Intelligent understanding of spectra: from structural elucidation to property design

Shuo Feng; Meng Huang; Y.P. Li; Aoran Cai; Xiaoyu Yue; Song Wang; Linjiang Chen; Jun Jiang; Yi Luo

doi:10.1039/d4cs01293c

January 1, 2025Chemical Society Reviews

Intelligent understanding of spectra: from structural elucidation to property design

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Key Points

AI-driven methods provide a foundation for connecting spectral fingerprints to material structures, enhancing design capabilities.
The study highlights spectrum–structure–property relationships, delivering insights relevant for material innovation.
Analysis involved examining how spectra can guide the design of functional substances, potentially revolutionizing material science.
Significance lies in enabling a more interpretable approach to material design, bridging the gap between structure and properties.

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Abstract

AI-driven methods link spectral fingerprints to structures and properties, providing a foundation for the unified inverse design of functional substances and delivering interpretable insights into universal spectrum–structure–property relationships.

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Cite This Study

Feng et al. (2025) studied this question.

synapsesocial.com/papers/68af4ec0ad7bf08b1ead7d21 https://doi.org/10.1039/d4cs01293c

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Intelligent understanding of spectra: from structural elucidation to property design

Key Points

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Abstract

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Cite This Study

Intelligent understanding of spectra: from structural elucidation to property design

Key Points

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Abstract

Discussion

Cite This Study

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