Utilizing python for potentiometric redox titrations: A study on ferrous ion detection with potassium permanganate

Instrumental chemical analysis offers a powerful approach for qualitative and quantitative methods estimating various parameters. An open-source programming language is used to automate potentiometric redox titrations. Modern methods are preferred over conventional methods as they are useful in identifying linear dynamical systems and they also have low computational complexity leading to accurate results. Potentiometric redox titrations are powerful analytical chemistry tools for quantifying the concentration of analytes based on their redox properties, and they find widespread use in various industries, including environmental monitoring, pharmaceuticals, and chemical process control. The aim of this work is to integrate instrumental chemical analysis with artificial intelligence. Artificial Intelligence in potentiometric titrations can further encourage innovations in the field of industry. The purpose of this study is to develop and implement a Python-based approach for automating potentiometric redox titrations, specifically focusing on ferrous ion detection using potassium permanganate as the titrant. By integrating Python with instrumental chemical analysis, the study aims to enhance the precision, efficiency, and accessibility of potentiometric titrations in analytical chemistry. Python is used effectively to simulate and analyse such titrations. NumPy for numerical operations, Matplotlib is used in plotting; the results were comparable with regular instrumental analysis and obtained satisfactory report.