Materials Design to Present Predictive Multiscale Nuclear Materials Research at GE Vernova Materials Frontiers Symposium

Materials Design, Inc. will participate in the upcoming GE Vernova Materials Frontiers Symposium, taking place June 2-4 at the GE Vernova Advanced Research Center. The event brings together leaders in materials science, advanced simulation, energy technologies, and industrial research to discuss emerging innovations shaping the future of materials development.

Representing Materials Design at the symposium will be Kyle Starkey and Naida Lacevic, who will also host a vendor table featuring company materials, technical datasheets, and showcasing of Materials Design’s computational materials science capabilities.

As part of the technical program, Kyle Starkey will present new research demonstrating a predictive multiscale modeling framework for zirconium corrosion in nuclear reactor environments. The work integrates first-principles calculations, machine-learned interatomic potentials, molecular dynamics, and continuum phase-field modeling to better understand the degradation mechanisms affecting zirconium alloy cladding in light water reactors.

The research highlights how physics-based, machine learning-enhanced simulations can reproduce experimentally observed oxide microstructures and stress evolution without empirical fitting to microstructural data. The approach represents an important step toward accelerated qualification and prediction of materials behavior in extreme environments.

Presentation

MULTISCALE MODELING OF ZIRCONIUM CORROSION: FROM MACHINE-LEARNED ATOMISTICS TO PREDICTIVE OXIDE MICROSTRUCTURES

K. Starkey1*, L. Kahle1, M. Christensen1, V. Eyert1, A. El-Azab2, C. B. Geller1, A. Shivprasad3, and E. Wimmer1

1. Materials Design, Inc., San Diego, CA, USA

2. School of Materials Engineering, Purdue University, West Lafayette, IN, USA

3. Electric Power Research Institute, 1300 W. W.T. Harris Blvd, Charlotte, NC, USA

   *Presenter Email: kstarkey@materialsdesign.com

Abstract

Corrosion of zirconium alloy cladding limits the lifetime of light water reactor fuel. The mechanistic origins of the columnar oxide microstructure, the undulatory metal/oxide interface, and the stress state driving oxide cracking remain incompletely resolved. We present a first-principles-informed multiscale framework that predicts these features without empirical adjustment to microstructural data.

The workflow combines density functional theory of ZrOx properties, molecular dynamics with a DFT-trained machine-learned interatomic potential, and a multiphase phase-field model resolving heterogeneous grain nucleation, growth, and elastic coupling. Atomistic free energies, interfacial energies, diffusivities, and elastic constants pass directly into the continuum description.

Simulated microstructures reproduce the columnar grain morphology and grain size distributions seen in transmission electron micrographs of oxidized Zr. A hexagonal ZrO sublayer adjacent to the α-Zr/ZrO2−x interface emerges from continuous heterogeneous nucleation and grain boundary transport. The interface develops the experimentally observed undulation, and local tensile stresses at regions of curvature, despite an overall compressive film, provide plausible initiation sites for the cyclic corrosion transition.

The DFT–MLP–continuum chain delivers predictive, microstructure-resolved models of nuclear materials degradation and points to ML-accelerated qualification of materials in extreme environments.

Presenter Bio

Kyle Starkey is a researcher at Materials Design, Inc., where his work focuses on multiscale computational modeling, machine-learned interatomic potentials, and predictive simulations of materials behavior in extreme environments. His research integrates density functional theory, molecular dynamics, and continuum-scale modeling approaches to accelerate materials development and improve understanding of degradation mechanisms in energy and nuclear systems.

Materials Design’s participation in the GE Vernova Materials Frontiers Symposium reflects the company’s continued commitment to advancing integrated computational materials engineering and AI-enabled scientific discovery for energy, aerospace, electronics, and advanced manufacturing applications.

Attendees are encouraged to visit the Materials Design vendor table during the symposium to learn more about the company’s software platforms, simulation technologies, and collaborative research capabilities.