Title: Building next generation analog computers: physics, materials, and systems
When: Friday 20th March 2026 at 12.00
Where: Sala de Grados, Modulo 8, Facultad de Ciencias, UAM (01.08.SS.202)
Speaker: Prof. Elliot Fuller, Principal Scientist, Sandia National Laboratories, Materials Physics Department
Abstract: Artificial intelligence is pushing the limits of digital computing to such an extent that, if current trends continue, global energy consumption from computation alone would surpass all other forms of energy in the next decade1. With the ending of Dennard scaling and Moore’s Law, silicon transistor technology has nearly reached its physical limits, and further efficiency gains are mostly achievable through architectural or algorithmic innovations. Consequently, it is crucial to explore new strategies that can reduce energy consumption and increase computational speed to meet growing demands. One promising approach is in-memory analog computing, which has the potential to deliver significant improvements in both efficiency and speed. However, designing analog computing systems presents considerable challenges. First, analog computing necessitates a fundamental rethinking of computation at the physics and materials level, where information is now stored as continuously variable observables. This shift introduces difficulties related to the accuracy, dynamic range, and reliability of analog systems—issues that prompted the transition to digital computing nearly a century ago. I will address strategies for overcoming these challenges in the context of developing materials and devices for resistive synaptic memory2,3. Second, digital computation has traditionally relied on a reductionist hierarchy, allowing for the separate design of devices, architectures, and algorithms without sensitivity to one another. In contrast, analog computing systems are inherently interdependent from the material to architectural level, and this sensitivity can be advantageous. I will discuss this concept in the context of our work on designing artificial axons, neurons, and networks by exploiting the physics of correlated oxides4-6.
[1] Based on SRC Decadal Report (2021), adapted from EES2 report
[2] Talin et al., “Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities.” Chemical Reviews (2025).
[3] Gross, Fuller, et. al., “A self-heating electrochemical cell with nine decades of programmable linear resistance”, in review Science (2026)
[4] Brown et al., “Axon-like active signal transmission.” Nature (2024)
[5] Zhang, Fuller, et al., “Tuning the Spin Transition and Carrier Type in Rare‐Earth Cobaltates via Compositional Complexity.” Advanced Materials (2024)
[6] Salagre, Fuller, et. al. “Electrothermally induced channel formation in a spin crossover neuron” ACS Nano (2026)
Elliot J. Fuller earned his doctorate in condensed matter physics from the University of California, Irvine, in 2015, where he focused on low-dimensional materials. In 2018, he joined the Materials Physics Department at Sandia National Laboratories in Livermore, CA. Elliot’s research interests encompass correlated oxides, novel physical computing paradigms, neuromorphic computing, and energy materials