The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene
The identification of atomic vacancy defects in graphene is an important and challenging issue, which involves inhomogeneous spatial randomness and requires high experimental conditions. In this paper, the fingerprints of resonant frequency for atomic vacancy defect identification are provided, base...
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| Format: | Article |
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MDPI AG
2021-12-01
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| Series: | Nanomaterials |
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| Online Access: | https://www.mdpi.com/2079-4991/11/12/3451 |
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| author | Liu Chu Jiajia Shi Eduardo Souza de Cursi |
| author_facet | Liu Chu Jiajia Shi Eduardo Souza de Cursi |
| author_sort | Liu Chu |
| collection | DOAJ |
| description | The identification of atomic vacancy defects in graphene is an important and challenging issue, which involves inhomogeneous spatial randomness and requires high experimental conditions. In this paper, the fingerprints of resonant frequency for atomic vacancy defect identification are provided, based on the database of massive samples. Every possible atomic vacancy defect in the graphene lattice is considered and computed by the finite element model in sequence. Based on the sample database, the histograms of resonant frequency are provided to compare the probability density distributions and interval ranges. Furthermore, the implicit relationship between the locations of the atomic vacancy defects and the resonant frequencies of graphene is established. The fingerprint patterns are depicted by mapping the locations of atomic vacancy defects to the resonant frequency magnitudes. The geometrical characteristics of computed fingerprints are discussed to explore the feasibility of atomic vacancy defects identification. The work in this paper provides meaningful supplementary information for non-destructive defect detection and identification in nanomaterials. |
| first_indexed | 2024-03-10T03:25:35Z |
| format | Article |
| id | doaj.art-a3dfda3f369f450b8fa6b2c35397141f |
| institution | Directory Open Access Journal |
| issn | 2079-4991 |
| language | English |
| last_indexed | 2024-03-10T03:25:35Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
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| series | Nanomaterials |
| spelling | doaj.art-a3dfda3f369f450b8fa6b2c35397141f2023-11-23T09:52:48ZengMDPI AGNanomaterials2079-49912021-12-011112345110.3390/nano11123451The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in GrapheneLiu Chu0Jiajia Shi1Eduardo Souza de Cursi2School of Transportation and Civil Engineering, Nantong University, Nantong 226019, ChinaSchool of Transportation and Civil Engineering, Nantong University, Nantong 226019, ChinaDépartement Mécanique, Institut National des Sciences Appliquées de Rouen, 76800 Rouen, FranceThe identification of atomic vacancy defects in graphene is an important and challenging issue, which involves inhomogeneous spatial randomness and requires high experimental conditions. In this paper, the fingerprints of resonant frequency for atomic vacancy defect identification are provided, based on the database of massive samples. Every possible atomic vacancy defect in the graphene lattice is considered and computed by the finite element model in sequence. Based on the sample database, the histograms of resonant frequency are provided to compare the probability density distributions and interval ranges. Furthermore, the implicit relationship between the locations of the atomic vacancy defects and the resonant frequencies of graphene is established. The fingerprint patterns are depicted by mapping the locations of atomic vacancy defects to the resonant frequency magnitudes. The geometrical characteristics of computed fingerprints are discussed to explore the feasibility of atomic vacancy defects identification. The work in this paper provides meaningful supplementary information for non-destructive defect detection and identification in nanomaterials.https://www.mdpi.com/2079-4991/11/12/3451fingerprintsatomic vacancy defectsresonant frequenciesgraphene |
| spellingShingle | Liu Chu Jiajia Shi Eduardo Souza de Cursi The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene Nanomaterials fingerprints atomic vacancy defects resonant frequencies graphene |
| title | The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene |
| title_full | The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene |
| title_fullStr | The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene |
| title_full_unstemmed | The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene |
| title_short | The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene |
| title_sort | fingerprints of resonant frequency for atomic vacancy defect identification in graphene |
| topic | fingerprints atomic vacancy defects resonant frequencies graphene |
| url | https://www.mdpi.com/2079-4991/11/12/3451 |
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