Synaptical Tunability of Multipore Nanofluidic Memristors

Unlocking Nanoprecipitation: A Pathway to High Reversibility in Nanofluidic Memristors

Solid-state nanochannels have emerged as a promising platform for the development of ionic circuit components with analog properties to their traditional electronic counterparts. In the last years, nanofluidic devices with memristive properties have attracted special interest due to their applicability in, for example, the construction of brain-like computing systems. In this work, an asymmetric track-etched nanofluidic channel with memory-enhanced ion transport is reported. The results illustrate that the formation of nanoprecipitates on the channel walls induces memory effects in ion transport, leading to characteristic hysteresis loops in the current-voltage curves, a hallmark of memristive behavior. Notably, these memristive properties are achievable with a straightforward experimental setup that combines an aqueous solvent and a relatively low-soluble inorganic salt. The various conductance states can be rapidly and reversibly tuned over prolonged time scales. Furthermore, under appropriate measurement conditions, the nanofluidic device can alternate between different iontronic regimes and states, encompassing ion current rectification, ON-OFF states, and memristor-like behavior. These findings provide insights into the design and optimization of nanofluidic devices for bioinspired ionic circuit components.

Scan-Rate-Dependent Ion Current Rectification in Bipolar Interfacial Nanopores

This study presents a theoretical investigation into the voltammetric behavior of bipolar interfacial nanopores due to the effect of potential scan rate (1-1000 V/s). Finite element method (FEM) is utilized to explore the current-voltage (I-V) properties of bipolar interfacial nanopores at different bulk salt concentrations. The results demonstrate a strong impact of the scan rate on the I-V response of bipolar interfacial nanopores, particularly at relatively low concentrations. Hysteresis loops are observed in bipolar interfacial nanopores under specific scan rates and potential ranges and divided by a cross-point potential that remains unaffected by the scan rate employed. This indicates that the current in bipolar interfacial nanopores is not just reliant on the bias potential that is imposed but also on the previous conditions within the nanopore, exhibiting history-dependent or memory effects. This scan-rate-dependent current-voltage response is found to be significantly influenced by the length of the nanopore (membrane thickness). Thicker membranes exhibit a more pronounced scan-rate-dependent phenomenon, as the mass transfer of ionic species is slower relative to the potential scan rate. Additionally, unlike conventional bipolar nanopores, the ion current passing through bipolar interfacial nanopores is minimally affected by the membrane thickness, making it easier to detect.

Tailored Fabrication of 3D Nanopores Made of Dielectric Oxides for Multiple Nanoscale Applications

Solid-state nanopores are a key platform for single-molecule detection and analysis that allow engineering of their properties by controlling size, shape, and chemical functionalization. However, approaches relying on polymers have limits for what concerns hardness, robustness, durability, and refractive index. Nanopores made of oxides with high dielectric constant would overcome such limits and have the potential to extend the suitability of solid-state nanopores toward optoelectronic technologies. Here, we present a versatile method to fabricate three-dimensional nanopores made of different dielectric oxides with convex, straight, and concave shapes and demonstrate their functionality in a series of technologies and applications such as ionic nanochannels, ionic current rectification, memristors, and DNA sensing. Our experimental data are supported by numerical simulations that showcase the effect of different shapes and oxide materials. This approach toward robust and tunable solid-state nanopores can be extended to other 3D shapes and a variety of dielectrics.

Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis

Iontronic fluidic ionic/electronic components are emerging as promising elements for artificial brain-like computation systems. Nanopore ionic rectifiers can be operated as a synapse element, exhibiting conductance modulation in response to a train of voltage impulses, thus producing programmable resistive states. We propose a model that replicates hysteresis, rectification, and time domain response properties, based on conductance modulation between two conducting modes and a relaxation time of the state variable. We show that the kinetic effects observed in hysteresis loops govern the potentiation phenomena related to conductivity modulation. To illustrate the efficacy of the model, we apply it to replicate rectification, hysteresis and conductance modulation of two different experimental systems: a polymer membrane with conical pores, and a blind-hole nanoporous anodic alumina membrane with a barrier oxide layer. We show that the time transient analysis of the model develops the observed potentiation and depression phenomena of the synaptic properties.

pH-Dependent Effects in Nanofluidic Memristors

Multipore membranes with nanofluidic diodes show memristive and current rectifying effects that can be controlled by the nanostructure asymmetry and ionic solution characteristics in addition to the frequency and amplitude of the electrical driving signal. Here, we show that the electrical conduction phenomena, which are modulated by the interaction between the pore surface charges and the solution mobile ions, allow for a pH-dependent neuromorphic-like potentiation of the membrane conductance by voltage pulses. Also, we demonstrate that arrangements of memristors can be employed in the design of electrochemical circuits for implementing logic functions and information processing in iontronics.

Dynamic Response of Ionic Current in Conical Nanopores

Ionic current rectification (ICR) of charged conical nanopores has various applications in fields including nanofluidics, biosensing, and energy conversion, whose function is closely related to the dynamic response of nanopores. The occurrence of ICR originates from the ion enrichment and depletion in conical pores, whose formation is found to be affected by the scanning rate of voltages. Here, through time-dependent simulations, we investigate the variation of ion current under electric fields and the dynamic formation of ion enrichment and depletion, which can reflect the response time of conical nanopores. The response time of nanopores when ion enrichment forms, i.e., at the "on" state is significantly longer than that with the formation of ion depletion, i.e., at the "off" state. Our simulation results reveal the regulation of response time by different nanopore parameters including the surface charge density, pore length, tip, and base radius, as well as the applied conditions such as the voltage and bulk concentration. The response time of nanopores is closely related to the surface charge density, pore length, voltage, and bulk concentration. Our uncovered dynamic response mechanism of the ionic current can guide the design of nanofluidic devices with conical nanopores, including memristors, ionic switches, and rectifiers.

Single-Pore Nanofluidic Logic Memristor with Reconfigurable Synaptic Functions and Designable Combinations

The biological neural network is a highly efficient in-memory computing system that integrates memory and logical computing functions within synapses. Moreover, reconfiguration by environmental chemical signals endows biological neural networks with dynamic multifunctions and enhanced efficiency. Nanofluidic memristors have emerged as promising candidates for mimicking synaptic functions, owing to their similarity to synapses in the underlying mechanisms of ion signaling in ion channels. However, realizing chemical signal-modulated logic functions in nanofluidic memristors, which is the basis for brain-like computing applications, remains unachieved. Here, we report a single-pore nanofluidic logic memristor with reconfigurable logic functions. Based on the different degrees of protonation and deprotonation of functional groups on the inner surface of the single pore, the modulation of the memristors and the reconfiguration of logic functions are realized. More noteworthy, this single-pore nanofluidic memristor can not only avoid the average effects in multipore but also act as a fundamental component in constructing complex neural networks through series and parallel circuits, which lays the groundwork for future artificial nanofluidic neural networks. The implementation of dynamic synaptic functions, modulation of logic gates by chemical signals, and diverse combinations in single-pore nanofluidic memristors opens up new possibilities for their applications in brain-inspired computing.

Brain-inspired computing with fluidic iontronic nanochannels

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.

Memristive arrangements of nanofluidic pores

We demonstrate that nanofluidic diodes in multipore membranes show a memristive behavior that can be controlled not only by the amplitude and frequency of the external signal but also by series and parallel arrangements of the membranes. Each memristor consists of a polymeric membrane with conical nanopores that allow current rectification due to the electrical interaction between the ionic solution and the pore surface charges. This surface charge-regulated ionic transport shows a rich nonlinear physics, including memory and inductive effects, which are characterized here by the current-voltage curves and electrical impedance spectroscopy. Also, neuromorphiclike potentiation of the membrane conductance following voltage pulses (spikes) is observed. The multipore membrane with nanofluidic diodes shows physical concepts that should have application for information processing and signal conversion in iontronics hybrid devices.

Neuromorphic responses of nanofluidic memristors in symmetric and asymmetric ionic solutions

We show that ionic conduction properties of a multipore nanofluidic memristor can be controlled not only by the amplitude and frequency of an external driving signal but also by chemical gating based on the electrolyte concentration, presence of divalent and trivalent cations, and multi-ionic systems in single and mixed electrolytes. In addition, we describe the modulation of current rectification and hysteresis phenomena, together with neuromorphic conductance responses to voltage pulses, in symmetric and asymmetric external solutions. In our case, memristor conical pores act as nanofluidic diodes modulated by ionic solution characteristics due to the surface charge-regulated ionic transport. The above facts suggest potential sensing and actuating applications based on the conversion between ionic and electronic signals in bioelectrochemical hybrid circuits.