| Download | - Download dataset: Big graphene dataset (BIGGRAPHENEDATASET.TAR.GZ, 3.6 GiB)
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| DOI | Resolve DOI: https://doi.org/10.4224/c8sc04578j.data |
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| Author | Search for: Mills, Kyle1ORCID identifier: https://orcid.org/0000-0003-1768-6873; Search for: Tamblyn, Isaac2ORCID identifier: https://orcid.org/0000-0002-8146-6667 |
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| Name affiliation | - University of Ontario Institute of Technology
- National Research Council of Canada. Security and Disruptive Technologies
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| Format | Text, Dataset |
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| Physical description | 1 compressed .tar.gz file (3.77 GB) containing 60,744 .h5 testing files and 501,473 .h5 training files |
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| Abstract | Density functional theory simulations of graphite structures with random (in size and location) structural defects. Dataset contains coordinates of carbon atoms and the total energy computed using the PBE functional as implemented in the software VASP. Input parameter files are also included so that the calculations can be reproduced.
NOTE: This dataset is useful for training machine learning models of carbon materials, as there are more than 500,000 unique calculations of graphene (3.5 nm x 3.5 nm unit cell). The dataset was used as training data for an extensive deep neural network which was used to simulate a micron of graphene. |
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| Publication date | 2019-03-12 |
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| Date created | 2018 |
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| Publisher | National Research Council of Canada |
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| Licence | |
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| Other version | |
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| Language | English |
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| Export citation | Export as RIS |
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| Collection | NRC Research Data |
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| Record identifier | 9f09901d-0736-4204-a35d-0c88ffb8da3b |
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| Record created | 2019-03-12 |
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| Record modified | 2022-05-09 |
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