大学化学

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基于Python模拟辅助的析氧催化剂的循环伏安测试——一个综合电化学实验设计

王子涵, 贾凯元, 刘宇涛, 马亮   

  1. 中国地质大学(武汉)材料与化学学院，湖北 武汉 430074
  • 收稿日期:2026-02-14 录用日期:2026-04-14
  • 通讯作者: 马亮 E-mail:liangma@cug.edu.cn Liang Ma
  • 基金资助:
    湖北省教学改革研究项目(2023144)；中国地质大学(武汉)教学改革研究项目(2025003, 2025187, 2024090)

Python-assisted simulation and integrated electrochemical experimental design of cyclic voltammetry for OER catalysts

Zihan Wang, Kaiyuan Jia, Yutao Liu, Liang Ma   

  1. Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, Hubei Province, China
  • Received:2026-02-14 Accepted:2026-04-14
  • Contact: Liang Ma E-mail:liangma@cug.edu.cn

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摘要： 针对传统循环伏安教学多以铁氰化钾/亚铁氰化钾可逆体系为范例，学生“会操作但难理解”的问题，设计了一套综合电化学实验，以帮助学生理解循环伏安测试的基本原理及方法。以电沉积法制备Co(OH)2/Ni(OH)2电催化剂，在碱性介质中开展循环伏安测试，结合自设计Python有限差分迭代模拟软件，开放调节扫速与电荷转移常数等参数深入探讨反应微观动力学特征。结果获得稳定氧化还原特征与析氧区响应，模拟可再现曲线规律并支撑机制探索。创新点在于将电极制备、循环伏安测试与数值模拟有机融合，形成分层递进的教学路径，具有良好可操作性与推广应用价值。

关键词: 综合实验设计, 循环伏安法, 析氧电催化剂, Python模拟, 电化学

Abstract: To address the limitation of traditional cyclic voltammetry (CV) instruction that primarily employs the reversible K3[Fe(CN)6]/K4[Fe(CN)6] redox system, where students often perform experiments without achieving deep conceptual understanding, we designed a comprehensive electrochemical experiment to enhance students’ comprehension of CV fundamentals and methodologies. The study involved preparing a Co(OH)2/Ni(OH)2 electrocatalyst via electrodeposition and conducting CV tests in alkaline media. By integrating a self-developed Python-based finite difference iterative simulation program that allows adjustable parameters (including scan rate and charge-transfer constants), we enabled detailed exploration of microscopic reaction kinetics. Experimental results demonstrated stable redox characteristics and oxygen evolution region responses, while simulations successfully reproduced voltammogram trends, thereby supporting mechanistic investigations. The innovation of this work lies in its seamless integration of electrode fabrication, CV measurements, and numerical simulation, creating a hierarchical and progressive instructional approach with strong practicality and broad application potential.

Key words: Comprehensive experimental design, Cyclic voltammetry, Oxygen evolution electrocatalyst, Python simulation, Electrochemistry