Kinetic modeling of reaction systems is essential for model-based scale-up, optimization, and control of chemical reactors. The process begins with generating high-quality experimental data from well-designed experiments across varying reaction conditions. Experts then propose stoichiometries and kinetic models based on prior knowledge of the system. Conventionally, a simultaneous identification approach is used to test all combinations of stoichiometries and kinetic models to determine the best model and parameter estimates. While statistically optimal, this approach is computationally expensive and often suffers from nonconvergence issues. Incremental identification offers an alternative by decomposing the task into subtasks: identifying stoichiometry, rate laws, and parameters separately. Although this method yields biased parameter estimates, it significantly reduces complexity and runtime, and the results can be refined using simultaneous identification. In this work, we present PyKineMod, a Python-based software tool for rapid kinetic identification of reaction systems using incremental identification. PyKineMod includes five major modules: (i) preprocess, (ii) datatools, (iii) ratelawgenerator, (iv) simulate, and (v) incremental. The preprocess module denoises concentration data, while datatools manage experimental inputs such as stoichiometry, molecular weights, and reactor types (batch, semi-batch, CSTR). The ratelawgenerator module automatically generates candidate rate expressions using stoichiometric information. The simulate module allows for system simulation under user-defined conditions. The incremental module identifies kinetic models using the generated rate laws and filtered data and implements both extent-based and rate-based identification approaches. Final parameter estimates are refined via a simultaneous approach. Overall, PyKineMod enables automated and efficient kinetic model development for homogeneous reaction systems. Future releases will support heterogeneous systems, expanding their utility for complex reaction engineering problems.
