A novel algorithm to identify the full kinetic model of solid state reactions according to the General Kinetic Equation is presented. It is a higher-order generalization of the Non-Parametric Kinetics method (NPK-method) and allows for the simultaneous identification of the conversion, temperature and pressure dependency from any combination of measurements. As a model-free identification method, it does not rely on a-priori assumptions about the kinetic model. The result vectors can be used to identify the kinetic parameters by means of model fitting for each variable independently.

The steps of the algorithm are described and its effectiveness is demonstrated by applying it to simulated datasets. The kinetic parameters could be recovered very accurately from the test data, also in the presence of noise.

Overall the higher order NPK-method is a very promising approach to derive kinetic models from experimental data with a minimum of a-priori assumptions about the reaction.