Stanford Researchers Achieve Breakthrough in Quantifying Energy Costs at the Nanoscale
New research published February 9th in Nature Physics offers a novel method for measuring energy dissipation in quantum systems, paving the way for more efficient and faster computing devices.
The quest to build the computers and devices of tomorrow hinges on a fundamental understanding of how energy is used today. This seemingly simple challenge is surprisingly complex, as modern technologies involve constant energy flow and never reach a state of thermodynamic balance. Now, a team at Stanford University has developed a groundbreaking approach to quantify energy costs during these dynamic processes with unprecedented sensitivity, focusing on the realm of quantum mechanics.
Unveiling Energy Costs with Quantum Dots
Researchers combined theoretical modeling, rigorous experimentation, and advanced machine learning techniques to achieve this breakthrough. Their work centers on extremely small nanocrystals known as quantum dots, which exhibit unique light-emitting properties stemming from quantum effects at the nanoscale. By meticulously measuring the entropy production of these quantum dots – a metric that reveals the reversibility of a microscopic process and encodes information about memory, information loss, and energy expenditure – the team gained insights into the ultimate speed and efficiency limits of devices.
“When I first saw this work, they really had to convince me that they were measuring the thing that they said they were measuring because it’s an incredibly hard thing to do,” noted a leading chemist involved in the study.
The implications extend to a wide range of materials and devices that undergo rapid structural changes at the atomic level. Improved measurements of the interplay between memory, information, and energy dissipation could unlock new possibilities for enhancing energy efficiency, stability, and speed in future technologies.
The Non-Equilibrium World and the Challenge of Measurement
The research acknowledges that the world around us is inherently non-equilibrium – from weather patterns and living organisms to the materials and devices we create. “No one has ever been able to measure things like entropy production in one of these real material systems. That’s the fundamental thing that our paper achieves,” explained Aaron Lindenberg, professor of materials science and engineering at Stanford and SLAC National Accelerator Laboratory, and the paper’s senior author.
Traditionally, measuring efficiency is straightforward in classical thermodynamics, like with an engine. However, these established tools become inadequate when applied to the nanoscale. “There is a lot of work thinking about what happens when you shrink systems down. How do fluctuations play a role? How should we define all of the quantities? There’s a big gap between what we can do theoretically and what can be done experimentally,” said a researcher. “This work is a significant step toward closing that gap for a specific class of systems, and for understanding efficiency in particular.”
Bridging Theory and Experiment with Machine Learning
The team’s innovative approach involved inducing a non-equilibrium state in the quantum dots by modulating their blinking with a laser field. As explained by Yuejun Shen, the lead author and a graduate student in the Lindenberg lab, “When the field is off, the blinking of a quantum dot follows a certain statistical blinking pattern. When the field is on, there’s another statistical pattern. This is how we induce the non-equilibrium state and it is how we make the experiment represent information dissipation.”
Following data acquisition, machine learning algorithms were employed to refine the parameters of a physics-based model, enabling the precise calculation of entropy production. This combination of experimental data and computational modeling represents a significant advancement in the field.
[Video showing the blinking quantum dots from the experiment. The researchers turned a laser field on and off to drive them far from equilibrium and modulate their blinking. | Shen, Y., Chen, C., Ma, H., et al. “Non-equilibrium entropy production and information dissipation in a non-Markovian quantum dot.” Nat. Phys. (2026), https://doi.org/10.1038/s41567-026-03177-8]
A Foundation for Future Innovation
This research builds upon recent advancements in computation, measurement, data analysis, and theoretical physics. The researchers emphasize that the computational power and analytical techniques required for this work were not readily available even a decade ago. “Conceptually, I’m not sure that the question could have been formulated as clearly 10 years ago,” one researcher commented.
Looking ahead, the team anticipates that their technique can be further refined and applied to a broader range of systems. “If you can measure energy dissipation within driven, non-equilibrium systems directly, you can start to explore different pathways to search for optimal ways to improve the process, like searching for a device that operates using less energy or is faster,” Lindenberg stated. “It is a problem of important technological relevance.” By starting with a complex, small system, the researchers hope to lay the groundwork for the development of devices that are both more energy-efficient and operate at higher speeds across various scales and complexities.
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