Research

Open Ph.D. and M.S. Positions

The Titus group currently has one or two open Ph.D. / M.S. positions. Please contact Prof. Titus (titus9@purdue.edu) for more information. All projects are fully-supported.

*1) Machine-learning design of oxidation-resistant refractory complex, concentrated alloys: As part of a multidisciplinary effort, we are developing a machine-learning and sequential acquisition framework to design new refractory complex, concentrated alloys (high entropy alloys) that form a protective alumina scale at high temperatures. This position will combine high-throughput experimental methods to rapidly fabricate new alloys with high-throughput thermodynamic calculations to accelerate oxidation screening methods for new alloys. This position will be co-advised by Profs. Titus and Sandhage.

2) First-principles modeling and validation of solute segregation to planar defects in NiCo-based superalloys: This effort will utilize a combination of first-principles calculations, Bayesian inference methods, and high-resolution experimental techniques to predict and quantify solute segregation to planar defects. This information will be used to develop future alloy design strategies and enhance creep properties of high temperature superalloys.

Students must apply to the MSE program to be formally considered. Apply at: https://www.purdue.edu/gradschool/admissions/how-to-apply/index.html

*For Purdue Military Research Initiative students, the first project listed above has positions available for both M.S. and Ph.D. applications. This project encompasses materials used for high temperature applications, including potentially hypersonic applications.

Current Research Activities

Solute-enhanced interfaces in NiCo-based alloys (NSF CAREER)

High-resolution scanning transmission electron micrograph with overlaid energy dispersive X-ray spectroscopy showing segregation of W and Ta to a stacking fault (SISF).

Solute in solid-solution alloys are able to segregate to interfaces to decrease the overall energy of the system. Examples of interfaces include: grain boundaries, phase interfaces, twin boundaries, and stacking faults. This work focuses solute segregation to twin boundaries and stacking faults, in particular, and we seek to understand how solue segregation affects the mechanical behavior of high temperature structural alloys. We utilize a combination of first-principles calculations, statistical mechanics, and advanced electron microscopy to (1) predict the equilibrium composition at stacking faults and twin boundaries, (2) calculate the segregated stacking fault and twin boundary energies, (3) and predict the mecahnical behavior response of dislocations in the vicinity of segregated stacking faults and twins.

Accelerated design of oxidation-resistant refractory complex, concentrated alloys via a machine learning-sequential acquisition framework (NSF DMREF)

In 2004, two researchers independently introduced a new concept in alloy design: high entropy alloys. These alloys are not based one or two elements (e.g. Ni-based, Fe-based, Ti-based) but are instead composed of four or more alloy components in roughly equi-molar portions. The concept of concentrated complex alloys (CCAs) simply lifts the restriction for equimolar compositions and thus widely opens available composition space for researchers to explore. This composition space spans thousands of unique alloy systems and hundreds of thousands, if not millions, of distinct alloy compositions. For example, if we wish to make a four-component alloy and want to consider elements like Al, Si, Ti, V, Cr, Zr, Nb, Mo, Ru, Hf, Ta, W, and Re, there are 715 unique four-component alloy systems available for us to investigate, and each system contains tens of thousands unique compositions. The possibilities are endless, and the work is daunting. In this work, we are utilizing a machine learning accelerated materials discovery approach to designing new refractory-based CCAs with high oxidation resistance through the formation of a dense, external scale of alpha-Al₂O₃.

Role of second phases in martensitic materials (DOE BES)

Martensitic transformations in alloys enable a wide range of engineering materials to be realized with properties that include shape memory, superelasticity, and of course strengthening in steels. Shape memory, or the ability for a material to return to its initial shape after deformation, is a well-studied phenomenon, and the effect is utilized in commercial products ranging from transportation, medical, to telecommunication. However, martensitic transformations can be further exploited and tuned via the introduction of coherent second phases that enable ultra-high cycle fatigue resistance, ultra-low stiffness, and modification of martensitic transformation temperatures. In this project, we seek to understand the role of coherent secondary phases in martensitic materials via a synergistic combination of atomistic simulations and experiments which relate the local properties of each phase and material nanostructure to the overall materias response. We aim to achieve second order martensitic transformations in shape memory alloys, ultra-low stiffness, increased control of martensitic/austenite transformation temperatures, and increased fatigue resistance.

Deformation Mechanisms in HAYNES® 244® (Haynes International)

HAYNES® 244® alloy was invented by Haynes International and patented on October 1^st, 2013. While the alloy’s application relevant properties (coefficient of thermal expansion, tensile strength, creep resistance, fatigue, and oxidation resistance) have been characterized, the precise origin of the alloy’s remarkable high temperature strength has not been established. Studies suggest that the strengthening phase is the same type of Ni₂(Cr, Mo) intermetallic phase that strengthens HAYNES® 242® alloy (nominal composition Ni-8Cr-25Mo). This project focuses on determining the deformation mechanisms both at room and elevated temperatures and key microstructural characteristics that control the tensile and creep strength. To elucidate the deformation behavior, we utilize first-principles calculations, conduct quasi-static mechanical tests, conduct elevated temperature creep tests, and analyze specimens samples using advanced X-ray-based techniques and electron microscopy.