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Applied Sciences
Volume 15
Issue 13
10.3390/app15137387
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Review

The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis

by
Tan Li
1,2,*,
Weining Song
2,
Nanjiang Chen
1,2,
Qi Wang
2,
Fangfang Gao
1,
Yalan Xing
3,
Shouluan Wu
2,
Chao Song
2,
Junjin Li
1,
Yu Liu
1,
Shenghua Li
1,
Congying Wu
1 and
Zhenyu Zhang
1
1
School of Information Engineering,Nanchang University, Nanchang 330047, China
2
QuikTech Co., Ltd., Beijing 100088, China
3
School of Materials Science and Engineering,Beihang University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(13), 7387; https://doi.org/10.3390/app15137387 (registering DOI)
Submission received: 14 May 2025 / Revised: 24 June 2025 / Accepted: 27 June 2025 / Published: 30 June 2025
(This article belongs to the Special Issue Advances in Organic Synthetic Chemistry)
Versions Notes

Abstract

The deep integration and application of artificial intelligence to organic chemistry are propelling the development of organic chemistry synthesis laboratories toward an intelligent automated laboratory model characterized by “hardware + software + AI”. This paper systematically explores the overall framework of AI-driven intelligent laboratories for organic chemistry synthesis, achieving automation and flexibility through standardized experimental integration workstations and intelligent scheduling and collaborative management of experimental resources. By leveraging multimodal databases, the integration of large models, machine learning, and other AI technologies enables AI-driven closed-loop intelligent chemical experiments, including product prediction, molecular retrosynthetic planning, and synthesis reaction optimization. The paper proposes a cloud-based shared operational model for chemical laboratories, aiming to achieve socialized sharing and intelligent matching of experimental resources, thereby facilitating the accumulation and sharing of chemical experimental data to promote the intelligent development of organic chemistry synthesis experiments. Practical cases of building intelligent chemical laboratories are shared, providing paths for technology implementation in constructing the next generation of automated and intelligent chemical laboratories.
Keywords: organic chemistry synthesis; computational chemistry; laboratory automation; AI-driven intelligent chemical experiment; cloud-based shared laboratory organic chemistry synthesis; computational chemistry; laboratory automation; AI-driven intelligent chemical experiment; cloud-based shared laboratory

Share and Cite

MDPI and ACS Style

Li, T.; Song, W.; Chen, N.; Wang, Q.; Gao, F.; Xing, Y.; Wu, S.; Song, C.; Li, J.; Liu, Y.; et al. The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis. Appl. Sci. 2025, 15, 7387. https://doi.org/10.3390/app15137387

AMA Style

Li T, Song W, Chen N, Wang Q, Gao F, Xing Y, Wu S, Song C, Li J, Liu Y, et al. The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis. Applied Sciences. 2025; 15(13):7387. https://doi.org/10.3390/app15137387

Chicago/Turabian Style

Li, Tan, Weining Song, Nanjiang Chen, Qi Wang, Fangfang Gao, Yalan Xing, Shouluan Wu, Chao Song, Junjin Li, Yu Liu, and et al. 2025. "The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis" Applied Sciences 15, no. 13: 7387. https://doi.org/10.3390/app15137387

APA Style

Li, T., Song, W., Chen, N., Wang, Q., Gao, F., Xing, Y., Wu, S., Song, C., Li, J., Liu, Y., Li, S., Wu, C., & Zhang, Z. (2025). The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis. Applied Sciences, 15(13), 7387. https://doi.org/10.3390/app15137387

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