大学化学 >> 2025, Vol. 40 >> Issue (9): 118-125.doi: 10.12461/PKU.DXHX202503062

所属专题： AI赋能化学教育

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人工智能在海洋特色物理化学综合实验中的应用探索

张岩, 周立敏, 曹晓燕, 包木太   

  1. 中国海洋大学化学化工学院, 山东 青岛 266100
  • 收稿日期:2024-03-18 录用日期:2025-06-03 发布日期:2025-09-16
  • 通讯作者: 包木太 E-mail:mtbao@mail.ouc.edu.cn
  • 基金资助:
    2023年教育部高等学校化学类专业教学指导委员会教学研究课题(H20230807)；中国海洋大学本科教育教学一般项目(2025JY010)

Exploring the Application of Artificial Intelligence in Marine-Themed Integrated Physical Chemistry Experiments

Yan Zhang, Limin Zhou, Xiaoyan Cao, Mutai Bao   

  1. College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, Shandong Province, China
  • Received:2024-03-18 Accepted:2025-06-03 Published:2025-09-16
  • Contact: Mutai Bao E-mail:mtbao@mail.ouc.edu.cn

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摘要： 本研究基于海洋特色物理化学实验教学，探索人工智能赋能实验教学的创新路径。介绍了知识图谱在系统化学习与跨学科知识方面的有效运用，并结合DeepSeek与Python开源大模型，提升了数据处理智能化水平，推动了实验教学智能化发展。

关键词: 物理化学实验, 人工智能, 海洋特色, 知识图谱, DeepSeek, Python

Abstract: This study investigates innovative approaches to AI-enhanced experimental teaching within the context of marine-themed integrated physical chemistry experiments. The research demonstrates the effective utilization of knowledge graphs for systematic learning and interdisciplinary knowledge integration. By incorporating DeepSeek and Python-based open-source models, the study significantly enhances intelligent data processing capabilities, thereby promoting the advancement of smart experimental teaching methodologies.

Key words: Physical chemistry experiments, Artificial intelligence, Marine-themed, Knowledge graph, DeepSeek, Python