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Spice dipeptides partial relaxation (#428)
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amcisaac authored Feb 27, 2025
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| `OpenFF NAGL2 Training Optimization Dataset v4.0` | [2024-12-09-OpenFF-NAGL2-Training-Optimization-Dataset-v4.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-12-09-OpenFF-NAGL2-Training-Optimization-Dataset-v4.0) | Optimization dataset for NAGL2 training, combined and filtered | Si, B, O, I, S, Cl, N, H, C, P, F, Br | |
| `SPICE Dipeptides Lowest E Conformer Optimization Dataset v4.0` | [2025-01-08-SPICE-Dipeptides-Lowest-E-Conformer-Optimization-Dataset-v4.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2025-01-08-SPICE-Dipeptides-Lowest-E-Conformer-Optimization-Dataset-v4.0) | Optimization dataset for the lowest energy conformers of the Dipeptides subset of SPICE | H, S, C, O, N | |
| `SPICE DES370k Monomers Lowest E Conformer Optimization Dataset v4.0` | [2025-01-08-SPICE-DES370k-Monomers-Lowest-E-Conformer-Optimization-Dataset-v4.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2025-01-08-SPICE-DES370k-Monomers-Lowest-E-Conformer-Optimization-Dataset-v4.0) | Optimization dataset for the lowest energy conformer of molecules in the DES370k monomer subset of SPICE | S, O, F, P, Br, N, H, C, Cl, I | |
| `SPICE Dipeptides Partial Relaxation Dataset v4.0` | [2025-02-26-SPICE-Dipeptides-Partial-Relaxation-Dataset-v4.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2025-02-26-SPICE-Dipeptides-Partial-Relaxation-Dataset-v4.0) | Partial relaxation dataset for the Dipeptides subset of SPICE | H, S, C, O, N | |
# TorsionDrive Datasets
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# SPICE Dipeptides Partial Relaxation Dataset v4.0

## Description
A dataset containing all entries of the `Dipeptides` subset of the SPICE dataset,
optimized for until the energy converges within 1e-4 Ha, at the OpenFF default level of theory (B3LYP-D3BJ/DZVP).
Detailed description on how the original dataset is generated can be found at https://github.com/openmm/spice-dataset/tree/main/dipeptides.


## General information
* Name: SPICE Dipeptides Partial Relaxation Dataset v4.0
* Number of unique molecules: 677
* Number of conformers: 33850
* Number of conformers (min, mean, max): 50.00, 50.00, 50.00
* Molecular weight (min, mean, max): 187.20, 313.73, 445.52
* Charges: -2.0 -1.0 0.0 1.0 2.0
* Dataset submitter: Alexandra McIsaac
* Dataset generator: Alexandra McIsaac

## QCSubmit generation pipeline
* `generate-dataset.ipynb`: Notebook used to generate dataset

## QCSubmit Manifest
* `dataset.json.bz2`: Compressed dataset ready for submission
* `dataset.pdf`: Visualization of dataset molecules
* `dataset.smi`: Smiles strings for dataset molecules
* `generate-dataset.ipynb`: Notebook used to generate dataset
* `input_environment.yaml`: Environment file used to create Python environment for the notebook
* `input_environment_full.yaml`: Fully-resolved environment used to execute the notebook.

## Metadata
* Elements: {O, S, H, N, C}
* Spec: default
* basis: DZVP
* implicit_solvent: None
* keywords: {}
* maxiter: 200
* method: B3LYP-D3BJ
* program: psi4
* SCF properties:
* dipole
* quadrupole
* wiberg_lowdin_indices
* mayer_indices
* GeometricProcedure
* program: geometric
* coordsys: dlc
* enforce: 0.0
* epsilon: 1e-05
* reset: True
* qccnv: False
* molcnv: False
* check: 0
* trust: 0.1
* tmax: 0.3
* maxiter: 300
* convergence_set: CUSTOM
* constraints: {}
* converge: ['energy', '1e-4', 'grms', '1', 'gmax', '1', 'drms', '1', 'dmax', '1']
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