Kinetic phenomena are ubiquitous in science and engineering research. A nice introduction to chemical kinetics is presented in this wikipedia page. Modelling kinetic systems involves solving set of coupled ordinary differential equation either analytically, for small systems, or numerically, for large systems. Scientific experiments under controlled environment are able to isolate various kinetic pathways and thus can be modeled analytically. However, most systems in reality, such as chemical reactions in the atmosphere, are relatively large and numerical integration need to be performed.
We have created a Python based program, NumKinFit, which can perform numerical integrations for kinetic systems and also fit the model parameters to experimental measurements. The program along with a manual with few examples are available in a GitHub repository linked here.
NumKinFit is free to use and distribute for non profit use. The GUI can be run in Windows OS without any Python installation. This program can be used for analyzing kinetic measurements in research laboratories and also as a tool to introduce kinetic modelling to undergraduate students.