Iontronic Neuromorphic Signaling with Conical Microfluidic Memristors

Metal-Organic Framework Nanofluidic Synapse

Chemical synapse completes the signaling through neurotransmitter-mediated ion flux, the emulation of which has been a long-standing obstacle in neuromorphic exploration. Here, we report metal-organic framework (MOF) nanofluidic synapses in which conjugated MOFs with abundant ionic storage sites underlie the ionic hysteresis and simultaneously serve as catalase mimetics that sensitively respond to neurotransmitter glutamate (Glu). Various neurosynaptic patterns with adaptable weights are realized via Glu-mediated chemical/ionic coupling. In particular, nonlinear Hebbian and anti-Hebbian learning in millisecond time ranges are achieved, akin to those of chemical synapses. Reversible biochemical in-memory encoding via enzymatic Glu clearance is also accomplished. Such results are prerequisites for highly bionic electrolytic computers.

Soft Memristor at a Microbubble Interface

Memristors show promising features for neuromorphic computing. Here we report a soft memristor based on the liquid-vapor surface of a microbubble. The thickness of the liquid film was modulated by electrostatic and interfacial forces, enabling resistance switches. We found a pinched current hysteresis at scanning periods between 1.6 and 51.2 s, while representing a resistor below 1.6 s and a diode-like behavior above 51.2 s. We approximate the thickening/thinning dynamics of liquid film by pressure-driven flow at the interface and derived the impacts of salt concentration and voltage amplitude on the memory effects. Our work opens a new approach to building nanofluidic memristors by a soft interface, which may be useful for new types of neuromorphic computing in the future.

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.

Discontinuous Transition in Electrolyte Flow through Charge-Patterned Nanochannels

We investigate the flow of an electrolyte through a rigid nanochannel decorated with a surface charge pattern. Employing lattice Boltzmann and dissipative particle dynamics methods, as well as analytical theory, we show that the electrohydrodynamic coupling leads to two distinct flow regimes. The accompanying discontinuous transition between slow, ionic, and fast, Poiseuille flows is observed at intermediate ion concentrations, channel widths, and electrostatic coupling strengths. These findings indicate routes to design nanochannels containing a typical aqueous electrolyte that exhibit a digital on-off flux response, which could be useful for nanofluidics and ionotronic applications.

Artificial chemotaxis under electrodiffusiophoresis

HYPOTHESIS

Through a large parameter space, electric fields can tune colloidal interactions and forces leading to diverse static and dynamical structures. So far, however, field-driven interactions have been limited to dipole-dipole and hydrodynamic contributions. Nonetheless, in this work, we propose that under the right conditions, electric fields can also induce interactions based on local chemical fields and diffusiophoretic flows.

EXPERIMENTS

Herein, we present a strategy to generate and measure 3D chemical gradients under electric fields. In this approach, faradaic reactions at electrodes induce global pH gradients that drive long-range transport through electrodiffusiophoresis. Simultaneously, the electric field induces local pH gradients by driving the particle's double layer far from equilibrium.

FINDINGS

As a result, while global pH gradients lead to 2D focusing away from electrodes, local pH gradients induce aggregation in the third dimension. Evidence points to a mechanism of interaction based on diffusiophoresis. Interparticle interactions display a strong dependence on surface chemistry, zeta potential and diameter of particles. Furthermore, pH gradients can be readily tuned by adjusting the voltage and frequency of the electric field. For large Péclet numbers, we observed a collective chemotactic-like collapse of particles. Remarkably, such collapse occurs without reactions at a particle's surface. By mixing particles with different sizes, we also demonstrate, through experiments and Brownian dynamics simulations, the emergence of non-reciprocal interactions, where small particles are more drawn towards large ones.

Nanofluidic Ionic Memristors

Living organisms use ions and small molecules as information carriers to communicate with the external environment at ultralow power consumption. Inspired by biological systems, artificial ion-based devices have emerged in recent years to try to realize efficient information-processing paradigms. Nanofluidic ionic memristors, memory resistors based on confined fluidic systems whose internal ionic conductance states depend on the historical voltage, have attracted broad attention and are used as neuromorphic devices for computing. Despite their high exposure, nanofluidic ionic memristors are still in the initial stage. Therefore, systematic guidance for developing and reasonably designing ionic memristors is necessary. This review systematically summarizes the history, mechanisms, and potential applications of nanofluidic ionic memristors. The essential challenges in the field and the outlook for the future potential applications of nanofluidic ionic memristors are also discussed.

Memristive Characteristics in an Asymmetrically Charged Nanochannel

The emergent nanofluidic memristor provides a promising way of emulating neuromorphic functions in the brain. The conical-shaped nanopore showed promising features for a nanofluidic memristor, inspiring us to investigate the memory effects in asymmetrically charged nanochannels due to their high current rectification, which may result in good memory effects. Here, the memory effects of an asymmetrically charged nanofluidic channel were numerically simulated by Poisson-Nernst-Planck equations. Our results showed that the I-V curves represented a diode in low scanning frequency and then became a memristor and finally a resistor as frequency increased. We successfully replicated the learning behavior in our system with history-dependent ion redistribution in the nanochannel. Some critical factors were quantitatively analyzed for the memory effects including voltage amplitude, optimal frequency, and Dukhin number. Experimental characterizations were also carried out. Our findings are useful for the design of nanofluidic memristors by the principle of enrichment and depletion as well as the determination of the best memory settings.

Geometrically Scalable Iontronic Memristors: Employing Bipolar Polyelectrolyte Gels for Neuromorphic Systems

Iontronics that are capable of mimicking the functionality of biological systems within an artificial fluidic network have long been pursued for biomedical applications and ion-based intelligence systems. Here, we report on facile and robust realization of iontronic bipolar memristors featuring a three-layer polyelectrolyte gel structure. Significant memristive hysteresis of ion currents was successfully accomplished, and the memory time proved geometrically scalable from 200 to 4000 s. These characteristics were enabled by the ion concentration polarization-induced rectification ratio within the polyelectrolyte gels. The memristors exhibited memory dynamics akin to those observed in unipolar devices, while the bipolar structure notably enabled prolonged memory time and enhanced the ion conductance switching ratio with mesoscale (10-1000 μm) geometry precision. These properties endow the devices with the capability of effective neuromorphic processing with pulse-based input voltage signals. Owing to their simple fabrication process and superior memristive performance, the presented iontronic bipolar memristors are versatile and can be easily integrated into small-scale iontronic circuits, thereby facilitating advanced neuromorphic computing functionalities.

Improved ionic current rectification utilizing cylindrical nanochannels coated with polyelectrolyte layers of non-uniform thickness

Conical nanochannels employed to create ionic current rectification (ICR) in nanofluidic devices are prone to clogging due to the contraction at one end. As an alternative approach for creating ICR, a cylindrical nanochannel covered with a polyelectrolyte layer (PEL) of variable thickness is proposed in the present study. The efficacy of the proposed design is studied by numerically solving the governing equations including the Poisson, Nernst-Planck, and Stokes-Brinkman equations. Furthermore, the fundamental mechanism behind ICR is explained using a simplified one-dimensional model. The effects of the nanochannel radius, concentration of PEL fixed charges, and bulk ionic concentration on the rectification factor are then investigated in detail. It is shown that the proposed nanochannel provides larger rectification factors as compared to conical nanochannels over wide ranges of the fixed charge concentration and bulk ionic concentration. Such a performance can be achieved even at channel radii much larger than the tip radius of conical nanochannels, indicating not only the better performance of the proposed nanochannel but also its likely longer service life, because of reducing the probability of total ionic current blockage. This means that the proposed nanochannel could find widespread use in fluidic devices, as a replacement for conical nanofluidic diodes.

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.

Enhanced Rectification Performance in Bipolar Janus Graphene Oxide Channels by Lateral Electric Fields

Improving the ionic rectification in nanochannels enables versatile applications such as biosensors, energy harvesting, and fluidic diodes. While previous work mostly focused on the effect of channel geometry and surface charge, in this work via a series of molecular dynamics simulations, we find a striking phenomenon that the ionic current rectification (ICR) ratio in Janus graphene oxide (GO) channels can be tremendously promoted by lateral electric fields. First, under a given axial electric field, an additional lateral electric field can improve the ICR ratio by several times to an order, depending on the channel symmetry. The symmetric channel has an obviously greater ICR ratio because it maintains a more pronounced ion transport disparity at opposite axial fields. The underlying mechanism for the function of the lateral electric field is that it promotes the lateral migration of ions and thus amplifies the ion-residue electrostatic interaction at opposite axial fields, enlarging the ion dynamical difference. Furthermore, for different axial electric fields, the ICR ratio can always be improved by lateral electric fields (up to two orders), suggesting that the ICR improvement is universal. Our results demonstrate that applying a lateral electric field could be a new method to improve the rectification performance of nanochannels, providing valuable guidance for the design of efficient ionic diode 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.

Asymmetric rectified electric fields: nonlinearities and equivalent circuits

Recent experiments [S. H. Hashemi et al., Phys. Rev. Lett., 2018, 121, 185504] have shown that a long-ranged steady electric field emerges when applying an oscillating voltage over an electrolyte with unequal mobilities of cations and anions confined between two planar blocking electrodes. To explain this effect we analyse full numerical calculations based on the Poisson-Nernst-Planck equations by means of analytically constructed equivalent electric circuits. Surprisingly, the resulting equivalent circuit has two capacitive elements, rather than one, which introduces a new timescale for electrolyte dynamics. We find a good qualitative agreement between the numerical results and our simple analytic model, which shows that the long-range steady electric field emerges from the different charging rates of cations and anions in the electric double layers.

Synaptical Tunability of Multipore Nanofluidic Memristors

We demonstrate a multipore nanofluidic memristor with conical pores showcasing a wide range of hysteresis and memristor properties that provide functionalities for brainlike computation in neuromorphic applications. Leveraging the interplay between the charged functional groups on the pore surfaces and the confined ionic solution, the memristor characteristics are modulated through the electrolyte type, ionic concentrations, and pH levels of the aqueous solution. The multipore membrane mimics the functional characteristics of biological ion channels and displays synaptical potentiation and depression. Furthermore, this property can be inverted in polarity by chemically varying the pH level. The ability to modulate memory effects by ionic conductivity holds promise for enhancing signal information processing capabilities.

Iontronic Nanopore Model for Artificial Neurons: The Requisites of Spiking

Brain-inspired neuromorphic computing is currently being investigated for effective artificial intelligence (AI) systems. The development of artificial neurons and synapses is imperative to creating efficient computational biomimetic networks. Here we propose the minimal configuration of an effective iontronic spiking neuron based on a conical nanofluidic pore ionic diode. The conductance is composed of a Boltzmann open channel probability and a blocking inactivation function, forming the structure of a memristor. The presence of a negative resistance and the combination of activation-deactivation dynamics cause a Hopf bifurcation. Using the characteristic frequencies of small perturbation impedance spectroscopy, we discuss the conditions of spiking, in which the system enters a limit cycle oscillation. We arrive at the conclusion that an excitable neuron-like system can be made with a single active channel instead of the more complex combination of multiple channels that occurs in the Hodgkin-Huxley neuron model.

Concluding remarks: Iontronics, from fundamentals to ion-controlled devices - Random access memories

Is this the dawn of iontronics? Iontronics underpins the notion of devices and ionic machines, whereby ion and water also act as information carriers. Thinking about iontronics gives a vision and a road map, with applications in the water-energy nexus.

Unveiling the capabilities of bipolar conical channels in neuromorphic iontronics

Conical channels filled with an aqueous electrolyte have been proposed as promising candidates for iontronic neuromorphic circuits. This is facilitated by a novel analytical model for the internal channel dynamics [T. M. Kamsma, W. Q. Boon, T. ter Rele, C. Spitoni and R. van Roij, Phys. Rev. Lett., 2023, 130(26), 268401], the relative ease of fabrication of conical channels, and the wide range of achievable memory retention times by varying the channel lengths. In this work, we demonstrate that the analytical model for conical channels can be generalized to channels with an inhomogeneous surface charge distribution, which we predict to exhibit significantly stronger current rectification and more pronounced memristive properties in the case of bipolar channels, i.e. channels where the tip and base carry a surface charge of opposite sign. Additionally, we show that the use of bipolar conical channels in a previously proposed iontronic circuit features hallmarks of neuronal communication, such as all-or-none action potentials and spike train generation. Bipolar channels allow, however, for circuit parameters in the range of their biological analogues, and exhibit membrane potentials that match well with biological mammalian action potentials, further supporting their potential biocompatibility.