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Citation: Yifei Li, Xuexin Chen, Sihan Liu, Shiyi Chen, Ling Pan. Design and Application of Chemical Analysis Platform Based on Intelligent Integration of Big Data and Deep Learning Algorithm in Undergraduate Experimental Teaching[J]. University Chemistry, ;2026, 41(1): 169-178. doi: 10.12461/PKU.DXHX202504098 shu

Design and Application of Chemical Analysis Platform Based on Intelligent Integration of Big Data and Deep Learning Algorithm in Undergraduate Experimental Teaching

Yifei Li ^1,, ,
Xuexin Chen ¹ ,
Sihan Liu ¹ ,
Shiyi Chen ² ,
Ling Pan ¹

1.
Faculty of Chemistry, Northeast Normal University, Changchun 130024, China;
2.
Faculty of Information Science and Technology, Northeast Normal University, Changchun 130024, China

Corresponding author: Yifei Li, liyf640@nenu.edu.cn
Received Date: 28 April 2025
Revised Date: 13 October 2025

To enhance students’ experimental operational skills and facilitate their profound comprehension of organic synthetic chemistry, we developed a chemical analysis platform incorporating intelligent big data fusion and deep learning algorithms. This platform guides students through autonomous exploration of digital experimental design processes, allowing them to directly experience the interdisciplinary research appeal during practical implementation. Utilizing a well-established digital platform infrastructure, we employed the synthesis of nifedipine as a teaching case to demonstrate the workflow of digital experimental design and its pedagogical applications in undergraduate laboratory courses. This experiment integrates knowledge from both organic chemistry and computer science disciplines, encompassing learning components related to synthetic chemistry and medicinal chemistry. Suitable for modular experimental teaching to accommodate diverse instructional requirements, this approach aims to cultivate students’ innovative thinking and comprehensive competencies.
- Organic synthesis,
- Digital empowerment,
- Interdisciplinary,
- Innovation experiment
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