Dr. Miller’s research interests include defect and structural evolution in crystalline material and experimental characterization via advanced electron microscopy techniques. She is particularly focused on deformation processing of metals and the associated microstructural evolution, particularly texture evolution, recovery, and recrystallization. Her group’s primary focus is on linking macroscopic processing phenomena to micro- and nanoscale mechanisms, enabling the development of predictive material models for engineering applications. Much of the group’s work has been in thermomechanical processing of low-symmetry metals including titanium alloys for aerospace and magnesium alloys for automotive and consumer electronic applications.

HeRX in γ/γ’ systems: Data-Driven Recyrstallization Analysis (Hγγ’DRA)

Heteroepitaxial Recrystallization is a strain driven recrystallization mechanism discovered to occur in gamma-gamma prime Ni-superalloys. HeRX is a mechanism of concern since it can lead to abnormal grain growth in superalloys, however the mechanism also hold’s promise for alternative processing methods resulting in recrystallization. The goal of this research is to determine which systems HeRX can occur in, which variables effect and activate the mechanism, and how the mechanism can be controlled.

Research Activities: Polishing of Ni and Co Base Superalloys, Scanning Electron Microscopy (SEM), Electron Backscatter Diffraction (EBSD), Energy Dispersive Spectroscopy (EDS), Image Processing using Matlab and the MTEX toolbox.

Current Students Involved: Cameron Hale, Scott Bentz.

Data Science Enabled Mechanistic Investigation of Liquid Metal Infiltration, Cracking, and Chemical Attack (DEMILICH)

Liquid Metal Embrittlement is a phenomenon in which a typically ductile solid metal becomes brittle or otherwise weakened in a particular liquid metal environment. Despite being studied for over 100 years, no proposed mechanism exists that satisfactorily describes even a majority of liquid metal embrittlement systems, and no model has been developed that can predict whether and given liquid-solid metal couple will result in embrittlement. The goal of this project is to leverage modern data science and machine learning techniques to identify previously hidden trends in historical data, and to guide experimentation to develop a model of LME to enable prediction and to reduce the hazard posed to emerging liquid metal based technologies such as flexible gallium based conductors or liquid cooled nuclear reactors.

Research Activities: Datamining, Clustering Analysis, Machine Learning, Mechanical Testing, In-Situ Scanning Electron Microscopy, Electron Backscatter Diffraction (EBSD), Thermo-Calc.

Current Students Involved: Justin Norkett, Cameron Frampton, Andrew Talburt

Improving Formability at Room Temperature by Inhibiting Twin Transfer (IFRIT)

Magnesium alloys are of critical interest to the aerospace, automotive, and defense industries, but are currently limited in use due to poor ductility and formability at room temperature. Magnesium’s plastic anisotropy and lack of active slip systems under ambient conditions result in excessive twinning and rapid texture formation, ultimately resulting in brittle failure. This project seeks to investigate the ways intermetallic particles modify and inhibit twinning behavior within these alloys, and to determine the role these intermetallics play in generating localized stress states that can activate additional slip systems at room temperature.

Research Activities: Mechanical Testing, Scanning Electron Microscopy, Electron Backscatter Defraction, Twinning Analyis, Full-Field Viscoplastic Fast Fourier Transform (VPFFT) modeling

Current Students Involved: Benjamin Anthony

Globularization In α/β and Near-α Titanium Alloys (GIαNT)

Like magnesium, titanium alloys are of critical interest to the aerospace, transportation, and defense industries, but unfavorable lamellar microstructures develop during initial processing steps. Costly and energy intensive thermomechanical processes are required to transform the microstructure to one favorable for end use. This project seeks to understand the underlying mechanisms of this microstructural evolution (called globularization) in order to promote the development of more efficient processing procedures.

Research Activities: Scanning Electron Microscopy (SEM), Electron Backscatter Diffraction (EBSD), Viscoplastic Self-Consistent (VPSC) Modeling

Current Students Involved: Benjamin Begley, Jennifer Perez, Thomas Spradley, Cameron Frampton