Predictive Modeling on the Mechanical Performance of Structural Materials at Complex Environments

Transcription

1 Predictive Modeling on the Mechanical Performance of Structural Materials at Complex Environments a tale of two solids by energy landscape-based atomistic modeling YUE FAN Assistant Professor Department of Mechanical Engineering University of Michigan, Ann Arbor

2 Compelling Need in Materials Performance Under Complex Environments far- from- Equilibrium high strain rates non-uniform thermo-mechanical environments non-equilibrium solidifications, large residue stresses and distortions 2 Presentation_name extreme T, irradiation, chemistry

3 Compelling Need in Materials Performance Under Complex Environments far- from- Equilibrium 3 Presentation_name

4 Compelling Need in Materials Performance Under Complex Environments far- from- Equilibrium 4 Presentation_name

5 S1: Disloca2on- Mediated Mechanics in Crystalline Materials q Multi-scale modeling scheme: current methods & challenges Dislocation-mediated microstructural evolution is an immensely complicated phenomenon involving multiple scales over many orders of magnitude. Length Scale m mm Atomic- scale µm e.g. first principle models, molecular dynamics (MD) MD ab initio nm challenges in traditional scheme Meso- scale e.g. dislocation dynamics (DD), visco-plastic self-consistent (VPSC) DD FEM Macro- scale e.g. finite element method (FEM) Traditional MD simulations cannot be validated by in situ TEM experiments MD simulations Condition: 2x10 7 s -1, 100 K Outcome: obstacle remains intact gliding dislocation SFT remains intact in situ TEM Condition: 10-2 s -1, 300 K Outcome: obstacle is removed by dislocation SFT absorption & gliding dislocation jog formation s 5 Presentation_name 10-6 s Time Scale 10 0 s 10 6 s

6 S1: Disloca2on- Mediated Mechanics in Crystalline Materials q Multi-scale modeling scheme: current methods & challenges Dislocation-mediated microstructural evolution is an immensely complicated phenomenon involving multiple scales over many orders of magnitude. Length Scale m mm Atomic- scale µm e.g. first principle models, molecular dynamics (MD) MD ab initio nm challenges in traditional scheme Meso- scale e.g. dislocation dynamics (DD), visco-plastic self-consistent (VPSC) DD FEM Macro- scale e.g. finite element method (FEM) Traditional MD simulations cannot be validated by in situ TEM experiments MD simulations Condition: 2x10 7 s -1, 100 K Outcome: obstacle remains intact gliding dislocation SFT remains intact in situ TEM Condition: 10-2 s -1, 300 K Outcome: obstacle is removed by dislocation SFT absorption & gliding dislocation jog formation s 6 Presentation_name 10-6 s Time Scale 10 0 s 10 6 s

7 S1: Disloca2on- Mediated Mechanics in Crystalline Materials q Employ PEL-based techniques to provide reliable mechanisms and parameters to higherlevel models such as DD, VPSC, and FEM, to enhance the capability of predictive design. Length Scale m mm Atomic- scale µm e.g. first principle models, molecular dynamics (MD) MD ab initio nm challenges in traditional scheme Meso- scale e.g. dislocation dynamics (DD), visco-plastic self-consistent (VPSC) DD FEM Macro- scale e.g. finite element method (FEM) Proposed new modeling roadmap to capture the fundamental processes at realistic timescale exp. verification Traditional MD simulations cannot be validated by in situ TEM experiments MD simulations Condition: 2x10 7 s -1, 100 K Outcome: obstacle remains intact gliding dislocation SFT remains intact in situ TEM Condition: 10-2 s -1, 300 K Outcome: obstacle is removed by dislocation SFT absorption & gliding dislocation jog formation s 7 Presentation_name 10-6 s Time Scale 10 0 s 10 6 s

8 S2: Mechanics of Disordered Alloys (e.g. Metallic Glasses) Processing history dependence cooling rate Glass (non-equilibrium) Testing condition dependence Crystal 8 Presentation_name P. G. Debenede*, F. H. S/llinger, Nature (2001)

9 Effec2ve PEL- Property Rela2onship Fan et al, Nat. Commun. 5 (2014) 5083; Fan et al, Phys. Rev. Lett. 115 (2015) ; Fan et al, Nat. Commun. 8 (2017) deis E = ν exp( A ) [ E A ER ] dt k BT Intrinsic Energy Dissipation Rate 9 Presentation_name & (ε&, φ&) +Λ ext coupling with external stimuli

10 Compelling Need in Materials Performance Under Complex Environments far- from- Equilibrium 10 Presentation_name What s Next?