大学化学 >> 2026, Vol. 41 >> Issue (1): 169-178.doi: 10.12461/PKU.DXHX202504098

所属专题： 化学实验数字化设计竞赛获奖作品

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基于智能融合大数据和深度学习算法的化学分析平台在本科实验教学中的设计与应用

李亦菲1, 陈雪鑫1, 刘思含1, 陈士乙2, 潘玲1   

  1. 1 东北师范大学化学学院, 长春 130024;
    2 东北师范大学信息科学与技术学院, 长春 130024
  • 收稿日期:2025-04-28 录用日期:2025-10-13 发布日期:2025-12-30
  • 通讯作者: 李亦菲 E-mail:liyf640@nenu.edu.cn Yifei Li
  • 基金资助:
    吉林省高等教育教学改革研究课题(2024L5L54AS001R)；东北师范大学本科教学综合改革“揭榜领题”项目资助(BKZG20230508)；东北师范大学研究生教学综合改革项目(131007655)

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

Yifei Li1, Xuexin Chen1, Sihan Liu1, Shiyi Chen2, Ling Pan1   

  1. 1 Faculty of Chemistry, Northeast Normal University, Changchun 130024, China;
    2 Faculty of Information Science and Technology, Northeast Normal University, Changchun 130024, China
  • Received:2025-04-28 Accepted:2025-10-13 Published:2025-12-30
  • Contact: Yifei Li E-mail:liyf640@nenu.edu.cn

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摘要： 为了强化实验操作技能训练，促进学生对于有机合成化学的深层次理解，我们提出了一种基于智能融合大数据和深度学习算法的化学分析平台。该平台通过引导学生自主探索数字化实验设计过程，使其在实验实践中直观感受多学科交叉融合的科研魅力。我们利用基础设施成熟完备的数字化平台，选取硝苯地平的合成反应作为教学案例，具体介绍数字化实验设计的流程及其在本科实验教学中的应用。本实验包含了有机化学和计算机科学领域的相关知识，涉及到合成化学与药物化学的相关学习内容，适用于模块化实验教学以满足不同教学需求，并期望以此提高学生的创新意识与综合能力。

关键词: 有机合成, 数字化赋能, 学科交叉, 创新实验

Abstract: 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.

Key words: Organic synthesis, Digital empowerment, Interdisciplinary, Innovation experiment