QTNano - Combining DFT Calculations and Clustering Techniques to Screen Organic Monovalent Cations for Applications in Halide Perovskite Solar Cells - ACS Omega, 2026

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Original abstract

This repository contains the primary dataset supporting the paper "Combining DFT Calculations and Clustering Techniques to Screen Organic Monovalent Cations for Applications in Halide Perovskite Solar Cells". Specifically, the dataset comprises 134 distinct organic molecules, a pristine 0D lead-iodine-cesium perovskite model, and the corresponding passivated systems featuring each organic molecule interacting with the perovskite. All structural and electronic properties were obtained via Density Functional Theory (DFT) calculations using the FHI-aims code, with post-processing and data analysis performed in Python. Repository Contents: 1) README: Instructions for navigating the directory structure and understanding the molecule identification (ID) system. 2) structure_ID_name_SMILES.csv: A mapping table that correlates each molecule's unique identification number (ID) with its chemical name and SMILES representation. 3) pbe_lt2_fhi-aims/: Geometry optimization data. Calculations were performed using the PBE exchange-correlation functional. The "lt2" suffix refers to the "light tier 2" basis set precision level. 4) hse06_lt2_fhi-aims/: Single-point energy calculation outputs, computed using the HSE06 hybrid functional. 5) hirshfeld_pbe_lt2_fhi-aims/: Hirshfeld population analysis (atomic charges) derived from the PBE/lt2 calculations.

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