Natural products derived porous carbons for CO2 capture

Mobin Safarzadeh Khosrowshahi, Hossein Mashhadimoslem, Hadi Shayesteh, Gurwinder Singh, Elnaz Khakpour, Xinwei Guan, Mohammad Rahimi, Farid Maleki, Prashant Kumar, Ajayan Vinu*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

As it is now established that global warming and climate change are a reality, international investments are pouring in and rightfully so for climate change mitigation. Carbon capture and separation (CCS) is therefore gaining paramount importance as it is considered one of the powerful solutions for global warming. Sorption on porous materials is a promising alternative to traditional carbon dioxide (CO2) capture technologies. Owing to their sustainable availability, economic viability, and important recyclability, natural products-derived porous carbons have emerged as favorable and competitive materials for CO2 sorption. Furthermore, the fabrication of high-quality value-added functional porous carbon-based materials using renewable precursors and waste materials is an environmentally friendly approach. This review provides crucial insights and analyses to enhance the understanding of the application of porous carbons in CO2 capture. Various methods for the synthesis of porous carbon, their structural characterization, and parameters that influence their sorption properties are discussed. The review also delves into the utilization of molecular dynamics (MD), Monte Carlo (MC), density functional theory (DFT), and machine learning techniques for simulating adsorption and validating experimental results. Lastly, the review provides future outlook and research directions for progressing the use of natural products-derived porous carbons for CO2 capture.

Original languageEnglish
Article number2304289
Pages (from-to)1-50
Number of pages50
JournalAdvanced Science
Volume10
Issue number36
DOIs
Publication statusPublished - 27 Dec 2023
Externally publishedYes

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • adsorption
  • biomass
  • CO capture
  • machine learning
  • porous carbon
  • simulation
  • synthesis

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