BenchmarkSet1500: High-Accuracy Excited-State Reference Benchmark Dataset for Organic Semiconductors
BenchmarkSet1500 is an open-access multireference excited-state database established to provide the first dedicated high-accuracy benchmark set for organic semiconductor research. The repository comprises 1,500 small organic molecules with consistently computed vertical excited-state properties obtained using state-averaged complete active space self-consistent field (SA-CASSCF) and strongly contracted N-electron valence state second-order perturbation theory (SC-NEVPT2), alongside the full reproducible workflow code used to generate the dataset. The dataset focuses on systems where single-reference approaches (e.g. TD-DFT) are known to fail, including molecules exhibiting strong static correlation and inverted singlet-triplet gaps. BenchmarkSet1500 is designed to support rigorous method benchmarking, systematic assessment of theory-level performance, development of predictive models, and screening for technologically relevant organic semiconductors.
This resource is part of the High-Accuracy Excited-State Reference Benchmark Dataset for Organic Semiconductors & OPTIMADE Providers' Datasets resource themes.
How to Access
- BenchmarkSet1500 Community Data Collection
This distribution of the dataset is in the form of a data collection with one entry per molecule which contains curated metadata, optimised geometries (at B3LYP/6-31g* level of theory), complete electronic-structure output files, and computed excited-state energies and oscillator strengths for low-lying singlet and triplet states.
- BenchmarkSet1500 aggregated AI Ready Dataset
A consolidated machine-learning-ready CSV file which aggregates all molecules with their structural descriptors and excited-state properties to enable immediate integration into data-driven workflows
- OPTIMADE API for BenchmarkSet1500 via PSDI Index Search
Use this base_url when constructing OPTIMADE API queries for BenchmarkSet1500.
Further Information
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Citation
Publication to be cited by Tahereh Nematiaram and Malin Zollner in review (details will shortly be updated here).

