Data

Graphene Nanoflake Data Set

Commonwealth Scientific and Industrial Research Organisation
Barnard, Amanda ; Sun, Baichuan ; Shi, Hongqing (Robyn)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/08/57998CC4D7891&rft.title=Graphene Nanoflake Data Set&rft.identifier=https://doi.org/10.4225/08/57998CC4D7891&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This is a set of graphene nanoflake FINAL CONFIGURATIONS, for use in data driven studies. These structures have been optimized (fully relaxed) using Density Functional Tight Binding. Sizes range from 16 atoms to 2176 atoms, and shapes include trigons, hexagons and a matrix of rectangular structures defined by the number of graphene rings along the zigzag (zz) and armchair (ac) directions. Hydrogen terminated versions of the structures are also provided.All files are in XYZ format, and the naming convention is defined in the accompanying spreadsheet that lists all of the structural, statistical and energetic properties. This spreadsheet is available in the Supporting Attachments (in two formats)Lineage: Simulated by Hongqing Shi for the purposes of studying the impact of polydispersivity on the properties of graphene ensembles.&rft.creator=Barnard, Amanda &rft.creator=Sun, Baichuan &rft.creator=Shi, Hongqing (Robyn) &rft.date=2016&rft.edition=v1&rft.relation=https://publications.csiro.au/rpr/pub?list=SEA&pid=csiro:EP133839&sb=RECENT&expert=false&n=22&rpp=25&page=3&tr=268&q=barnard&dr=all&rft_rights=CSIRO Data Licence https://research.csiro.au/dap/licences/csiro-data-licence/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2016.&rft_subject=materials&rft_subject=molecules&rft_subject=molecular&rft_subject=nanoparticle&rft_subject=nanostructure&rft_subject=computational&rft_subject=DFT&rft_subject=simulation&rft_subject=results&rft_subject=graphene&rft_subject=Theory and design of materials&rft_subject=Macromolecular and materials chemistry&rft_subject=CHEMICAL SCIENCES&rft_subject=Theoretical and computational chemistry not elsewhere classified&rft_subject=Theoretical and computational chemistry&rft_subject=Nanomaterials&rft_subject=Nanotechnology&rft_subject=ENGINEERING&rft_subject=Nanotechnology not elsewhere classified&rft_subject=Condensed matter modelling and density functional theory&rft_subject=Condensed matter physics&rft_subject=PHYSICAL SCIENCES&rft_subject=Condensed matter physics not elsewhere classified&rft.type=dataset&rft.language=English Access the data
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This is a set of graphene nanoflake FINAL CONFIGURATIONS, for use in data driven studies. These structures have been optimized (fully relaxed) using Density Functional Tight Binding. Sizes range from 16 atoms to 2176 atoms, and shapes include trigons, hexagons and a matrix of rectangular structures defined by the number of graphene rings along the zigzag (zz) and armchair (ac) directions. Hydrogen terminated versions of the structures are also provided.

All files are in XYZ format, and the naming convention is defined in the accompanying spreadsheet that lists all of the structural, statistical and energetic properties. This spreadsheet is available in the Supporting Attachments (in two formats)
Lineage: Simulated by Hongqing Shi for the purposes of studying the impact of polydispersivity on the properties of graphene ensembles.

Available: 2016-07-28

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Subjects
Chemical Sciences | Condensed Matter Modelling and Density Functional Theory | Condensed Matter Physics | Condensed Matter Physics Not Elsewhere Classified | DFT | Engineering | Macromolecular and Materials Chemistry | Nanomaterials | Nanotechnology | Nanotechnology Not Elsewhere Classified | Physical Sciences | Theoretical and Computational Chemistry | Theoretical and Computational Chemistry Not Elsewhere Classified | Theory and Design of Materials | computational | graphene | materials | molecular | molecules | nanoparticle | nanostructure | results | simulation |

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Australian Research Council (ARC) : DP110101362

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ACN 633 798 857