The emerging novel class of two-dimensional materials - MХenes - have attracted significant research attention. However, there are only few reports on using the most prominent member of the MXene family, Ti C T , as an active material for memristive devices within a polyelectrolyte matrix and its deposition on inert electrodes like ITO and Pt. In this study, we systematically investigate Ti C T MXenes synthesized with two classical delamination agents, such as lithium chloride and tetramethylammonium hydroxide, to identify the most suitable candidate for memristive device applications. The characteristics of memristors based on the hybrid structures consisting of MXene-polyelectrolyte multilayers, specifically polyethyleneimine (PEI) and poly(sodium 4-styrenesulfonate) (PSS) are explored. The PEI(MXene)/PSS memristor exhibits a voltage threshold (V ) range of 1.5-2.0 V, enabling the transition from a high-resistive state (HRS) to a low-resistive state (LRS), along with a significant current switching ratio of approximately two orders of magnitude. The observed V difference of approximately 4 V is further supported by density functional theory (DFT) calculated redox potential. These findings underscore the potential of polyelectrolyte-based memristors, such as the in PEI-Ti C T -PSS system, in facilitating the development of highly functional, self-assembled memristive devices with diverse applications.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/cphc.202300187 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware.
Nat Commun
January 2025
Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Via Opera Pia 13, I-16145, Genoa, Italy.
Mixed signal analog/digital neuromorphic circuits represent an ideal medium for reproducing bio-physically realistic dynamics of biological neural systems in real-time. However, similar to their biological counterparts, these circuits have limited resolution and are affected by a high degree of variability. By developing a recurrent spiking neural network model of the retinocortical visual pathway, we show how such noisy and heterogeneous computing substrate can produce linear receptive fields tuned to visual stimuli with specific orientations and spatial frequencies.
View Article and Find Full Text PDFIdentifying and understanding the nonlinear behavior of memristive devices.
Sci Rep
December 2024
Chair of Applied Electrodynamics and Plasma Technology, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany.
Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage characteristics. To comprehend the nonlinear behavior, we have to understand the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in these devices.
View Article and Find Full Text PDFMemristive Ion Dynamics to Enable Biorealistic Computing.
Chem Rev
December 2024
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089, United States.
Conventional artificial intelligence (AI) systems are facing bottlenecks due to the fundamental mismatches between AI models, which rely on parallel, in-memory, and dynamic computation, and traditional transistors, which have been designed and optimized for sequential logic operations. This calls for the development of novel computing units beyond transistors. Inspired by the high efficiency and adaptability of biological neural networks, computing systems mimicking the capabilities of biological structures are gaining more attention.
View Article and Find Full Text PDFUnraveling the Interplay Between Memristive and Magnetoresistive Behaviors in LaCoO/SrTiO Superlattice-Based Neural Synaptic Devices.
Small Methods
December 2024
State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China.
Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field-induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO/SrTiO)/LaCoO/Nb:SrTiO (Pt/(LCO/STO)/LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively.
View Article and Find Full Text PDFElectrically-driven control of nanoscale chemical changes in amorphous complex oxide memristive devices.
Nanotechnology
December 2024
Instituto de Nanociencia y Nanotecnología (CONICET-CNEA), Gral. Paz 1499 - San Martín - Argentina, BUENOS AIRES, 1650, ARGENTINA.
Our study demonstrates that strong cationic segregation can occur in amorphous complex oxide memristors during electrical operation. With the help of analytic techniques, we observed that switching the electrical stimulation from voltage to current significantly prevents structural changes and cation segregation at the nanoscale, improving also the device cycle-to-cycle variability. These findings could contribute to the design of more reliable oxide-based memristors and underscore the crucial effect that has the type of electrical stimulation applied to the devices on their integrity and reliability.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!