Python在分析化学实验数据处理中的应用——以铁和铋的络合滴定实验为例

Application of Python in Analytical Chemistry Experiment Data Processing: Complexation Titration of Iron and Bismuth

分析化学实验是化学和化工专业的核心基础课之一,其中数据分析处理是分析化学实验课程的重难点。基于此,以铁、铋的络合滴定实验数据处理为例,讨论了如何运用Python处理分析化学实验数据。将编程好的Python程序直接用于实验数据处理,能够快速、准确、高效地得到物质含量及相对平均偏差等数值,并仅需通过对关键代码的修改就能将程序扩展到其他实验应用中。Python程序应用于分析化学数据处理中能为实验的高效进行提供切实的保障,并具有较好的普适性和推广性,同时能够激发学生的探究兴趣和培养学生的创新能力。

Analytical chemistry experiment is one of the core basic courses of chemistry & chemical engineering majors. Data analysis and processing have always been the most important and difficult points of the course. Herein, taking the “complexation titration of iron and bismuth” as an example, a new Python based data analyzing and processing method for analytical chemistry experiment is discussed. Using Python processing, the experimental data including substance content and relative mean deviation can be obtained more quickly, accurately and efficiently. In addition, the program can be easily extended to other experimental applications by just modifying the key code. This work provided a practical guarantee for the efficient conduct of the experiment. Furthermore, it is significant in cultivating the independent innovation and inspiring the research interest of students.