Research Overview

Brief summary

Integrated computational material models that link materials processing to microstructure to properties will enable designers to engineer the next generation of materials and components through coupling both the material system/processing with component geometry during the engineering design process. However, to realize this vision, integrated multiscale material models that capture both the macroscopic material response and the underlying nanoscale physical mechanisms must be developed. This statement outlines my interest in developing a world-class research group for integrated computational design of advanced materials for aerospace applications (e.g., high temperature materials, etc.). My primary research interest is to delve into multiscale modeling and integrated computational materials engineering through examining the relationship between microstructure and properties over multiple length and time scales, with specific emphasis on structure-property relationships that help understand the mechanics and physics of material response. My dissertation experience used computational techniques to investigate these relationships in interfaces at the nanoscale. Contrary to my dissertation research, my postdoctoral experience used both experimental and computational techniques to study the relationship between microstructure and high temperature mechanics (creep, fatigue) in high temperature structural materials. At CAVS, my research projects involve high temperature aerospace material uncertainty and its relation to failure, multi-objective design of nanoscale material models, mechanics of polymer and polymer composites for automotive systems, lightweight automotive alloy design (Mg and Al alloys) for automotive applications, steel alloy design, and nuclear materials design. Integrating computational material models that link materials processing to microstructure to properties will result in a paradigm shift from material selection to material design for defense and energy applications.

Extended Discussion

Accelerating the pace of discovery, development, manufacturing, and deployment of advanced materials systems has been described as crucial to achieving global competitiveness in the 21st century in a “Materials Genome Initiative” white paper recently released by the White House's National Science and Technology Council. Moreover, recent discussions and reports on integrated computational materials engineering (ICME) provide a conceptual roadmap for how to design materials, but the community also agrees that there are still a number of challenges that must be addressed before ICME reaches its full potential. Nevertheless, success stories in the automotive and aerospace sectors show that the grand challenge of reducing the materials design cycle through computational means is solvable. To do so requires physically-based models that accurately describe the “processing-structure-property-performance” relationships over multiple length and time scales, though. Multiscale constitutive models that adequately capture these relevant physics at each length scale are still evolving and there is a need for additional information from simulations at multiple length and time scales (electronic structure to finite element), 3D microstructural characterization, and critical experiments to develop the necessary material models for specific applications. Future research in this area will require an interdisciplinary approach with researchers familiar with both materials and their properties, familiar with engineering design approaches, as well as with how to combine information from both computational techniques and experiments.

• • Grain boundary inelastic deformation of nanocrystalline materials. Grain boundary properties are important to understand mechanical behavior in nano- and polycrystalline materials. Prior work explored dislocation nucleation to shed light on deformation mechanisms in nanocrystalline materials. Molecular dynamics simulations were used to investigate the effect of grain boundary character, material, temperature, and stress state on dislocation nucleation in various grain boundary systems. In addition to examining the heterogeneous dislocation nucleation mechanisms, phenomenological relationships that predict the stresses required to nucleate dislocations from the boundary are formulated in terms of continuum parameters.

  • Microstructure-sensitive design of high temperature materials. Microstructural-sensitive design of single crystal nickel-base superalloys for use in aerospace turbine blade applications can reduce the lead time of new alloy/process development. This program entailed understanding mechanical behavior of high temperature superalloys at relevant length scales and stress states for aerospace applications, i.e., high temperature (up to 1100 C) creep and fatigue. An MTS tensile system was set up to deform specimens at 1100 C with a specimen size (3-mm x 1-mm cross-section) that can be directly extracted from turbine blades.

  • 3D Materials Characterization and Reconstruction. 3D material characterization requires accurately identifying microstructure features and quantifying the relevant statistics. In this work, the 3D microstructure and associated statistics of a turbine blade were characterized using etched optical montage images to reconstruct statistically-informed synthetic microstructures for modeling purposes. Digital image processing techniques, including feature identification and image segmentation, were used to characterize image montages to show how part geometry and processing affect the underlying single crystal microstructure (i.e., spatial statistics of dendrites, eutectic particles, pores, and carbides). More recent work has examined how various statistical descriptors affect the microstructure reconstruction process. Long term interests in this area include 4D material science whereby 3D microstructure is measured experimentally and its evolution is tracked as a function of time and/or deformation.

  • In situ microstructure evolution during deformation. At AFRL, in situ SEM tensile experiments were combined with digital image correlation to analyze how microstructure influences the localization of strain and damage near grain boundaries in polycrystalline nickel-based superalloys. At CAVS, acoustic emission has been combined with optical images obtained during interrupted testing to non-destructively quantify damage evolution (e.g., due to particle cracking) as a function of strain in automotive alloys.

  • Computational materials design for energy-related applications. Point defects and alloying elements/impurities in grain boundaries plays an important role in the mechanical behavior of automotive and nuclear materials. This project explores their segregation to a database of grain boundary structures using an unprecedented number of simulations (>1,000,000). Materials informatics and data mining approaches are being used to develop new knowledge pertaining to their interaction. Moreover, subsequent work has explored heterogeneous twin and dislocation nucleation in HCP magnesium as well as void nucleation/growth in Al/Mg systems, which are both vital for capturing plasticity in these alloys.