Characterizing Na2S kinetics for thermochemical energy storage applications through algorithmic optimization

In this study, the application of the Shuffled Complex Evolution (SCE) method for algorithmic optimization has demonstrated its effectiveness in calibrating the reaction model for sodium sulfide (Na2S) for use in thermochemical energy storage (TCES) systems. The research revealed that both twostep and three-step reaction models for Na2S align well with experimental data. This method significantly streamlines the data requirements, as it relies primarily on time-series data of conversion, temperature, and pressure, which are readily accessible from Thermogravimetric (TG) measurements. However, despite these advancements, thorough validation of these models is essential, especially under diverse operating conditions beyond the initial test environments. This study highlights the potential of advanced algorithmic techniques for material characterization for TCES applications.