Kathryn Chain
University of Nebraska
email:kchain@unomaha.edu
TAMU mentor: Michael Dimitriyev
Project Title: Prototyping inhomogeneous swelling responses in polymer gel systems via a linear elastic model
Jesse Contreras
Oregon State University
email:contreje@oregonstate.edu
LANL mentor: Khanh Dang
Project Title: Investigating Mechanical Properties of Li-Alloys for Application in Solid-State Batteries
Emily Dunn
Duke University
email: emily.dunn@duke.edu
TAMU mentor: Jean-Briac le Graverend
Project Title: Bimodal Microstructures in Ni-based Single-crystal Superalloys subjected to Non-isothermal Loading via Phase-field Method
Landon Ellis
Oklahoma Christian University
email: landon.ellis@eagles.oc.edu
TAMU mentor: Don Lipkin
Project Title: Extracting Thermal Diffusivity During High-Heat Flux Testing
Ryan Le
Texas A&M University
email:ryanmle@tamu.edu
LANL mentors: John Bernardin & Jacob Mingear
TAMU mentor: Darren Hartl
Project Title: Advanced Modeling of Shape Memory Alloy Applications
Kayla Levy
Texas A&M University
email:klevy@tamu.edu
TAMU mentor: David Eckman
Project Title: A Julia Package for Plausible Inference Methods
Jackson Martin
Texas A&M University
email:martijb02@tamu.edu
TAMU mentor: Michael J. Demkowicz
Project Title: Nickel Dissolution and Hydrogen Uptakes in Different Electrolytes
Trevont Moore
Oral Roberts University
email:mooretre@oru.edu
TAMU mentor: Raymundo Arroyave
Project Title: Gradient-based Discovery of Initial Feasible Solutions for Inverse Materials Design
Mikayla Obrist
Penn State University
email:mao5591@psu.edu
TAMU mentor: Raymundo Arroyave
Project Title: Identifying Suitable Subgraphs for Design of Compositionally Graded Alloys
(CGAs)
Gabriela Polakovic
Boston University
email: gabypol1@bu.edu
LANL mentor: Bernard Gaskey
Project Title: 3D Apples and Oranges: Comparing Residual Stress and Distortion Modeling for Metal Additive Manufacturing
Jason Richards
University of Rochester
email: jricha48@u.rochester.edu
LANL mentor: Anup Pandey
Project Title: Optimizing He Dopants in Nuclear Materials through Machine Learning Interatomic Potential