A self-heating electrochemical cell with nine decades of programmable linear resistance
Abstract
A programmable linear resistor with a compact footprint would have profound implications for microelectronics, enabling efficient in-sensor analog signal processing and in-memory computing. Non-volatile memory offers a potential solution but suffers from limitations due to the programming mechanisms that confine switching to nanoscale constrictions or field-sensitive semiconductor junctions, leading to non-linear current-voltage relationships and errors. Here, we introduce a tunable resistor that is programmed into non-volatile, high-precision resistance states spanning nine orders of magnitude, with linear current-voltage characteristics across the entire range -- significantly improving the performance and widening the application space of resistive memory. A key advance is an electrothermal gate that simultaneously spreads heat and electrochemical reactions during programming to enable large, bulk composition modulation. The volumetric modulation can host thousands of linear resistance states with 100x lower conductance errors than other memory. This enables direct processing of analog signals with high fidelity, and we demonstrate variable-gain amplification, division, and multiplication. Integration with CMOS is used to show resilience to electrical and thermal disturb in arrays and to demonstrate retention of analog levels at <1% average loss for more than 2 months across 100 devices. Simulations indicate matrix multiplication efficiency could approach >1,000 TOPS/W.
Keywords
Cite
@article{arxiv.2505.15936,
title = {A self-heating electrochemical cell with nine decades of programmable linear resistance},
author = {Adam L. Gross and Sangheon Oh and Minseong Park and T. Patrick Xiao and François Léonard and Wyatt Hodges and Joshua D. Sugar and Jacklyn Zhu and Sritharini Radhakrishnan and Sangyong Lee and Jolie Wang and Adam S. Christensen and Sam Lilak and Patrick S. Finnegan and Patrick Crandall and Christopher H. Bennett and William Wahby and Robin Jacobs-Gedrim and Matthew J. Marinella and Yiyang Li and Su-in Yi and Nad Gilbert and Sapan Agarwal and A. Alec Talin and Elliot J. Fuller},
journal= {arXiv preprint arXiv:2505.15936},
year = {2026}
}