Advancing chemical engineering technology with artificial intelligence
Развитие технологий химической инженерии с помощью искусственного интеллекта
2025-07-04
SCID: 54.1/j56mauzj
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artificial intelligencechemical engineeringdigital twinsretrosynthetic analysisstructure–property relationship modeling
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Abstract (AI)
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.
Key Findings
1
AI advances structure–property relationship modeling, retrosynthetic analysis, and computational chemistry, enabling faster material optimization.
2
Applications in energy, catalysis, batteries, and water treatment demonstrate AI’s potential to address major global challenges.
3
Artificial intelligence is reshaping chemical engineering by integrating computational intelligence with experimental workflows for discovery, optimization, and scale-up.
4
Smart process control, digital twins, and automated laboratories support translation from laboratory innovations to industrial production.
5
The review identifies current limitations and proposes a roadmap toward more adaptive, intelligent, and sustainable chemical engineering.
Research Object
chemical engineering materials, processes, and industrial production systems
Research Subject
the applications and transformative impact of artificial intelligence on material discovery, process optimization, scale-up, and sustainable chemical engineering
Publication Details
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2025-07-04
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References available in scid.ai7
Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence2023
An autonomous laboratory for the accelerated synthesis of inorganic materials2023
DScribe: Library of descriptors for machine learning in materials science2019
The promise of artificial intelligence in chemical engineering: Is it here, finally?2018
Machine learning for heterogeneous catalyst design and discovery2018
Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)2024
Completing density functional theory by machine learning hidden messages from molecules2020