Theoretical Perspectives of Precision Chemistry

Precise prediction and control of chemical reactions and material properties─the central goal of precision chemistry─truly rely on accurate and efficient theoretical modeling of chemical systems. In recent years, significant progress has been made in theoretical and computational chemistry. Especially, interdisciplinary studies in the direction of the two emerging computational frontiers, artificial intelligence and quantum computation, are revolutionizing this field. Expressive neural networks can be used to represent many-electron wave functions with high accuracy, capturing strong correlations with a favorable computational cost compared to other methods. Leveraging quantum computation in quantum chemistry is also expected to deliver a quantum advantage in problems including electronic structure calculations. With artificial intelligence and quantum computation, we expect to establish a unified, high-precision, and scalable computational foundation for generating accurate quantum chemical data essential for precision chemistry.

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Publication Details

Journal
Precision Chemistry
Published
2026-02-24
DOI
https://doi.org/10.1021/prechem.5c00382
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

Theoretical Perspectives of Precision Chemistry

Zhenyu Li, Huan Ma, Jie Liu, Jinlong Yang
Precision Chemistry
Machine Learning in Materials Science
article

Theoretical Perspectives of Precision Chemistry

Zhenyu Li, Huan Ma, Jie Liu, Jinlong Yang
article en

Abstract

Precise prediction and control of chemical reactions and material properties─the central goal of precision chemistry─truly rely on accurate and efficient theoretical modeling of chemical systems. In recent years, significant progress has been made in theoretical and computational chemistry. Especially, interdisciplinary studies in the direction of the two emerging computational frontiers, artificial intelligence and quantum computation, are revolutionizing this field. Expressive neural networks can be used to represent many-electron wave functions with high accuracy, capturing strong correlations with a favorable computational cost compared to other methods. Leveraging quantum computation in quantum chemistry is also expected to deliver a quantum advantage in problems including electronic structure calculations. With artificial intelligence and quantum computation, we expect to establish a unified, high-precision, and scalable computational foundation for generating accurate quantum chemical data essential for precision chemistry.

Precision Chemistry
University of Science and Technology of China (CN)
Openalex Percentile: Top 46%
Machine Learning in Materials Science
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