Data for: Data-Driven Discovery of Synthetically Compatible Organic Semiconductors for Multifunctional Applications

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: PATRICK SORREL MVOTO KONGO, Steve Cabrel Teguia Kouam, Jean-Pierre Tchapet Njafa, Serge Guy Nana Engo
DOI: 10.5281/zenodo.18201813
Cited by: 0

Abstract

This dataset contains the complete computational results for the manuscript "Data-Driven Discovery of Synthetically Compatible Organic Semiconductors for Multifunctional Applications: A Computational Workflow". The dataset includes:- PCE calculations for 17,458 organic molecules from PubChemQC database- Top 7 candidate molecules with detailed optoelectronic and physicochemical properties- Molecular structure analysis results- PCE_SAScore sensitivity analysis results- Analysis scripts and Jupyter notebooks for full reproducibility All data is provided in CSV format for easy reuse. Code is provided under MIT License.

Fields of Study & Subjects

Machine Learning in Materials Science Organic Electronics and Photovoltaics Advanced Chemical Physics Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 January 2026
Document type
Dataset