The brain’s remarkable and efficient information processing capability is driving research into brain-inspired (neuromorphic) computing paradigms. Artificial aqueous ion channels are emerging as an exciting platform for neuromorphic computing, representing a departure from conventional solid-state devices by directly mimicking the brain’s fluidic ion transport. Supported by a quantitative theoretical model, we present easy-to-fabricate tapered microchannels that embed a conducting network of fluidic nanochannels between a colloidal structure. Due to transient salt concentration polarization, our devices are volatile memristors (memory resistors) that are remarkably stable. The voltage-driven net salt flux and accumulation, that underpin the concentration polarization, surprisingly combine into a diffusionlike quadratic dependence of the memory retention time on the channel length, allowing channel design for a specific timescale. We implement our device as a synaptic element for neuromorphic reservoir computing. Individual channels distinguish various time series, that together represent (handwritten) numbers, for subsequent in silico classification with a simple readout function. Our results represent a significant step toward realizing the promise of fluidic ion channels as a platform to emulate the rich aqueous dynamics of the brain.

Ion current rectification (ICR) is the ratio of ion current by forward bias to backward bias and is a critical indicator of diode performance. In previous studies, there have been many attempts to improve the performance of this ICR, but there is the intrinsic problem for geometric changes that induce ionic rectification due to fabrication problems. Additionally, the high ICR could be achieved in the narrow salt concentration range only. Here, we propose a multi-layered bipolar ionic diode based on an asymmetric nanochannel network membrane (NCNM), which is realized by soft lithography and self-assembly of homogenous-sized nanoparticles. Owing to the freely changeable geometry based on soft lithography, the ICR performance can be explored according to the variation of microchannel shape. The presented diode with multi-layered configuration shows strong ICR performance, and in a broad range of salt concentrations (0.1 mM~100 mM), steady ICR performance. It is interesting to note that when each anion-selective (AS) and cation-selective (CS) NCNM volume was similar to each optimized volume in a single-layered device, the maximum ICR was obtained. Multi-physics simulation, which reveals greater ionic concentration at the bipolar diode junction under forward bias and less depletion under backward in comparison to the single-layer scenario, supports this tendency as well. Additionally, under different frequencies and salt concentrations, a large-area hysteresis loop emerges, which indicates fascinating potential for electroosmotic pumps, memristors, biosensors, etc.

Ultrasensitive mass detection is essential across various fields, including environmental monitoring, biosensing, and medical diagnostics. Quartz crystal microbalance (QCM) and nanoelectromechanical system (NEMS) sensors are widely utilized, yet NEMS approaches are hindered by issues of stability and reproducibility, whereas QCMs face fundamental physical limitations in enhancing sensitivity. To address the limitations of current sensing technologies, we demonstrate that increasing the driving force applied to the QCM induces non-linear resonance, and that utilizing the abrupt amplitude drop occurring at this non-linear resonance enables mass detection down to 100 fg. Unlike conventional linear QCM operation, our method significantly enhances mass sensitivity by exploiting amplitude-drop behavior in the non-linear regime, without requiring additional surface functionalization or device modification. We validated this sensing strategy through the detection of micro/nanoparticles and protein-antibody interactions, successfully achieving single micro/nanoparticle detection and reaching a detection limit of 100 fg. Notably, this method enables reliable single micro/nanoparticle detection with high reproducibility. This sensing approach provides a simple yet powerful platform that overcomes key limitations of traditional QCM systems. With the potential for real-time biomolecular diagnostics in aqueous environments and future integration with microfluidic chips, our approach represents a promising strategy for ultra-sensitive mass detection.