning implemented exploration of the adsorption mechanism of carbon dioxide onto porous carbons-Reference-Cited by-同舟云学术

Machine learning implemented exploration of the adsorption mechanism of carbon dioxide onto porous carbons

Published:2023-10 Issue: Volume:647 Page:174-187
ISSN:0021-9797
Container-title:Journal of Colloid and Interface Science
language:en
Short-container-title:Journal of Colloid and Interface Science

Author:

Namdeo Sarvesh,Srivastava Vimal Chandra,Mohanty Paritosh

Publisher

Elsevier BV

Subject

Colloid and Surface Chemistry,Surfaces, Coatings and Films,Biomaterials,Electronic, Optical and Magnetic Materials

Reference75 articles.

1. Global Monitoring Laboratory, Earth System Research Laboratories, Trends Atmos. Carbon Dioxide, (2022) (https://gml.noaa.gov/ccgg/trends/global.html).

2. Carbon dioxide capture in gallate-based metal-organic frameworks;Chen;Sep. Purif. Technol.,2022

3. Robust smart schemes for modeling carbon dioxide uptake in metal− organic frameworks;Amar;Fuel,2022

4. Global Warming and the Future of the Earth;Watts;Synth. Lect. Energy. Environ. Tech., sci., soc.,2007

5. Nitrogen amelioration-driven carbon dioxide capture by nanoporous polytriazine;Chaudhary;Langmuir,2019

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