Ultralow‐Power Peptide‐Based Memristor Enabled by Emulation of Proton‐Mediated Synaptic Signaling
Open Access
- 24 October 2025
- journal article
- Published by Wiley in Small Methods
- Vol. 9 (12) , e01472
Abstract
The substantial power consumption of traditional computing architectures, arising from the physical separation of memory and processing units, has motivated the exploration of neuromorphic systems that emulate the remarkable energy efficiency of the human brain. However, artificial neural networks implemented on neuromorphic devices still require billions of weight updates, and conventional devices typically consume power in the milliwatt range per switching event, posing a significant challenge even for neuromorphic systems. In this study, a synapse‐like memristive device utilizing a tyrosine‐rich peptide is presented as the resistive switching layer. By emulating proton‐mediated signaling of biological synapses, the device leverages proton–electron dual‐carrier transport enabled by the redox‐active properties of tyrosine to realize ultralow‐power resistive switching. Proton modulation is implemented through two methods: i) exposure to external humidity and ii) electrically driven injection using a PdH x proton reservoir layer. Comparative analysis reveals that the electrically driven approach achieves an ultralow switching power of 215 pW—≈2500 times lower than that of the intrinsic device—primarily owing to the sustained low off‐current during proton injection. These results demonstrate a promising strategy for developing highly energy‐efficient, synapse‐like memristive devices through precise control of proton dynamics.Keywords
This publication has 65 references indexed in Scilit:
- Peptide‐Based Electronics for Neuromorphic HardwareAdvanced Functional Materials, 2025
- Proton‐Modulated Resistive Switching in a Synapse‐Like Tyrosine‐Rich Peptide‐Based MemristorAdvanced Functional Materials, 2024
- Memristor‐Based Neuromorphic ChipsAdvanced Materials, 2024
- Bulk‐Switching Memristor‐Based Compute‐In‐Memory Module for Deep Neural Network TrainingAdvanced Materials, 2023
- Natural Acidic Polysaccharide‐Based Memristors for Transient Electronics: Highly Controllable Quantized Conductance for Integrated Memory and Nonvolatile Logic ApplicationsAdvanced Materials, 2021
- Robust DNA‐Bridged Memristor for Textile ChipsAngewandte Chemie International Edition, 2020
- Self‐Assembled Networked PbS Distribution Quantum Dots for Resistive Switching and Artificial Synapse Performance Boost of MemristorsAdvanced Materials, 2018
- ReRAM: Role of the Electrode Material on the RESET Limitation in Oxide ReRAM Devices (Adv. Electron. Mater. 2/2018)Advanced Electronic Materials, 2018
- Proton Conduction in a Tyrosine‐Rich Peptide/Manganese Oxide Hybrid NanofilmAdvanced Functional Materials, 2017
- The Possible Role of Proton‐Coupled Electron Transfer (PCET) in Water Oxidation by Photosystem IIAngewandte Chemie International Edition, 2007