大学化学 >> 2025, Vol. 40 >> Issue (10): 233-242.doi: 10.12461/PKU.DXHX202412024

所属专题： 教育数字化推动高等化学教育改革

化学实验 上一篇    下一篇

基于Python语言的循环伏安法(CV)可视化仿真实验

杨鹰, 武泳含, 李紫瑄, 张露, 林荣沁, 张叶梵, 刘季铨, 宁晓辉, 李延, 崔斌   

  1. 西北大学化学与材料科学学院, 化学国家级实验教学示范中心, 西安 710127
  • 收稿日期:2024-12-02 录用日期:2025-01-23 发布日期:2025-09-17
  • 通讯作者: 杨鹰 E-mail:yingyang@nwu.edu.cn
  • 基金资助:
    西北大学 2024 年度本科人才培养建设项目(JX2024003, JX2024105);教育部高等学校化学类专业教学指导委员会教学研究与实践项目(H20210602, H20210603)

Visualization Simulation Experiment of Cyclic Voltammetry (CV) Based on Python

Ying Yang, Yonghan Wu, Zixuan Li, Lu Zhang, Rongqin Lin, Yefan Zhang, Jiquan Liu, Xiaohui Ning, Yan Li, Bin Cui   

  1. National Demonstration Center for Experimental Chemistry Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710127, China
  • Received:2024-12-02 Accepted:2025-01-23 Published:2025-09-17
  • Contact: Ying Yang E-mail:yingyang@nwu.edu.cn

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摘要： 循环伏安法(CV)是利用电化学方法研究氧化还原反应的关键表征手段之一。传统的循环伏安法教学实验中往往未能深入探讨CV曲线反映的物理化学过程，导致学生对CV表征过程中电化学动力学行为的理解停留在表面。为了弥补这一缺陷，本实验利用Python语言编写了CV数字化仿真程序，对CV曲线和电极表面的电活性物质浓度变化过程进行了可视化仿真。这一数字化设计不仅减少了实验材料的消耗，提高了实验效率，而且通过动态可视化的形式，使枯燥的电化学数据转化为直观易懂的图像。本数字化仿真实验对传统实验进行了有益的补充和提升，提高了教学的互动性和学生的参与度，激发了学生对电化学知识的学习兴趣和探索欲望。

关键词: 电化学, 仿真, 循环伏安法, 可视化, Python, 动力学

Abstract: Cyclic voltammetry (CV) stands as a pivotal electrochemical technique for investigating redox reactions. Traditional CV teaching experiments often lack in-depth exploration of the physicochemical processes underlying CV curves, leading to students' limited comprehension of electrochemical kinetics during CV characterization. To address this pedagogical gap, we developed a digital simulation program using Python to visualize both CV curves and the dynamic concentration changes of electroactive species at the electrode surface. This computational approach not only minimizes material consumption and enhances experimental efficiency but also transforms complex electrochemical data into accessible visual representations through dynamic visualization. The digital simulation experiment serves as a valuable complement to traditional methods, enhancing instructional interactivity and student engagement while fostering greater interest and curiosity in electrochemical studies.

Key words: Electrochemistry, Simulation, Cyclic voltammetry, Visualization, Python, Kinetics