Large-Scale Dataset of Porous Carbon Materials for Supercapacitors Extracted via Large Language Models

The database covers over 5,000 distinct carbon samples and includes more than 10,000 specific capacitance data points under varying testing conditions. It offers a holistic view of the material properties, integrating synthesis parameters (preparation crafts), microstructural characteristics (pore size distribution, surface area), and surface elemental composition.

Furthermore, it details key electrochemical performance metrics, including Specific Capacitance, Energy Density, Power Density, and Equivalent Series Resistance (ESR). This dataset serves as a valuable resource for data-driven materials science, enabling quantitative analysis of structure-performance correlations and the inverse design of high-performance energy storage materials.