Published in Scientific Data, 2025
Recommended citation: Gao S, Liu X, Luo Y, Wang X, Zhao K, Chang V, Schatschneider B, Marom N. PAH101: A GW+BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals. Scientific Data. 2025 Apr 23;12(1):679.
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Published in Digital Discovery, 2025
Recommended citation: Gao S, Luo Y, Liu X, Marom N. Predicting the excited-state properties of crystalline organic semiconductors using GW+ BSE and machine learning. Digital Discovery. 2025.
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Published in The Journal of Physical Chemistry C, 2024
Recommended citation: Wang X, Gao S, Luo Y, Liu X, Tom R, Zhao K, Chang V, Marom N. Computational Discovery of Intermolecular Singlet Fission Materials Using Many-Body Perturbation Theory. The Journal of Physical Chemistry C. 2024 May 1;128(19):7841-64.
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Published in SCIENTIA SINICA Physica, Mechanica & Astronomica, 2022
Recommended citation: Zhou M, Luo Y, Song H. Applications of machine learning in relativistic heavy ion physics. SCIENTIA SINICA Physica, Mechanica & Astronomica. 2022 Apr 15; 52(5).
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Published in NOMAD, 2025
This is the PAH101 dataset of GW+BSE calculations for 101 molecular crystals of polycyclic aromatic hydrocarbons (PAHs) on NOMAD.
Recommended citation: Gao S, Liu X, Luo Y, Wang X, Zhao K, Chang V, Schatschneider B, Marom N. PAH101: AGW+ BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals. Scientific Data. 2025 Apr 23;12(1):679.
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