Vienna, August 7, 2025 — A research team led by Andrej Pustogow from the Institute of Solid State Physics at TU Wien has successfully predicted and synthesized a new class of thermoelectric materials using a computer-based protocol, bypassing the traditional trial-and-error approach. Their work, recently published in Science Advances, demonstrates how computational methods can lead directly to application-ready materials, potentially accelerating the development of energy-efficient technologies.
Thermoelectric materials, which convert heat into electricity, have long been researched—traditionally focusing on semiconductors. But despite nearly a century of investigation, their widespread application remains limited. “After decades of focusing on semiconductors, it was time for a fresh approach,” said Pustogow.
Instead of testing endless combinations in the lab, the team harnessed supercomputer simulations to narrow down the periodic table to a targeted set of transition metal compounds, beginning with nickel, iron, and cobalt. They then evaluated each compound’s suitability for thermoelectric use. This strategy led them to Ni₃Sn (nickel-tin) and Ni₃Ge (nickel-germanium) as promising candidates.
While nickel-tin occurs naturally as the mineral nisnite, it is difficult to synthesize in standard lab settings. The team focused instead on Ni₃Ge, which they were able to successfully synthesize and test, confirming its excellent thermoelectric properties.
Fabian Garmroudi, first author of the study, emphasized the importance of moving beyond outdated textbook assumptions. “In thermoelectricity, many materials were ignored for decades based on early theoretical suggestions. Our research proves that even simple binary alloys can outperform complex systems when chosen intelligently.”
The automated protocol used for this discovery not only streamlines material selection but also saves time and resources, providing a blueprint for discovering future materials with custom properties. The team now aims to expand their method to even more complex combinations involving three or more elements.
The research also highlights the growing importance of artificial intelligence and data-driven approaches in materials science—techniques already being used by major tech firms like Google and Microsoft. Yet, as Garmroudi notes, human insight remains vital: “The best outcomes still come from combining human creativity with computational power.”
Source: TU Wien
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