Porous Carbon Materials: from Traditional Synthesis, Machine Learning‐Assisted Design, to Their Applications in Advanced Energy Storage and Conversion

Abstract Porous carbon materials (PCMs) have long played key roles in energy storage and conversion fields, known for their abundant raw materials, tunable pore structures, large surface area, and excellent conductivity. Despite significant progress, there remains a substantial gap between the precise design of PCMs and the full utilization of their unique properties for developing high‐performance electrode materials. Herein, this review systematically and comprehensively introduces PCMs from traditional synthesis, machine learning‐assisted design principles to their energy storage and conversion applications. Specifically, the preparation methods for microporous, mesoporous, macroporous, and hierarchically porous carbon materials are thoroughly summarized, with an emphasis on structural control rules and formation mechanisms. It also highlights the unique advantages of PCMs in alkali metal‐ion batteries, metal–sulfur batteries, supercapacitors, and electrocatalysis. Insights from in situ and operando characterizations provide a deep understanding of the correlation between structure and performance. Finally, current challenges and future directions are discussed, emphasizing the need for further advancements to meet evolving energy storage and conversion demands. This review offers valuable guidance for the rational design of high‐performance porous carbon electrode materials, and points out key research directions for future development.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-03-18
DOI
https://doi.org/10.1002/adfm.202504272
Citations
41
Primary Topic
Advancements in Battery Materials
Type
article
Field-Weighted Citation Impact
29.22

Funders

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article

Porous Carbon Materials: from Traditional Synthesis, Machine Learning‐Assisted Design, to Their Applications in Advanced Energy Storage and Conversion

Haijiao Zhang, Jihao Li, Jieshan Qiu, Haitao Li et al.
41 citations
Advanced Functional Materials
Advancements in Battery Materials
29.22
article

Porous Carbon Materials: from Traditional Synthesis, Machine Learning‐Assisted Design, to Their Applications in Advanced Energy Storage and Conversion

Haijiao Zhang, Jihao Li, Jieshan Qiu, Haitao Li, Yan Qu
article en
41 citations

Abstract

Abstract Porous carbon materials (PCMs) have long played key roles in energy storage and conversion fields, known for their abundant raw materials, tunable pore structures, large surface area, and excellent conductivity. Despite significant progress, there remains a substantial gap between the precise design of PCMs and the full utilization of their unique properties for developing high‐performance electrode materials. Herein, this review systematically and comprehensively introduces PCMs from traditional synthesis, machine learning‐assisted design principles to their energy storage and conversion applications. Specifically, the preparation methods for microporous, mesoporous, macroporous, and hierarchically porous carbon materials are thoroughly summarized, with an emphasis on structural control rules and formation mechanisms. It also highlights the unique advantages of PCMs in alkali metal‐ion batteries, metal–sulfur batteries, supercapacitors, and electrocatalysis. Insights from in situ and operando characterizations provide a deep understanding of the correlation between structure and performance. Finally, current challenges and future directions are discussed, emphasizing the need for further advancements to meet evolving energy storage and conversion demands. This review offers valuable guidance for the rational design of high‐performance porous carbon electrode materials, and points out key research directions for future development.

Advanced Functional MaterialsVol. 35(33)
Shanghai University (CN), Beijing University of Chemical Technology (CN)
Natural Science Foundation of Shanghai
Openalex Percentile: Top 0%
Advancements in Battery Materials
29.22
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