Advancing chemical engineering technology with artificial intelligence

Chuxuan Ding; Xin Gui; Jun Jiang

doi:10.1093/ce/zkaf036

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Advancing chemical engineering technology with artificial intelligence

更新时间：2026-01-15

- Advancing chemical engineering technology with artificial intelligence
- Advancing chemical engineering technology with artificial intelligence
- 清洁能源（英文） 2025年第5期
- 作者机构：
  
  1. State Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China
  2. Hefei National Laboratory, University of Science and Technology of China
- 作者简介：
- 基金信息：
  
  J.J. acknowledge the Strategic Priority Research Program of the Chinese Academy of Sciences for funding (Grant XDB0450302). J.J. acknowledges the National Natural Science Foundation of China (Grants 22025304, 22033007), the Innovation Program for Quantum Science and Technology (2021ZD0303303), and the CAS Project for Young Scientists in Basic Research (Grant YSBR-005) for funding.
- DOI：10.1093/ce/zkaf036
  中图分类号：
- 纸质出版：2025
- 稿件说明：
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Chuxuan Ding, Xin Gui, Jun Jiang. Advancing chemical engineering technology with artificial intelligence[J]. 清洁能源（英文）, 2025,(5).

Chuxuan Ding, Xin Gui, Jun Jiang, Advancing chemical engineering technology with artificial intelligence, Clean Energy, Volume 9, Issue 5, October 2025, Pages 55–74, https://doi.org/10.1093/ce/zkaf036
Chuxuan Ding, Xin Gui, Jun Jiang. Advancing chemical engineering technology with artificial intelligence[J]. 清洁能源（英文）, 2025,(5). DOI： 10.1093/ce/zkaf036.

Chuxuan Ding, Xin Gui, Jun Jiang, Advancing chemical engineering technology with artificial intelligence, Clean Energy, Volume 9, Issue 5, October 2025, Pages 55–74, https://doi.org/10.1093/ce/zkaf036 DOI：

摘要

Abstract

Artificial intelligence is fundamentally transforming chemical engineering by redefining how materials are discovered

processes are optimized

and innovations are deployed at scale. This review provides a unique perspective on artificial intelligence’s role as a catalyst for chemical engineering’s evolution

emphasizing its ability to synergize computational intelligence with experimental workflows. Key contributions include artificial intelligence-enabled breakthroughs in structure–property relationship modeling

retrosynthetic analysis

and computational chemistry for rapid material optimization

followed by artificial intelligence’s impact on industrial translation through smart process control

digital twins

and automated laboratories

which facilitates seamless scaling from laboratory innovation to industrial production. Specific applications in energy

catalysis

batteries

and water treatment demonstrate artificial intelligence’s potential to address critical global challenges. By critically evaluating limitations and offering a roadmap for future advancements

this review highlights artificial intelligence not just as a tool but as a transformative force driving a more adaptive

intelligent

and sustainable chemical engineering paradigm.

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