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

ChemPhysChem, Journal Year: 2024, Volume and Issue: 25(23)

Published: Aug. 9, 2024

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

Language: Английский

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Leaving Constraints of Single Nanopores and Designing Biomimetic Nanopore Arrays

Current Opinion in Electrochemistry, Journal Year: 2025, Volume and Issue: unknown, P. 101677 - 101677

Published: Feb. 1, 2025

Language: Английский

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Bioinspired ion-shuttling memristor with both neuromorphic functions and ion selectivity

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(10)

Published: March 5, 2025

The fluidic memristor has attracted growing attention as a promising candidate for neuromorphic computing and brain-computer interfaces. However, with ion selectivity that of natural channels remains key challenge. Herein, inspired by the structure biomembranes, we developed an ion-shuttling (ISM) utilizing organic solvents artificial carriers to emulate embedded in which exhibited both functions selectivity. Pinched hysteresis I-V loop curve, scan rate dependency, distinctive impedance spectra confirmed memristive characteristics as-prepared device. Moreover, memory mechanism was discussed theoretically validated finite-element modeling. ISM features multiple functions, such paired-pulse facilitation, depression, learning-experience behavior. More importantly, observed, allowed further emulation ion-selective neural like resting membrane potential. Benefiting from structural similarity membrane-embedded channels, opens door ion-based sophisticated chemical regulation manipulating multifarious ions functions.

Language: Английский

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Nanofluidic Volatile Threshold Switching Ionic Memristor: A Perspective

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

The fast development of artificial intelligence and big data drives the exploration low-power computing hardware. Neuromorphic devices represented by memristors may provide a possible paradigm beyond von Neumann's architecture because they enable integration processing storage units mimicking how brain processes complex information in parallel. In brain, is processed via multilevel spiking coding event-driven mechanisms, whose simplified neural circuit leaky-integration-and-fire model combining volatile threshold switching capacitors. As unit to emulate working environment explore unique functions ions molecules biological systems, nanofluidic ionic become essential but are still missing. This Perspective will review mechanism role as building block for neuromorphic list three routes ones.

Language: Английский

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Emerging Liquid‐Based Memristive Devices for Neuromorphic Computation

Small Methods, Journal Year: 2025, Volume and Issue: unknown

Published: March 18, 2025

Abstract To mimic the neural functions of human brain, developing hardware with natural similarities to nervous system is crucial for realizing neuromorphic computing architectures. Owing their capability emulate artificial neurons and synapses, memristors are widely regarded as a leading candidate achieving computing. However, most current memristor devices solid‐state. In contrast, biological systems operate within an aqueous environment, brain accomplishes intelligent behaviors such information generation, transmission, memory by regulating ion transport in neuronal cells. achieve that more analogous energy‐efficient, based on liquid environments developed. contrast traditional solid‐state memristors, liquid‐based possess advantages anti‐interference, low energy consumption, heat generation. Simultaneously, they demonstrate excellent biocompatibility, rendering them ideal option next generation intelligence systems. Numerous experimental demonstrations reported, showcasing unique memristive properties novel functionalities. This review focuses recent developments discussing operating mechanisms, structures, functional characteristics. Additionally, potential applications development directions proposed.

Language: Английский

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Nanofluidic Memristive Transition and Synaptic Emulation in Atomically Thin Pores

Nano Letters, Journal Year: 2025, Volume and Issue: unknown

Published: March 29, 2025

Ionic transport across nanochannels is the basis of communications in living organisms, enlightening neuromorphic nanofluidic iontronics. Comparing to angstrom-scale long biological ionic pathways, it remains a great challenge achieve memristors at such thinnest limit due ambiguous electrical model and interaction process. Here, we report atomically thin memristive nanopores two-dimensional materials by designing optimized conductance decouple memristive, ohmic, capacitive effects. By conducting different charged iontronics, realize reconfigurable transition between nonvolatile-bipolar volatile-unipolar characteristics, which arises from distinct processes governed energy barriers. Notably, emulate synaptic functions with ultralow consumption ∼0.546 pJ per spike reproduce learning behaviors. The are similar biosystems angstrom structure, rich iontronic responses, millisecond-level operating pulse width, matching potential width. This work provides new paradigm for boosting brain-inspired devices.

Language: Английский

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Resistance-Restorable Nanofluidic Memristor and Neuromorphic Chip

Nano Letters, Journal Year: 2025, Volume and Issue: unknown

Published: April 12, 2025

Resistance drift due to residual ions limits the accuracy of memristor-based neuromorphic computing. Here, we demonstrate nanofluidic memristors based on voltage-driven ion filling within Ångström channels, immersed in asymmetrically concentrated electrolyte solutions. Inspired by brain's waste clearance, restore conductance after 20,000 cycles removing trapped ions, paving way for endurance enhancement. The devices exhibit hour-long retention and ultralow energy consumption (∼0.2 fJ per spike channel). By tuning voltage, frequency, pH, emulate short-term synaptic plasticity. Finally, demonstrated first 4 × memristor array capable recognizing mathematical operators. Our work that fluidic are promising energy-efficient, long-retention, chips.

Language: Английский

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Heterojunction Nanofluidic Memristors based on Peptide Chain Valves for Neuromorphic applications

Biosensors and Bioelectronics, Journal Year: 2025, Volume and Issue: 282, P. 117496 - 117496

Published: April 18, 2025

Language: Английский

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Recent advances in fluidic neuromorphic computing

Applied Physics Reviews, Journal Year: 2025, Volume and Issue: 12(2)

Published: April 21, 2025

Human brain is capable of optimizing information flow and processing without energy-intensive data shuttling between processor memory. At the core this unique capability are billions neurons connected through trillions synapses—basic units brain. The action potentials or “spikes” based temporal using regulated ions across ion channels in neuron cells allows sparse efficient transmission Emerging systems on confined fluidic have provided a framework for new type neuromorphic computing with lower energy consumption, hardware-level plasticity, multiple carriers that emulate natural processes mechanisms human These mimic neuronal architectures by harnessing modulating transport along artificial channels. spikes-induced ion-to-surface interactions within these enables control ionic conductivity to achieve synaptic plasticity realization brain-inspired functionalities such as memory effect signal transmission. Herein, review provides an overview recent advances devices memristors other components, covering their basic operations, materials architectures, well applications computing. concludes brief outline challenges emerging technologies face outlook development fluidic-based

Language: Английский

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Ion–Electron Interactions in 2D Nanomaterials-Based Artificial Synapses for Neuromorphic Applications

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: April 29, 2025

With the increasing limitations of conventional computing techniques, particularly von Neumann bottleneck, brain's seamless integration memory and processing through synapses offers a valuable model for technological innovation. Inspired by biological synapse facilitating adaptive, low-power computation modulating signal transmission via ionic conduction, iontronic synaptic devices have emerged as one most promising candidates neuromorphic computing. Meanwhile, atomic-scale thickness tunable electronic properties van der Waals two-dimensional (2D) materials enable possibility designing highly integrated, energy-efficient that closely replicate plasticity. This review comprehensively analyzes advancements in based on 2D materials, focusing electron-ion interactions both transistors memristors. The challenges material stability, scalability, device are evaluated, along with potential solutions future research directions. By highlighting these developments, this insights into advancing systems.

Language: Английский

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