Work

Leveraging Electrochemical Diversity in Engineering Liquid‐State Ionic Devices for Neuromorphic Computing

Year: 2026

Type: article

Abstract: ABSTRACT Implementing the brain's electrochemical principles in liquid‐state ionic devices for neuromorphic computing has gained notable momentum. A unique advantage of such devices is the abundance of ions and molecular species available for electrochemical signaling. In this work, we demonstrate that electrochemical diversity translates into functional diversity within the barrier‐limited transport regime, a phenomenon not captured by classical diffusion transport. Using molecular dynamics simulations, we investigate multi‐ionic transport through Ångström‐scale pores and reveal diverse behaviors, including voltage‐inactivated transport, electrochemical pulse generation, and synaptic potentiation. The resulting design space scales exponentially with the number of ion species, as , yielding an astronomically large number given the existence of more than 100 known ionic species. Our work highlights an extensive, unexplored design space of electrochemical computing devices occurring in the barrier‐limited transport regime.

Source: Small

DOI: 10.1002/smll.202511663

Authors: Yechan Noh, Alex Smolyanitsky

Institutions: University of Notre Dame, National Institute of Standards and Technology, University of Colorado Boulder

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $5,790

Funders: National Science Foundation, National Institute of Standards and Technology