Identification of descriptors for thiophene desulfurization and heavy metal immobilization over K-modified calcium-based materials

Inhibiting the emission of sulfurous species and heavy metals is essential for the clean utilization of carbon-containing resources in the co-pyrolysis of sludge and low-rank coal. Although calcium-based materials show promise for pollutant control, existing materials suffer from limited multifunctionality and low utilization efficiency. Herein, a theoretical investigation based on density functional theory (DFT) calculations was conducted to elucidate thiophene desulfurization mechanisms and heavy metal adsorption energies on CaCO 3 and K 2 Ca(CO 3 ) 2 , while ab initio molecular dynamics (AIMD) simulations were performed to evaluate the structural stability of the optimized catalyst. The KCa-terminal of K 2 Ca(CO 3 ) 2 exhibits optimal bifunctional performance. Density of states analysis reveals that K incorporation enhances the electronic activity of p orbitals, and there exists a positive correlation between the p -band center to the Fermi level and both desulfurization and immobilization performance. Microscopic dynamic analysis identifies 873−923 K as the optimal desulfurization temperature. Furthermore, machine learning-based feature correlation analysis identifies eight key descriptors governing heavy metal adsorption energy, which are integrated into a unified expression to quantitatively elucidate the contributions of geometric structure and electronic properties. This work establishes a theoretical insight into the rational design of efficient bifunctional materials.