Research


The MONSTER group’s research interests include defect and structural evolution in crystalline material and experimental characterization via advanced electron microscopy techniques. They are particularly focused on deformation processing of metals and the associated microstructural evolution, particularly texture evolution, recovery, and recrystallization. The 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.

Current Projects


The MONSTER menagerie.

Hγγ’DRA

HeRX in γ/γ’ systems: Data-Driven Recrystallization Analysis

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.

MANTICORE

Magnetic field-induced Anisotropic Tailoring of Iron-Carbon alloys for Optimal Transformation Evolution

Magnetic field-assisted processing is a developing, energy-efficient alternative to current heat treatment processes in the steel industry, which leverages a high static magnetic field to improve processing outcomes. Attempts to precisely tailor steel microstructures using magnetic field-assisted processing are hindered by poor understanding of how the field alters microstructural evolution. In this project, we use electron backscatter diffraction to examine martensite morphologies and reconstruct prior austenite microstructures to reveal the effects of processing under varied magnetic field strengths, annealing times, and heating methods.

ARACHNE

Agitated Ray Actuated Construction in High/No Atmosphere Environments

A finely tuned laser beam can induce a thermal gradient in a sample, causing a through thickness differential in thermal expansion and yield strength that can induce plastic deformation. This phenomenon works on a wide variety of materials regardless of ductility to create a staggering array of geometries, but little is known about the microstructural evolution during the process. Additionally, difficulties in predictive modeling for multiple passes makes laser forming currently impractical for large scale industrial applications. This project seeks to properly predict and characterize the effects of multi-pass laser forming on various space ready materials in atmospheric and vacuum conditions for on-orbit construction.

SLIME

Solid-Liquid Interface-driven Microstructural Evolution

Liquid Metal Embrittlement (LME) is a phenomenon in which a typically ductile solid metal becomes brittle or otherwise weakened in a particular liquid metal environment. Despite millennia of documented observation and over a century of active investigation, the underlying mechanisms of LME remain poorly understood. As liquid metals have found increased interest in the fields of microelectronics and nuclear fusion, it is more important than ever to be able to predict LME in critical environments. This project seeks to untangle the complex web of microstructural interactions and evolutions seen in various systems in order to predict the destructive (and sometimes beneficial) effects of liquid metals.

PIRATES

Process-Scale Industry-Research Automated Texture Evolution Simulation

The PIRATES framework links the commercial finite element software, DEFORM with the viscoplastic self-consistent (VPSC) mean-field crystal plasticity model as a post-processor to predict site-specific texture evolution, with a focus on computational efficiency and user-level modularity for an evolving forming industry ICME (integrated computational materials engineering) pipeline.

VAMPYR

VPSC Automation in MTEX for Polycrystal plasticitY Research

A toolbox for running and automating the Viscoplastic Self-Consistent (VPSC) model using MATLAB, depending on the MTEX crystallographic toolbox.

DRAGON

Digital Reconstruction of Ancient Graphical ODFs (eNabling quantitative comparative analysis)

DRAGON is a MATLAB-based tool for the digitization of pole figures and ODFs from images published in literature, developed by the MONSTER Research Group at the University of Florida in order to enable quantitative comparison of experimental and simulated texture data with old experiments where the only remnant of the original texture data is a scan of a scan of a journal and the pole figure looks like it was painted by Salvador Dali. DRAGON allows users to upload images of pole figures and manually add datapoints with known values on the pole figure (generally at contour lines and minima/maxima). Projecting that data onto the sphere then interpolating between the contours provides an estimation of the formerly-analog pole figure which can be evaluated for any pole orientation. With the data for enough unique poles, DRAGON uses the MTEX algorithm to reconstruct an ODF from the pole figures, in much the same way one uses MTEX to reconstruct an ODF from X-ray diffraction data.

PHOENIX

Pt/Co magnet Hysteresis Optimization: Evolution during aNnealing In eXtreme fields

CHIMERA

Conventional Heating vs. Induction in Metals: Effects on Recrystallization Attributes

KOBOLD

Kinetic Oxide Buildup for Optimal Laser-forming Data

DEMILICH (Inactive)

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

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.

IFRIT (Inactive)

Improving Formability at Room Temperature by Inhibiting Twin Transfer

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.

CERBERUS (Inactive)

Cooperative Evolution Restricting Breakdown Efficiency Under Rotationally Uniform Strains