机器学习及大数据视域下分析化学实验数字化探索—

引用本文: 饶靖杰, 蔡雯雯, 赵佳辉, 杨旭, 颜紫嫣, 张天锦, 张航. 机器学习及大数据视域下分析化学实验数字化探索——以测量水体硬度为例[J]. 大学化学, 2026, 41(1): 276-288. doi: 10.12461/PKU.DXHX202504104 shu

Citation: Jingjie Rao, Wenwen Cai, Jiahui Zhao, Xu Yang, Ziyan Yan, Tianjin Zhang, Hang Zhang. Digital Exploration of Analytical Chemistry Experiments in the Context of Machine Learning and Big Data: A Case Study on Water Hardness Measurement[J]. University Chemistry, 2026, 41(1): 276-288. doi: 10.12461/PKU.DXHX202504104 shu

机器学习及大数据视域下分析化学实验数字化探索——以测量水体硬度为例

饶靖杰 ^1, ,
蔡雯雯 ^1, ,
赵佳辉 ^1, ,
杨旭 ^2, ,
颜紫嫣 ^3, ,
张天锦 ^1, ,
张航 ^{1,
,}

1.
江西师范大学化学与材料学院, 化学国家级实验教学示范中心(江西师范大学), 南昌 330022;
2.
江西师范大学计算机信息工程学院, 南昌 330022;
3.
江西师范大学软件学院, 南昌 330022

通讯作者: 张航，E-mail:zhanghangjx@163.com

基金项目:
江西省高等学校教学改革研究课题(JXJG-24-2-26)

摘要: 本文在数智教育背景下，以水体硬度测定为例，融合机器学习与大数据技术，构建分析化学实验数字化教学辅助系统。通过采集滴定图像，结合颜色直方图与SVM模型判定滴定进程，实现结果自动分析与评价及个性化学习反馈。该研究将传统实验与数字技术相结合，培养学生数据分析、跨学科思维与实践能力，为高校化学实验教学数字化提供了新方法。

关键词:

English

Digital Exploration of Analytical Chemistry Experiments in the Context of Machine Learning and Big Data: A Case Study on Water Hardness Measurement

1.
National Demonstration Center for Experimental Chemistry Education, College of Chemistry and Materials, Jiangxi Normal University, Nanchang 330022, China;
2.
School of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, China;
3.
School of Software, Jiangxi Normal University, Nanchang 330022, China

Corresponding author: Hang Zhang, zhanghangjx@163.com

Received Date: 28 April 2025
Revised Date: 30 September 2025
Available Online: 31 October 2025

Abstract: Within the framework of digital-intelligent education, this study develops a digital teaching assistance system for analytical chemistry experiments by integrating machine learning and big data technologies, using water hardness determination as a representative example. The system captures titration images and employs color histograms combined with a support vector machine (SVM) model to determine titration endpoints, enabling automated result analysis, evaluation, and personalized learning feedback. This research successfully bridges traditional experimental methods with digital technologies, fostering students’ competencies in data analysis, interdisciplinary thinking, and practical skills. The proposed approach offers an innovative methodology for promoting digital transformation in university-level analytical chemistry laboratory education.

Key words:

Digital teaching
/ University-level chemistry experiments
/ Machine learning
/ Digital and intelligent

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

机器学习及大数据视域下分析化学实验数字化探索——以测量水体硬度为例

通讯作者: 张航，E-mail:zhanghangjx@163.com

English

Digital Exploration of Analytical Chemistry Experiments in the Context of Machine Learning and Big Data: A Case Study on Water Hardness Measurement

Corresponding author: Hang Zhang, zhanghangjx@163.com

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通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

机器学习及大数据视域下分析化学实验数字化探索——以测量水体硬度为例

通讯作者: 张航，E-mail:zhanghangjx@163.com

English

Digital Exploration of Analytical Chemistry Experiments in the Context of Machine Learning and Big Data: A Case Study on Water Hardness Measurement

Corresponding author: Hang Zhang, zhanghangjx@163.com

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南： 你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

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通讯作者: 陈斌, bchen63@163.com

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