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Volumn 114, Issue 10, 2015, Pages

Identifying structural flow defects in disordered solids using machine-learning methods

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DEFECTS; GLASS; GLASS TRANSITION;

EID: 84925373077     PISSN: 00319007     EISSN: 10797114     Source Type: Journal    
DOI: 10.1103/PhysRevLett.114.108001     Document Type: Article
Times cited : (491)

References (40)
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    • M. L. Manning and A. J. Liu, Phys. Rev. Lett. 107, 108302 (2011). PRLTAO 0031-9007 10.1103/PhysRevLett.107.108302
    • (2011) Phys. Rev. Lett. , vol.107 , pp. 108302
    • Manning, M.L.1    Liu, A.J.2
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    • J. J. Gilman, Phys. Today 28, No. 5, 46 (1975). PHTOAD 0031-9228 10.1063/1.3068966
    • (1975) Phys. Today , vol.28 , Issue.5 , pp. 46
    • Gilman, J.J.1
  • 26
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    • See the Supplemental Material at for details, which includes Refs. [7,12,13,15,16,27]
    • See the Supplemental Material at http://link.aps.org/supplemental/10.1103/PhysRevLett.114.108001 for details, which includes Refs. [7,12,13,15,16,27].
  • 30
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    • S. Plimpton, J. Comput. Phys. 117, 1 (1995). JCTPAH 0021-9991 10.1006/jcph.1995.1039
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    • Plimpton, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.