Citation: Sihan Wang, Chenxi Yu, Shuzhang Ran, Jiawei Chen, Shoutong Rao, Xinyi Liang, Ruiqi Dong, Guixiang Zeng, Guoqiang Wang, Jing Ma. 铁配合物合成与性质探究的数智化改进——大学化学实验中“磺基水杨酸合铁配合物的组成与稳定常数的测定”的创新设计[J]. University Chemistry, ;2026, 41(5): 36-49. doi: 10.12461/PKU.DXHX202511137 shu

铁配合物合成与性质探究的数智化改进——大学化学实验中“磺基水杨酸合铁配合物的组成与稳定常数的测定”的创新设计

Sihan Wang ¹ ,
Chenxi Yu ¹ ,
Shuzhang Ran ¹ ,
Jiawei Chen ¹ ,
Shoutong Rao ¹ ,
Xinyi Liang ¹ ,
Ruiqi Dong ² ,
Guixiang Zeng ^2,, ,
Guoqiang Wang ^1,, ,
Jing Ma ^1,,

1.
School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, Jiangsu Province, China;
2.
Kuang Yaming Honors School, Nanjing University, Nanjing 210023, Jiangsu Province, China

Corresponding author: Guixiang Zeng, Guoqiang Wang, Jing Ma,
Received Date: 20 November 2025
Revised Date: 25 February 2026

本项目针对“基础化学实验”中磺基水杨酸合铁配合物测定实验存在的技术瓶颈，如本底吸光干扰、无法确认未知配位体系的配位比n以及实验效率低(单次实验只测1种配体)，开展了系统性改进。在实验方法上，通过建立包含所有组分吸光度的方程组进行求解，有效消除了本底吸光的干扰效应，使单次实验可测配体种类由1种提升至11种。在分析技术方面，引入机器学习算法构建配合物稳定常数预测模型，协助探明实验体系中的配位比n，结合紫外-可见光谱实测数据进行验证分析，通过特征重要性分析揭示配位作用的关键影响因素，为配位场理论的教学提供实证依据。在教学方法方面，构建智能实验教学平台，有效降低师生数智化技术门槛，促进改进实验方法的推广应用。改进后的实验在保持分析精度的同时，显著提高了通量性和普适性，通过探究式教学模式有效培养了学生的数据解析能力和复杂化学问题的解决能力。
- Digitalization and intelligence,
- Chemical experiment,
- Improvement and innovation,
- Iron complex
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