This article discusses a study focusing on developing a mathematical model for creating and modifying the structure of chocolates. In the experimental study at the University of Birmingham's Centre for Formulation Engineering, researchers cooled and heated chocolate through rapid programmed temperature changes and then studied what happened using differential scanning calorimetry. The data was fitted to six kinetic processes. To make the modeling easier, the system of six polymorphs and liquid chocolate was simplified to model only three materials: stable solids, unstable solids, and melt. Then equations were developed to describe the nucleation of crystals, growth of stable and unstable phases, and the melting of the stable and unstable solids. The model developed simplifies the number of crystal forms, but this simplification makes it possible to model differential scanning calorimetry data. Once fitted to differential scanning calorimetry data over a range of cooling rates, the model can then be used both to predict behavior and to explain what is happening in the process. The model can be used to show how ‘frozen cone’ methods work.
Hopfield Neural Network-Based Algorithm Applied to Differential Scanning Calorimetry Data for Kinetic Studies in Polymorphic Conversion
