4.7 Article

Tuned Critical Avalanche Scaling in Bulk Metallic Glasses

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SCIENTIFIC REPORTS
卷 4, 期 -, 页码 -

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NATURE RESEARCH
DOI: 10.1038/srep04382

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资金

  1. US National Science Foundation (NSF) [DMR 1005209, DMS 1069224, DMR-0909037, CMMI-0900271]
  2. Department of Energy (DOE) [NEUP 00119262, DE-FE-0008855, DE-FE-0011194]
  3. National Natural Science Foundation of China [51101110]
  4. Youth Science Foundation of Shanxi Province, China [2012021018-1]
  5. U.S. Army Research Office [W911NF-13-1-0438]
  6. Division Of Materials Research
  7. Direct For Mathematical & Physical Scien [0909037] Funding Source: National Science Foundation
  8. Division Of Materials Research
  9. Direct For Mathematical & Physical Scien [1005209] Funding Source: National Science Foundation
  10. Division Of Mathematical Sciences
  11. Direct For Mathematical & Physical Scien [1069224] Funding Source: National Science Foundation
  12. Div Of Civil, Mechanical, & Manufact Inn
  13. Directorate For Engineering [1100080] Funding Source: National Science Foundation
  14. Div Of Civil, Mechanical, & Manufact Inn
  15. Directorate For Engineering [0900271] Funding Source: National Science Foundation

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Ingots of the bulk metallic glass (BMG), Zr64.13Cu15.75Ni10.12Al10 in atomic percent (at. %), are compressed at slow strain rates. The deformation behavior is characterized by discrete, jerky stress-drop bursts (serrations). Here we present a quantitative theory for the serration behavior of BMGs, which is a critical issue for the understanding of the deformation characteristics of BMGs. The mean-field interaction model predicts the scaling behavior of the distribution, D(S), of avalanche sizes, S, in the experiments. D(S) follows a power law multiplied by an exponentially-decaying scaling function. The size of the largest observed avalanche depends on experimental tuning-parameters, such as either imposed strain rate or stress. Similar to crystalline materials, the plasticity of BMGs reflects tuned criticality showing remarkable quantitative agreement with the slip statistics of slowly-compressed nanocrystals. The results imply that material-evaluation methods based on slip statistics apply to both crystalline and BMG materials.

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