Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Talin, A. Alec; Meyer, Jordan; Li, Jingxian; Huang, Mantao; Schwacke, Miranda; Chung, Heejung W.; Xu, Longlong; Fuller, Elliot J.; Li, Yiyang; Yildiz, Bilge

doi:10.1021/acs.chemrev.4c00512

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Journal Article · Mon Feb 17 00:00:00 EST 2025 · Chemical Reviews

DOI:https://doi.org/10.1021/acs.chemrev.4c00512· OSTI ID:2530829

^[1]; ^[2]; ^[3]; ^[2]; ^[2]; Chung, Heejung W. ^[2]; Xu, Longlong ^[2]; ^[1]; ^[3]; ^[2]

Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Univ. of Michigan, Ann Arbor, MI (United States)

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

View Accepted Manuscript (DOE)

Research Organization:: Northwestern Univ., Evanston, IL (United States); Sandia National Laboratories (SNL-CA), Livermore, CA (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: NA0003525; SC0023450

OSTI ID:: 2530829

Alternate ID(s):: OSTI ID: 3015276

Report Number(s):: SAND--2025-02982J

Journal Information:: Chemical Reviews, Journal Name: Chemical Reviews Journal Issue: 4 Vol. 125; ISSN 0009-2665

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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