Joe Gauthier will use computational tools to tackle a key barrier in water-splitting technology: the costly breakdown of catalyst materials.
Hydrogen plays an indispensable role in modern industry. It is a starting material for refining fuels, synthesizing plastics, and producing the fertilizers that sustain global agriculture. Yet the dominant method of making hydrogen, steam reforming natural gas, has a significant carbon footprint. Water electrolysis, which splits water into hydrogen and oxygen using electricity, offers a cleaner path forward, but its widespread adoption has been held back by a stubborn materials problem.
Joe Gauthier, an assistant professor in the Department of Chemical Engineering at Texas Tech University, has received a National Science Foundation CAREER Award to confront that problem head-on. The five-year grant will support a research program aimed at understanding why the catalyst materials inside water-splitting devices corrode under operating conditions, and how to engineer replacements from Earth-abundant elements that can withstand the punishment.
The CAREER Award is a prestigious recognition for early-career faculty who demonstrate exceptional promises as both scholars and educators.
A Durability Puzzle at the Atomic Scale
At the heart of every water electrolyzer is a pair of electrodes. The oxygen-producing side, the anode, operates under particularly harsh electrochemical conditions, and the best-performing anode catalysts today rely on iridium and other platinum-group metals that are among the scarcest elements on Earth. Over time, even these premium materials dissolve and degrade, eroding device performance and driving up costs.
“We know these catalysts degrade over time, but the atomic-level details of how and why that happens are still surprisingly unclear,” Joe said. “If we can map out the degradation pathways with the same level of detail and understanding we have for the catalytic reaction itself, we can open the door to designing cheaper materials that last far longer.”
The project will deploy machine-learning-accelerated quantum-mechanical simulations to model both the desired oxygen-evolution reaction and the unwanted corrosion processes occurring at the catalyst surface. By benchmarking these calculations against experimental data, the team aims to build a predictive framework that links a material’s catalytic activity to its long-term stability – two properties that have historically been difficult to optimize simultaneously.
Closing a Gap in How Simulations Are Tested
A distinctive thread of the project tackles a deeper methodological challenge that affects the entire field of computational electrochemistry. Researchers routinely use quantum-mechanical simulations – specifically, density functional theory, or DFT – to predict how reactions unfold on electrode surfaces. But unlike related areas of catalysis where high-quality experimental benchmarks are abundant, electrochemistry has a benchmarking blind spot: there is currently no reliable way to compare DFT predictions of elementary charge-transfer steps to experiment.
The root of the problem, Joe explains, is that measuring the activation energy of a single electrochemical reaction step, say, a proton and an electron transferring to a surface, is extraordinarily difficult in the presence of a liquid electrolyte. Without those measurements, modelers have little ground truth to calibrate against.
“In thermal catalysis, decades of careful surface-science experiments gave theorists clear targets to aim at,” Joe said. “In electrochemistry, we’ve been flying blind. This project aims to help change that by introducing ion solvation energies, quantities we can measure accurately, as a new metric for evaluating simulations of charge-transfer processes.”
Preliminary results from Joe’s group suggest the stakes are high. The team’s early calculations suggest that the typical modeling approach, consisting of surrounding a reacting ion with just two to four water molecules in a simulation, is likely insufficient to capture the physics correctly. Increasing the size of this solvation shell and testing multiple levels of theory against known experimental values reveals significant and sometimes surprising errors, particularly for the kinds of multivalent ions that form when a metal oxide corrodes.
By systematically mapping where these errors come from and how to correct them, the project aims to establish best practices that the broader community can adopt – not only for corrosion modeling, but for any electrochemical process where reaction speed matters, from hydrogen production to carbon dioxide conversion to battery cycling.
From Scarce Metals to Sustainable Alternatives
Armed with improved modeling tools, Joe’s group will screen families of oxide catalysts composed of common, inexpensive elements for combinations that strike a better balance between performance and durability. The long-term vision is a new generation of anode materials that could make electrolyzers cheaper and more practical, accelerating the shift toward hydrogen produced with renewable electricity rather than fossil fuels.
“Reducing our dependence on scarce metals is directly tied to whether hydrogen produced by water electrolysis will ever compete economically with conventional production methods, and that has real consequences for energy security and the climate,” Joe said.
“Joe brings a rare combination of computational depth and practical vision to this challenge,” said Rajesh Khare, chair of the department of chemical engineering. “This award reflects his potential to reshape how the field thinks about catalyst design for clean-energy technologies.”
Cultivating the Next Generation of Computational Scientists
The award also funds two education and outreach initiatives woven into the research plan. The first is a new project-based undergraduate course in computational materials science. Because no single major fully prepares students for this inherently interdisciplinary field, the course is designed to give undergraduates hands-on experience bridging chemistry, physics, and computing – skills increasingly in demand across academia and industry.
The second initiative targets middle-school students in rural West Texas, where access to STEM enrichment opportunities can be limited. Through interactive workshops and demonstrations, the program aims to spark curiosity about science and engineering while broadening the pipeline of students who see themselves in research careers.
“The students we reach today are the ones who will push this science forward tomorrow,” Joe said. “I want to make sure the path into computational research feels welcoming and achievable, especially for folks who might not have a centralized compute facility down the street.”
The NSF CAREER Award for the project “Engineering Earth-abundant and corrosion-resistant water oxidation electrocatalysts” will support five years of research and education at Texas Tech University.