Research

Projects in our research group are supported by a range of government agencies and partners from academia and industry and have received acclaim for pushing the state-of-the-art in materials characterization. Key elements in the group's approach are:

4D Characterization: 

The development of tomography systems has expanded possibilities for characterizing complex material structures from the micro- to the meso-scale. By taking advantage of the non-destructive nature of tomography, time can be added as a crucial dimension in understanding materials, and models for microstructural development and performance can be updated.

Correlative Analysis:

Material properties are defined by complex relationships between composition, structure, and material history. To analyze these relationships, characterization methods like electron microscopy, micromechanical testing, and x-ray tomography are combined across length scales.

 

We plan to continue answering fundamental questions in the mechanical and corrosion behavior of materials and to increase the accuracy and efficiency of 4D methods by combining them with machine learning and simulation.

Current Projects

Projects which are underway in the group are summarized below and the associated researchers are listed. More information on each is provided in the tabs under "Research" above. Questions about research can be sent through the Contact Us page.

Environmentally-Assisted Fracture in High Performance Metallic Materials

Researchers: Daniel Sinclair, Ankit Kumar

Nonferrous alloys with high strength-to-weight ratios are crucial for aerospace, naval, and energy applications, but the ways in which agressive environments contribute to their mechanical behaviors are poorly understood. Localized corrosion and oxide formation are two key factors in this process, and both are heavily influenced by alloy composition and microstructure as well as variations in environments. Correlative techniques including 4D X-ray Microtomography, nanoindentation, and correlative microscopy are applied to develop new models of corrosion and its effects on the mechanical performance of lightweight alloy systems.

Structural Characterization of Recycled Aluminum Alloys

Researchers: Satyaropp Patnaik, Eshan Ganju

Aluminum is a highly sustainable material for durable and single-use products owing to its high recyclability. Repeated recycling and pressing gradually alters the microstructure, however, and may contribute to degradation of the base material. Through a correlative analysis, key features are measured in X-ray Microtomography and connected to sub-micron compositional imaging. Thus, the effects of repeated processing can be tracked and studied to improve recycling and maximize the reusability of key alloys.

Rare Earth Doped Solders

Researchers: John Wu

Sn-Ag-Cu alloys have replaced lead-containing solders in most electronics applications due to health and environmental concerns. These alloys can be made to be shock resistant and highly ductile through the addition of indium and bismuth, among other rare earth elements. Mechanical behaviors and electromigration are characterized in these solder materials alongside microstructural characterization and simulations of intermetallic formation and In substitution.

Biomimetic Material Structures

Researchers: Rahul Franklin, Nicole Balog

The unique structures of biological materials, such as those found in plant and animal tissues, can inspire those of manmade polymers and composites. By quantifying the structures and mechanical properties of organic materials, lightweight material solutions can be designed and simulated to advance materials for aerospace and other high-performance applications.

Porous and Cellular Materials

Researchers: Eshan Ganju, Ankit Kumar

Porous structures offer unique physical and mechanical properties, largely being selected for applications requiring weight reduction or impact resistance. Additionally, these structures are applied for a wide range of materials systems. Here, 3D visualization and quantification are applied to polymer foams and porous titanium to understand their structures and their time-resolved responses to compression.

Novel Neural Architectures for 4D Materials Science

Researchers: Eshan Ganju, Daniel Sinclair

Convolutional Neural Networks (CNN) and other modern machine learning algorithms provide a method for the rapid processing and analysis of raw materials data. In this NSF AI Institute Planning Grant, they are applied to automate the filtering and segmentation of tomography data to accelerate throughput and develop physics models for material behavior. Learn about the projects this planning grant will be joining at the NSF website here

Technology Security

Researchers: Min-Woo Cho, Eshan Ganju

Given the global reach of computer manufacturing and supply chains, there is a steadily increasing incidence of counterfit electronic chips. This endangers consumer-level product reliability as well as the security of information on a personal and national level. Fingerprinting, whereby packages are marked with a unique and inimitable pattern, offers one way to prevent counterfits from entering the supply chain. Three-dimensional fingerprinting methods are being explored with the help of X-ray tomography systems.

Advanced Processing of Metallic Materials

Researchers: Daniel Sinclair, Eshan Ganju, Poonchezhian Vishnu Prakash

The failure of steel weld joints under tensile and tensile-fatigue conditions is assessed to understand the microstructural origins of failure and the impacts of shot peening as a surface-smoothing technique.

Meteorite Mechanics

Researchers: Tai-Jan Huang

Meteorites provide a precious opportunity to examine the formation and properties of meteors and asteroids in our solar system; however, established relations between the microstructure and mechanical properties of meteorites are currently lacking. By correlating microscopy, XRT, and nanohardness data, the structures in a meteorite fragment can be thoroughly probed and used to inform simulations and studies of meteor formation.