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This project, funded by Office of Naval Research, is aimed to design a new near-α Titanium alloy for naval structural applications with both the high strength of Ti-64 and the high fracture toughness of Ti-5111. In order to enhance strength and fracture toughness simultaneously, transformation-induced plasticity (TRIP) effect was used. A new generation of TRIP toughened near-α Ti alloy Ti-8111Fe, meeting predicted strength with required phase stability and transformation dilatancy, was computationally designed. Mechanistic models on the thermodynamics and kinetics of martensitic transformation in titanium alloys were built and applied to calculate the characteristic MSσ temperatures defining the β phase stability at the stress states of uniaxial tension (ut) and crack tip (ct). Martensitic transformation dilatation was calculated from room temperature molar volume database developed for β, α’and α” phases. The model predictions of transformation kinetics, transformation dilatancy and associated toughening behavior are being experimentally tested.

This project is focused on designing fatigue resistant shape memory alloys (SMAs) for biomedical devices. This research combines analytical techniques such as Atom Probe Tomography to measure phase relations and particle size evolution during ageing with other experimental techniques such as differential scanning calorimetry (DSC) and mechanical testing to measure transformation temperature, strength, and cyclic transformation stability. Experimentally calibrated models combined with CALPHAD-based simulations allow for predictive design of optimally-strengthened superelastic alloys. Besides, processing design is taken to optimize the inclusion morphology and to decrease the inclusion size according to the finite element analysis results.

SHAPE MEMORY ALLOYS
TRIP TITANIUM ALLOYS

The projects mentioned below are currently being researched by individual graduate students in the group.

CURRENT PROJECTS

Nick Wengrenovich designs blast and fragment resistant TRIP (transformation induced plasticity) steels for structural components on naval warships, specifically focusing on extending the adiabatic shear instability strain to prevent the plugging phenomenon during fragment impact. In order to achieve the high strength required for this application (minimally 120 ksi / 827 MPa), he studies and models the evolution of nanoscale gamma prime precipitates. To prevent the plugging phenomenon, he performs experiments to determine optimized TRIP which significantly delays plastic instability in both tension and shear stress states, thus extending the uniform shear deformation which delays the onset of localization and the plugging mode of failure. The goal of the research is to bring together experimentally optimized austenite stability, service use requirements, and calibrated parametric models to computationally design the next generation high performance steels for blast and fragment protection.

BLAST PROTECTION STEELS

Automotive manufacturers have progressively focused on the development of lightweight Al-alloys over traditional cast Fe-based alloys for applications in vehicle components such as engine cylinder heads. In addition to reducing vehicle weight, there is a strong push to increase engine operating temperature, thereby improving fuel efficiency. This poses a significant engineering challenge, as the mechanical properties of conventional Al-alloys degrade above 200°C due to rapid coarsening of strengthening precipitates. The high temperatures and pressures to which engine cylinder heads are exposed during extended periods of operation can induce failure by low cycle fatigue as well as high-cycle thermomechanical fatigue. There is a clear need for a relatively low-cost Al-alloy composition with superior strength and fatigue resistance above 200°C, but that retains the favorable properties of conventional Al-alloys, such as density, castability, and elongation.

Integrated Computational Materials Engineering (ICME) tools are used to design a high-temperature fatigue resistant Al-alloy for use in lightweight vehicles. Designing for both macro-scale properties and multi-scale material structures down to the atomic scale over large time domains requires the use of experimental data (APT, TEM), atomistic simulations (DFT), and precipitation kinetic modeling (PrecipiCalc). Integrating predictive modeling enables long time scale property projections for applications in high-temperature high-efficient engine operating environments.

ALUMINUM ALLOYS

Quench and partitioning (Q&P) in steels is a new processing concept for development of multiphase steels (third generation advanced high strength steels (AHSS)) with improved mechanical properties and cost efficiency. The process involves quenching the material from a purely austenitic phase region to a temperature (quench temperature, QT) below the martensite start temperature and then reheating it at a higher temperature (partitioning temperature, PT) to facilitate carbon partitioning to austenite and thus improving its stability. The microstructure consists of martensite and carbon enriched austenite that provides better strength and formability via the transformation induced plasticity (TRIP) effect.

 

The objective of the project is to determine an optimized combination of alloy composition and processing parameters for Q&P cycles to have the best possible combination of mechanical properties. It also aims at understanding the mechanisms at work at different stages of the Q&P process and their influence on the final alloy performance.  

QUENCH AND PARTITION STEELS

My current PhD project is ‘Development and Validation of Physics-Based AM Models for Process Control and Quality Assurance’, in collaboration with NIU, QCML and Northwestern groups. Under the supervision of Prof. Greg Olson, I am mainly responsible for materials characterizations, relationships of microstructures and processing parameters, thermodynamic and kinetic modellings, and 3D tomography analysis of additive manufactured materials, such as 316L stainless steel and Ti-6Al-4V alloy. The technology of additive manufacturing (AM), which can build complex-shaped 3D objects layer-by-layer, may have revolutionized the manufacturing industry. This technology has been around for decades, but to commercialize it in metals, there are still underlying problems, including the assurance of the repeatable and reliable results. Up to date, there have not been complete and profound integrated physical understandings of the 

relationships among AM process parameters, microstructures, mechanical and properties, as well as of the thermal histories that the materials experience during the processing.

ADDITIVE MANUFACTURING
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