Optimizing the Selection of Phase Change Materials for Thermal Energy Storage Using Simple Data Analysis

This research introduces a streamlined, data-driven methodology for selecting Phase Change Materials (PCMs) in thermal energy storage (TES) systems, optimized for low-temperature (20–60°C) and high-temperature (100–300°C) applications. Employing a weighted scoring model, the framework evaluates ten PCMs—organic, inorganic, and eutectic—based on melting temperature, latent heat, thermal conductivity, density, and cost, derived from 30 peer-reviewed sources and validated through thermal cycling experiments. Results, presented via tables, bar charts, scatter plots, and statistical analysis (ANOVA, p < 0.05), identify sodium sulfate decahydrate and sodium nitrate as optimal for low- and high-temperature TES, respectively. Sensitivity analysis ensures ranking robustness, while cost data, sourced from 2023–2025 market reports, enhance economic feasibility. By prioritizing simplicity over complex AI-based or multi-objective optimization methods, this framework empowers engineers and researchers to design energy-efficient TES systems, reducing carbon emissions and enhancing energy access in buildings and renewable energy systems.