Statistics of dislocation avalanches in FCC and BCC metals: dislocation mechanisms and mean swept distances across microsample sizes and temperatures

Abstract

Plastic deformation in crystalline materials consists of an ensemble of collective dislocation glide processes, which lead to strain burst emissions in micro-scale samples. To unravel the combined role of crystalline structure, sample size and temperature on these processes, we performed a comprehensive set of strict displacement-controlled micropillar compression experiments in conjunction with large-scale molecular dynamics and physics-based discrete dislocation dynamics simulations. The results indicate that plastic strain bursts consist of numerous individual dislocation glide events, which span over minuscule time intervals. The size distributions of these events exhibit a gradual transition from an incipient power-law slip regime (spanning $$\approx$$ ≈ 2.5 decades of slip sizes) to a large avalanche domain (spanning $$\approx$$ ≈ 4 decades of emission probability) at a cut-off slip magnitude $${s}_{\mathrm{c}}$$ s c . This cut-off slip provides a statistical measure to the characteristic mean dislocation swept distance, which allows for the scaling of the avalanche distributions vis-à-vis the archetypal dislocation mechanisms in face-centered cubic (FCC) and body-centered cubic (BCC) metals. Our statistical findings provide a new pathway to characterizing metal plasticity and towards comprehension of the sample size effects that limit the mechanical reliability in small-scale structures.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 04, 2020
Source ID
10.1038/s41598-020-75934-5

Entities

People

  • Jaafar A El-Awady
  • Jan Očenášek
  • Javier Varillas
  • Jeffrey M. Wheeler
  • Johann Michler
  • Jorge Alcalá

Organizations

  • Air Force Office of Scientific Research
  • Ministry of Economy, Industry and Competitiveness
  • Ministry of Education, Youth and Sports

Tags

Fields of Study

  • Physics

Readers

  • Materials Science (Mechanical Engineering).
  • Powder metallurgy of Titanium alloys.
  • Regression Analysis.