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| Hauptverfasser: | , , , |
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| Format: | Recurso digital |
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Zenodo
2025
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| Online-Zugang: | https://doi.org/10.5281/zenodo.15206611 |
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Inhaltsangabe:
- <p>This dataset contains 100,000 molecular structures sampled from a quantum molecular dynamics trajectory of a porphyrin molecule, generated using Density Functional Tight Binding (DFTB). The initial structure was obtained from ChemSpider (ID: 4086) and optimized using density functional theory (DFT) at the B3LYP/6-31G* level of theory.</p> <p>Subsequently, 150,000 femtoseconds (fs) of ground-state molecular dynamics at 300 K were performed using the DFTB+ package. From the final part of this trajectory, 100,000 snapshots were extracted at 1 fs intervals.</p> <p>For each structure, excitation energies were computed using time-dependent long-range corrected DFTB (TD-LC-DFTB). This dataset was used for evaluating uncertainty estimation methods for Gaussian process regression-based machine learning interatomic potentials, as described in the accompanying publication.</p> <p> </p> <p>In the .npz file the key for the coordinates is 'coordinates', the key for the nuclear charges is 'charges' and the key for the excitation energies is 'ES_energies'.</p>