journal article·2020-12

Effect of nitrogen or boron impurities on the mechanical and vibrational properties of graphene nanosheets: a molecular dynamics approach

Mahboube Mehrabani, Mohammad Mahdi Khatibi, Mohammad Reza Ashory, Sadegh Sadeghzadeh

Micro & Nano Letters· Volume 15· Issue 14
Publisher page

Abstract

Investigation of mechanical and vibrational properties of nano‐structures using the analytical methods would be time‐consuming. Therefore, using a semi‐empirical method would reduce the time needed to investigate materials characterisation. One of the semi‐empirical approaches is molecular dynamics. In this Letter, the large‐scale atomic/molecular massively parallel simulator software is used to simulate the mechanical and vibrational behaviour of a nitrogen‐ and boron‐doped 24.04 × 51.13 Å graphene nano‐sheet. The natural frequencies, Young's modulus, and ultimate tensile strength (UTS) are studied. By adding impurity to the nanosheet and increasing its density, Young's modulus, UTS, and natural frequencies were decreased. The decrease in tensile properties was more significant in the case of boron impurity. When the boron (nitrogen) impurity increased to about 20%, Young's modulus and the first natural frequency were decreased 7.1% (9%) and 16.8% (73%), respectively. This illustrates that Young's modulus and natural frequencies are directly related. Therefore, for the same dimensions and boundary conditions, it is obvious that the increase in impurity content has reduced the natural frequencies of the nanostructure.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Thermal properties of materials · Boron and Carbon Nanomaterials Research · Carbon Nanotubes in Composites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Mechanical Engineering Department Semnan University Semnan P.O. Box 3513119111 Iran

Faculty of Mechanical Engineering Semnan University Semnan P.O. Box 3513119111 Iran

Nanotechnology Department School of New Technologies Iran University of Science and Technology (IUST) Tehran P.O. Box 1684613114 Iran

References (51)

Show source-provided references
1. 10.1021/nn100315s10.1021/nn100315s ↗
2. 10.1016/j.pmatsci.2011.03.00310.1016/j.pmatsci.2011.03.003 ↗
3. 10.1021/nn700143q10.1021/nn700143q ↗
4. 10.1002/smll.20080193810.1002/smll.200801938 ↗
5. 10.1063/1.325965010.1063/1.3259650 ↗
6. 10.1039/c0jm00782j10.1039/c0jm00782j ↗
7. 10.1039/C6RA14273G10.1039/C6RA14273G ↗
8. 10.1016/j.ijnonlinmec.2015.08.00210.1016/j.ijnonlinmec.2015.08.002 ↗
9. 10.1155/2015/49509510.1155/2015/495095 ↗
10. 10.1016/j.euromechsol.2015.09.00810.1016/j.euromechsol.2015.09.008 ↗
11. 10.1016/j.ijengsci.2017.08.01610.1016/j.ijengsci.2017.08.016 ↗
12. 10.1007/s00419‐015‐1037‐010.1007/s00419‐015‐1037‐0 ↗
13. Vibration analysis of material size‐dependent CNTs using energy equivalent model
14. 10.1016/j.ijengsci.2019.06.01610.1016/j.ijengsci.2019.06.016 ↗
15. 10.1080/15397734.2014.92822110.1080/15397734.2014.928221 ↗
16. 10.1177/002199831773182210.1177/0021998317731822 ↗
17. Axial and torsional free vibrations of elastic nano‐beams by stress‐driven two‐phase elasticity
18. 10.1016/j.compstruct.2017.02.09110.1016/j.compstruct.2017.02.091 ↗
19. 10.1016/j.compositesb.2019.01.01210.1016/j.compositesb.2019.01.012 ↗
20. 10.1016/j.ijengsci.2019.10314010.1016/j.ijengsci.2019.103140 ↗
21. 10.1103/PhysRevB.93.17411210.1103/PhysRevB.93.174112 ↗
22. 10.1016/S0894‐9166(16)30003‐910.1016/S0894‐9166(16)30003‐9 ↗
23. 10.1016/j.physleta.2011.11.03410.1016/j.physleta.2011.11.034 ↗
24. OkamotoS.ItoA.: ‘Investigation of mechanical properties of nitrogen‐containing graphene using molecular dynamics simulations’ Proceedings of the International Multi Conference of Engineers and Computer Scientists Volume I & Volume II Hong Kong 2012 pp.350–355
25. 10.1049/mnl.2010.005810.1049/mnl.2010.0058 ↗
26. 10.1016/j.ssc.2012.04.04810.1016/j.ssc.2012.04.048 ↗
27. 10.1007/s00707‐016‐1562‐010.1007/s00707‐016‐1562‐0 ↗
28. 10.1016/j.ijengsci.2019.01.00310.1016/j.ijengsci.2019.01.003 ↗
29. 10.1016/j.ijengsci.2018.05.00110.1016/j.ijengsci.2018.05.001 ↗
30. 10.1016/j.compstruct.2017.06.03910.1016/j.compstruct.2017.06.039 ↗
31. 10.1016/j.mechrescom.2014.08.00410.1016/j.mechrescom.2014.08.004 ↗
32. 10.1016/j.amc.2016.05.03410.1016/j.amc.2016.05.034 ↗
33. 10.1016/j.cap.2018.07.01410.1016/j.cap.2018.07.014 ↗
34. 10.1103/PhysRevB.86.11541010.1103/PhysRevB.86.115410 ↗
35. 10.1016/j.commatsci.2014.01.04010.1016/j.commatsci.2014.01.040 ↗
36. 10.1103/PhysRevB.80.11340510.1103/PhysRevB.80.113405 ↗
37. 10.1201/b1905610.1201/b19056 ↗
38. Wenzel H. · 2008
39. ZhangL.BrinckerR.: ‘An overview of operational modal analysis: major development and issues’.1st Int. Operational Modal Analysis Conf. Copenhagen Denmark 2005 pp.179–190
40. BrinckerR.ZhangL.AndersenP.: ‘Modal identification from ambient responses using frequency domain decomposition’.Proc. 18th Int. Modal Analysis Conf. (IMAC) San Antonio Texas 2000
41. 10.1088/0964‐1726/10/3/30310.1088/0964‐1726/10/3/303 ↗
42. Ewins D.J. · 1984
43. Available athttps://lammps.sandia.gov/
44. Chen D. · 2014
45. 10.1049/mnl.2015.042710.1049/mnl.2015.0427 ↗
46. 10.1007/s00339‐016‐0337‐810.1007/s00339‐016‐0337‐8 ↗
47. 10.1016/j.carbon.2016.03.00710.1016/j.carbon.2016.03.007 ↗
48. Huheey J. · 1958
49. 10.1016/j.jsv.2009.03.00710.1016/j.jsv.2009.03.007 ↗
50. 10.1002/978047011786610.1002/9780470117866 ↗
51. Timoshenko S.P. · 2009