引用本文:
赵泽华, 安孝彦, 徐金荣, 杨玲, 赵浩, 吴忠云. 量热实验数据采集处理软件的自主开发与应用[J]. 大学化学,
2025, 40(11): 402-408.
doi:
10.12461/PKU.DXHX202505045
Citation: Zehua Zhao, Xiaoyan An, Jinrong Xu, Ling Yang, Hao Zhao, Zhongyun Wu. Independent Development and Application of Calorimetric Experiment Data Acquisition and Processing Software[J]. University Chemistry, 2025, 40(11): 402-408. doi: 10.12461/PKU.DXHX202505045
Citation: Zehua Zhao, Xiaoyan An, Jinrong Xu, Ling Yang, Hao Zhao, Zhongyun Wu. Independent Development and Application of Calorimetric Experiment Data Acquisition and Processing Software[J]. University Chemistry, 2025, 40(11): 402-408. doi: 10.12461/PKU.DXHX202505045
量热实验数据采集处理软件的自主开发与应用
摘要:
量热实验是物理化学实验课程中验证能量守恒定律和测定焓变的经典热力学实验。然而，传统手动操作存在数据采集效率低、处理繁琐等问题。为此，基于Python自主开发了具有图形界面的量热实验软件。集成数据采集、智能处理与可视化功能，实现了溶解热与燃烧热实验的数字化改造。软件通过串口通信模块实时获取温差数据，利用科学计算库自动完成雷诺校正与热力学计算，并结合交互式界面直观呈现实验数据。实践表明，该软件可缩短实验操作时长约30%，释放的课时资源为实验教学创造了更多探究空间。其教学应用有效推动了实验教学从操作训练向热力学原理深度理解的转型，并构建了“基础-进阶-创新”三级培养体系，为高校实验教学数字化转型提供了可复制的技术路径。
English
Independent Development and Application of Calorimetric Experiment Data Acquisition and Processing Software
Abstract:
Calorimetry experiments are classic thermodynamic investigations in physical chemistry laboratory courses, serving to verify the law of energy conservation and determine enthalpy changes. However, conventional manual operations are characterized by inefficient data acquisition and laborious processing procedures. To address these limitations, we developed a Python-based software featuring a graphical user interface (GUI) specifically designed for calorimetric experiments in undergraduate chemistry education. This software integrates comprehensive functionalities including real-time data acquisition, intelligent processing, and visualization capabilities, facilitating the digital transformation of both dissolution and combustion calorimetry experiments. The software acquires real-time temperature difference data via serial communication modules, executes Reynolds correction and thermodynamic calculations using scientific computing libraries, and displays experimental data in real-time through an interactive interface. Implementation results demonstrate that the software reduces experimental operation time by approximately 30% and frees up instructional time, creating more opportunities for in-depth exploration of thermodynamic principles. This innovation effectively shifts the instructional focus from basic operational training to deep understanding of thermodynamic principles, and establishes a “Foundation-Engagement-Innovation” three-tier training system, providing a replicable technical path for the digital transformation of experimental teaching in higher education institutions.
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