Information processing by digitalizing confined ion transport

Ion transport under Ångström-scale confinement exhibits discontinuous and stochastic dynamics, inherently encoding information beyond merely transporting masses and charges. This capability has sparked growing interest in iontronics, a field aiming to harness ions as information carriers akin to biological systems. In contrast to electrons, which dominate modern electronics through high-speed switching at electron-volt energy scales, ions operate near the thermal energy scale (~ kBT). Their diverse sizes, solvation characteristics, and interaction with the channels promise low-energy processing by leveraging thermal fluctuations. Here we investigate digitalized ion flow (the ‘ionbit’) using molecular dynamics simulations of single-file transport through Ångström-scale single-walled carbon nanotubes. By shaping the free-energy landscape of ion transport, we functionalize nanotube entrances and interconnect them via nanoscale pockets that regulate kinetics through a hopping-and-diffusion mechanism. Specifically, ion accumulation, dissipation, and sorption processes in the pocket emulate synaptic integration, leakage, and firing events, while intrinsically embedding a memory function analogous to biological systems. Governed by kBT-level physics, this spiking neural network operates at ultralow energy cost, positioning iontronic circuits as a promising substrate for energy-efficient neuromorphic computation. We further discuss the key challenges that must be overcome to translate nanofluidic iontronic networks into scalable technologies, including precise assembly, robustness, and manufacturability.