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Title: Tunable magnetism in metal adsorbed fluorinated nanoporous graphene

Abstract

Developing nanostructures with tunable magnetic states is crucial for designing novel data storage and quantum information devices. Using density functional theory, we study the thermodynamic stability and magnetic properties of tungsten adsorbed tri-vacancy fluorinated (TVF) graphene. We demonstrate a strong structure-property relationship and its response to external stimuli via defect engineering in graphene-based materials. Complex interplay between defect states and the chemisorbed atom results in a large magnetic moment of 7 μ B along with high in-plane magneto-crystalline anisotropy energy (MAE) of 17 meV. Under the influence of electric field, spin crossover effect accompanied by a change in the MAE is observed. The ascribed change in spin-configuration is caused by the modification of exchange coupling between defect states and a change in the occupation of d-orbitals of the metal complex. In conclusion, our predictions open a promising way towards controlling the magnetic properties in graphene based spintronic and non-volatile memory devices.

Authors:
 [1];  [2];  [2];  [3];  [1]
  1. Boise State Univ., ID (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Huazhong University of Science and Technology, Wuhan (China)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1324102
Grant/Contract Number:
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 6; Journal Issue: 6; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Electronic structure; Magnetic properties and materials; Two-dimensional materials

Citation Formats

Kumar, Pankaj, Sharma, Vinit, Reboredo, Fernando A., Yang, Li-Ming, and Pushpa, Raghani. Tunable magnetism in metal adsorbed fluorinated nanoporous graphene. United States: N. p., 2016. Web. doi:10.1038/srep31841.
Kumar, Pankaj, Sharma, Vinit, Reboredo, Fernando A., Yang, Li-Ming, & Pushpa, Raghani. Tunable magnetism in metal adsorbed fluorinated nanoporous graphene. United States. doi:10.1038/srep31841.
Kumar, Pankaj, Sharma, Vinit, Reboredo, Fernando A., Yang, Li-Ming, and Pushpa, Raghani. Wed . "Tunable magnetism in metal adsorbed fluorinated nanoporous graphene". United States. doi:10.1038/srep31841. https://www.osti.gov/servlets/purl/1324102.
@article{osti_1324102,
title = {Tunable magnetism in metal adsorbed fluorinated nanoporous graphene},
author = {Kumar, Pankaj and Sharma, Vinit and Reboredo, Fernando A. and Yang, Li-Ming and Pushpa, Raghani},
abstractNote = {Developing nanostructures with tunable magnetic states is crucial for designing novel data storage and quantum information devices. Using density functional theory, we study the thermodynamic stability and magnetic properties of tungsten adsorbed tri-vacancy fluorinated (TVF) graphene. We demonstrate a strong structure-property relationship and its response to external stimuli via defect engineering in graphene-based materials. Complex interplay between defect states and the chemisorbed atom results in a large magnetic moment of 7 μB along with high in-plane magneto-crystalline anisotropy energy (MAE) of 17 meV. Under the influence of electric field, spin crossover effect accompanied by a change in the MAE is observed. The ascribed change in spin-configuration is caused by the modification of exchange coupling between defect states and a change in the occupation of d-orbitals of the metal complex. In conclusion, our predictions open a promising way towards controlling the magnetic properties in graphene based spintronic and non-volatile memory devices.},
doi = {10.1038/srep31841},
journal = {Scientific Reports},
number = 6,
volume = 6,
place = {United States},
year = {Wed Aug 24 00:00:00 EDT 2016},
month = {Wed Aug 24 00:00:00 EDT 2016}
}

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