2026-10-14T11:24:39Z https://www.scidb.cn/oai

10.57760/sciencedb.j00213.00161 2025-07-22T20:36:46Z

2025-07-22 Supporting Information for Interpretable Machine Learning Modeling of Bulk Modulus in Cubic Perovskites and Its Application to Soft-Lattice Screening doi:10.57760/sciencedb.j00213.00161 en The supporting information includes four supplementary tables: Table S1 summarizes 22 elemental features generated by the Magpie tool, including English names, symbols, and Chinese names; Table S2 provides the elemental feature values of 213 perovskite samples used in the SISSO model, the bulk moduli predicted based on the thermal-structural coupling descriptors, and the corresponding DFT calculated values; Table S3 corresponds to the VS-SISSO model, listing the elemental feature values, DFT moduli, and the bulk moduli predicted using the electron-thermal-structural triple coupling descriptors for the same set of perovskite samples; Table S4 compiles 169 lead-free perovskite candidate materials with bulk moduli similar to those of Pb-I perovskites and their predicted values, which were screened out through this descriptor. Bulk modulus; Soft lattice; SISSO; VS-SISSO; Perovskite; Interpretable machine learning jiang jin ming Sun Qingde Zhang Weibing PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.7498/aps.74.20250652 Science Data Bank