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15 January, 2018

Event:  MSE PhD Dissertation Defense - Jie Chen
Location:  IMS-147B
Details: PhD Proposal Defense

Presenter: Jie Chen

Major Advisor: Dr. Avinash Dongare

Associate Advisors: Dr. Mark Aindow, Dr. Harold Brody, Dr. Seok-Woo Lee, Dr. Ying Li

Date: Monday, January 15, 2018

Time: 10:00 am

Room: IMS 147B

Title: Unraveling the Role of Interfaces in the Deformation and Failure Behavior of Metallic Materials under Dynamic Loading Conditions

Abstract:
Design of next-generation high strength metallic materials for damage-resistant applications relies on a fundamental understanding of the deformation mechanisms and failure behavior of these materials under dynamic loading conditions. The dynamic strength of metals is typically characterized based on the “spall strength” defined as the peak tensile pressure the metal can withstand prior to failure. For pure metals, the capability to increase the spall strength is limited due to insufficient microstructure features that can be used to tailor/modify the deformation and failure behavior. A promising strategy to further enhancing the spall strength is the addition of microstructural features such as bi-metal interfaces to the microstructure alloys to provide heterogeneities that may alter the nucleation and evolution of defects/damage. A critical challenge in engineering these microstructures is the lack of understanding of the role of bi-metal interfaces on the dynamic strengths of the metallic materials. Such an understanding is particularly challenging using experimental techniques due to the short time and length scales of the processes of nucleation and evolution of defects/damage.
This dissertation undertakes a systematic study to investigate the role of FCC/BCC interfaces on the dynamic strengths of bi-metal alloy systems at the atomic scales using molecular dynamics (MD) simulations. The Cu/Ta will be used as model systems for FCC/BCC interfaces. For Cu/Ta particular emphasis of the study is on the effects of structure, size and distribution of interfaces on the shock propagation, nucleation and evolution of dislocation densities, and void nucleation and growth behavior during spall failure. The aim is to identify key microstructural descriptors of the interfaces that determine the spall strength, so as to aid in the design of Cu/Ta microstructures with enhanced spall strengths for damage-tolerant applications. The proposed research also aims to extend this study to the Mg/Al system to investigate the role of FCC/HCP systems. A current challenge, however, is that the available interatomic potentials do not accurately reproduce the energetics of the various types of defects, defect interactions and accumulation under shock loading conditions. This dissertation therefore aims to address this challenge by using a machine learning approach based on artificial neural networks (ANN) to develop a more robust neural network interatomic potential (NNIP) for the Mg/Al system. The first applications of the NNIP will be the study of the role of FCC/HCP interfaces on the spall behavior for Mg/Al nanolaminate microstructures.

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