.. This file is autogenerated by dev/scripts/generate_page.py AC-2D-22 ======== .. grid:: 1 1 2 2 .. grid-item:: .. raw:: html :file: ../_static/visualisations/AC-2D-22.html .. grid-item:: :class: info-card Amorphous, 2D graphene structures generated using a Monte Carlo bond-switching algorithm, as described in Figure 3 of the paper: `Exploring the Configurational Space of Amorphous Graphene with Machine-Learned Atomic Energies `_. Files are downloaded from `Zenodo `_. .. code-block:: pycon >>> from load_atoms import load_dataset >>> load_dataset("AC-2D-22") AC-2D-22: structures: '150' atoms: 30,000 species: C: 100.00% properties: per atom: (forces, local_energy, nn_local_energy) per structure: (beta, config, criterion) License ------- This dataset is licensed under the `CC BY-NC-SA 4.0 `_ license. Citation -------- If you use this dataset in your work, please cite the following: .. code-block:: latex @article{El-Machachi-22-10, title = { Exploring the Configurational Space of Amorphous Graphene with Machine-Learned Atomic Energies }, author = { {El-Machachi}, Zakariya and Wilson, Mark and Deringer, Volker L. }, year = {2022}, journal = {Chemical Science}, doi = {10.1039/D2SC04326B} } Properties ---------- **Per-atom**: .. list-table:: :header-rows: 1 * - Property - Units - Type - Description * - :code:`forces` - eV/Å - :class:`ndarray(N, 3) ` - force vectors (C-GAP-17) * - :code:`local_energy` - eV - :class:`ndarray(N,) ` - local energy of each atom (C-GAP-17) * - :code:`nn_local_energy` - eV - :class:`ndarray(N,) ` - average nearest neighbour local energy (C-GAP-17) **Per-structure**: .. list-table:: :header-rows: 1 * - Property - Units - Type - Description * - :code:`beta` - 1/eV - :class:`~float` - β used for MC bond-switching * - :code:`criterion` - - :class:`~str` - energy term used in MC criterion * - :code:`config` - - :class:`~str` - type of the structure (paracrystalline | CRN) Miscellaneous information ------------------------- ``AC-2D-22`` is imported as an :class:`~load_atoms.atoms_dataset.InMemoryAtomsDataset`: .. dropdown:: Importer script for :code:`AC-2D-22` .. literalinclude:: ../../../src/load_atoms/database/importers/ac_2d_22.py :language: python .. dropdown:: :class:`~load_atoms.database.DatabaseEntry` for :code:`AC-2D-22` .. code-block:: yaml name: AC-2D-22 year: 2022 category: Synthetic Data license: CC BY-NC-SA 4.0 minimum_load_atoms_version: 0.2 description: | Amorphous, 2D graphene structures generated using a Monte Carlo bond-switching algorithm, as described in Figure 3 of the paper: `Exploring the Configurational Space of Amorphous Graphene with Machine-Learned Atomic Energies `_. Files are downloaded from `Zenodo `_. citation: | @article{El-Machachi-22-10, title = { Exploring the Configurational Space of Amorphous Graphene with Machine-Learned Atomic Energies }, author = { {El-Machachi}, Zakariya and Wilson, Mark and Deringer, Volker L. }, year = {2022}, journal = {Chemical Science}, doi = {10.1039/D2SC04326B} } per_atom_properties: forces: desc: force vectors (C-GAP-17) units: eV/Å local_energy: desc: local energy of each atom (C-GAP-17) units: eV nn_local_energy: desc: average nearest neighbour local energy (C-GAP-17) units: eV per_structure_properties: beta: desc: β used for MC bond-switching units: 1/eV criterion: desc: energy term used in MC criterion config: desc: type of the structure (paracrystalline | CRN) representative_structure: 61 # TODO: remove after Dec 2024 # backwards compatability: unused as of 0.3.0 files: - url: https://zenodo.org/record/7221166/files/data.tar.gz hash: 023de5805f15 processing: - Custom: id: AC-2D-22