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RASEI Fellow Steven Spurgeon has been awarded the Burton Medal for his work harnessing AI and Machine Learning to accelerate the study of the microscopic world of energy materials

By Tara McMurty | Adapted from an

National Renewable Energy Laboratory (NREL) materials data scientist and RASEI Fellow����has been honored with the Microscopy Society of America’s (MSA’s) Burton Medal award. The award, which is given annually to a single physical sciences researcher under the age of 40, is the highest honor the MSA bestows upon early-career scientists in the field of microscopy and microanalysis.

“I’ve been involved with the MSA for 15 years and have been fortunate to work with amazing leaders in the field of microscopy,” Spurgeon said. “To be recognized with this award and join their ranks is a true honor.”

Throughout his career, Spurgeon has pioneered the integration of machine learning (ML) with electron microscopy, using artificial intelligence (AI), to help make sense of the detailed images generated by electron microscopes. This approach not only dramatically enhances the efficiency of microscopy techniques; it also provides new insights into the behavior of functional materials—like silicon microprocessors used in computers and cell phones—at the atomic level. These insights enable researchers to fine-tune material properties and enhance efficiency to drive advancements in energy solutions.

“Dr. Spurgeon’s pioneering work at the intersection of AI and microscopy continues to transform materials science,” said Katherine Jungjohann, who manages NREL’s Analytical Microscopy and Imaging Science group. “His visionary leadership and groundbreaking research make him a truly deserving recipient of the Burton Medal.”

Spurgeon’s journey to the AI/microscopy frontier began with a deep curiosity about the fundamental building blocks of matter. As a graduate student at Drexel University, he studied materials science and engineering, focusing on developing new functional materials. After Spurgeon completed his Ph.D., he joined Pacific Northwest National Laboratory (PNNL), first as a postdoctoral research associate, and later as a staff scientist in the laboratory’s longstanding thin-film Basic Energy Sciences program. At PNNL, he developed new functional materials that could be used for energy storage and computing, which was recognized by the PNNL Laboratory Director’s Award for Early Career Achievement. He also had a realization that would shape the trajectory of his career.

AI-powered tools like transformers—which is what the “T” in ChatGPT stands for—began to emerge in the scientific community about 10 years ago and were used in areas like processing internet data and building autonomous vehicles. Watching the rise of these ML tools, Spurgeon began to wonder if they could benefit his own field of work.

“I realized we were collecting and analyzing all our data by hand,” Spurgeon recalled. “That made me ask, ‘Can we use AI to accelerate our experiments so that humans don’t have to make every single decision?’ I saw that machine learning could help us analyze larger datasets, uncover patterns that would be difficult to detect manually, and ultimately shorten the time to discovery.”

Inspired by these possibilities, Spurgeon helped launch an AI initiative at PNNL and established a groundbreaking partnership with industry to design a completely new AI-infused microscope. His efforts led to the development of the��, a platform that leverages AI to improve the way researchers study and understand functional materials. The platform, which enables researchers to conduct analyses up to 1,000 times faster than traditional methods, earned Spurgeon and his team an R&D 100 Award in 2024.

“During his time at PNNL, Dr. Spurgeon rapidly ascended to international prominence in AI-guided materials science and electron microscopy,” said Sergei Kalinin, chief scientist of Physics-Informed Machine Learning at PNNL. “He established himself as a brilliant researcher, a staunch advocate for our field, and an exceptional mentor, and he continues this reputation today.”

After nearly 10 years at PNNL, Spurgeon joined NREL’s Material Science team in May 2024 with a mission to lead research on autonomous materials science and characterization in the development of new energy technologies.

“I joined NREL to help establish a forward-thinking vision for autonomous science,” Spurgeon said. “NREL's leadership in emerging energy technologies, coupled with its proactive approach to integrating AI, creates an environment like no other, where researchers can strategically innovate and push the boundaries of energy solutions.”

Since joining NREL, Spurgeon has integrated autonomous capabilities into lab workflows, established new industry partnerships, and created effective teams. In May 2025, he is����to convene leading experts to explore practical, real-world applications of autonomous research.

His work has sped up experiments and led to faster discoveries in energy materials and microelectronics, which translates to tangible benefits for NREL’s partners and the wider community. Moving forward, he is focused on using AI to develop important materials—like advanced semiconductors and catalysts—that could lead to major breakthroughs in technology.

As Spurgeon explained, “AI-driven autonomy in materials science is the key to breaking through current research bottlenecks. It allows us to move beyond incremental improvements and achieve truly transformative discoveries in the energy materials we use every day, saving money and improving resilience.”

Reflecting on his career, Spurgeon identified the thrill of discovery, bolstered by persistence in the face of failure, as a driving factor in all that he has achieved.

“Breakthroughs don’t come easily. They often follow many, many failures,” Spurgeon said. “But every once in a while, you get a new process to work or you uncover a phenomenon no one has seen before. Those moments of seeing something for the first time—something no one else has seen—are what make me come to work every day.”

Beyond the personal satisfaction of pushing the boundaries of knowledge, Spurgeon finds inspiration in the support of the scientific community and in the impact of his work on real-world technologies.

“When you’re all pushing in the same direction, you can help each other, share in the struggles, and celebrate the wins,” Spurgeon said. “It has been especially rewarding to work with so many talented early-career staff and students over the years.”

Spurgeon also recognizes that the focus of his work—AI integration—has been the subject of a fair amount of debate in recent years.

“We're at the start of a significant transformation in science, but the essence of the scientific process—generating and testing a hypothesis—still belongs to humans,” Spurgeon said. “AI can help us analyze more data and refine our decision-making, but it’s still on us as scientists to take responsibility for our conclusions.”

With this in mind, Spurgeon emphasizes the importance of building practical, trustworthy AI implementations whose conclusions can be clearly explained and that provide real value for users.

Looking ahead, Spurgeon is optimistic: “The future of materials science lies in the collaborative power of AI and human ingenuity. Together, we'll push the boundaries of innovation and improve the lives of everyone around the world.”