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By Elizabeth Egan

“I am honored and humbled to be a part of the Forbes 30 Under 30 Asia, Healthcare and Science, Class of 2025,” said Peng. “I am grateful for the support I have received from my mentors and colleagues, and I look forward to growing as a scholar and educator at the School of Engineering and Applied Sciences.”

The list showcases the achievements of talented individuals across multiple categories who are under the age of 30. Peng uses data science, machine learning, and materials physics to discover novel materials, and his research has been published in Advanced Materials and Nature Materials, receiving almost 3,000 citations over the past five years.

Peng believes the work he has done in helping to electrify key industrial sectors made him stand out for the recognition.

“Electrifying key industrial sectors, including chemical and materials industries, as well as transportation and aviation, is a pressing mission of our time,” said Peng. “It is crucial to develop technologies powered by materials that can drive key chemical transformations at a capacity exceeding megawatts and maintain performance over thousands of hours of operation.”

Peng said that understanding and optimizing materials and interfaces are essential to building such technologies and that unprecedented materials are needed, but current state-of-the-art materials with the necessary capabilities are not yet optimal.

To address this, Peng has worked at the forefront of building a joint computational–experimental approach to accelerate catalyst materials design with the use of first-principles atomistic simulations, synchrotron X-ray spectroscopies, and physics-inspired machine learning. Peng said that his work has specifically focused on exploring how to systematically understand, control, and engineer catalyst materials on the atomic scale to realize optimal activity and stability for energy technologies.

“My work provides a physically meaningful framework with quantitative predictive power for accelerating materials design to combat the most critical societal challenges in chemical transformation and energy technologies,” said Peng.

While pursuing his undergraduate degree in applied physics at the University of Science and Technology of China, Peng became interested in materials science and engineering due to his fascination with the simple principles that connect microscopic particles in materials with other categories of macroscopic physical and chemical properties.

This interest led him to pursue a PhD in materials science and engineering at the Massachusetts Institute of Technology and then continue there for two years as a postdoctoral associate before joining the University at Buffalo as an assistant professor in January.

“Within the five years of my PhD, I discovered similarly elegant design principles that bridge the fundamental states of atoms and electrons in catalyst materials with their reactivity and durability for making chemicals and fuels and producing electricity,” said Peng. “This can serve as an essential guiding physical rule with quantitative predictive power for understanding, controlling, and engineering new materials for critical applications of chemical transformation and energy technologies that can significantly benefit society.”

During his postdoctoral research, Peng said he further incorporated this physics-driven framework for materials design with data science and machine learning. His work aimed to accelerate the optimization of new materials with complicated atomic structures and chemical compositions to be efficiently and thoroughly studied by traditional computational or experimental approaches.

“As I have just begun my independent career and developed my own research group as an assistant professor, I am determined to continue this path to bridge physics-informed and data-driven materials design for catalyzing further scientific innovations in chemical transformation and energy technologies,” said Peng.