White-box methodologies for achieving robust correlations in hydrogen storage with metal-organic frameworks.

Hydrogen is recognized as a clean energy replacement for non-renewable fossil fuels, and the utilization of metal-organic frameworks (MOFs) for hydrogen storage has gained considerable interest in recent years. In this study, hydrogen storage in MOFs was estimated using white-box methods, namely group method of data handling (GMDH), genetic programming (GP), and gene expression programming (GEP), which are robust soft-computing methods known for generating innovative correlations. To this end, temperature, pressure, pore volume, and surface area were implemented as input parameters for constructing these robust correlations.