Emerging materials for resistive switching memories: Prospects for enhanced sustainability and performance for targeted applications DOI Creative Commons
Michalis Loizos, Konstantinos Rogdakis, Ashitha Paingott Parambil

et al.

APL Energy, Journal Year: 2024, Volume and Issue: 2(4)

Published: Dec. 1, 2024

Resistive switching (RS) memories are novel devices that have attracted significant attention recently in view of their potential integration deep neural networks for intense big data processing within the explosive artificial intelligence era. While oxide- or silicon-based memristive been thoroughly studied and analyzed, there alternative material technologies compatible with lower manufacturing cost less environmental impact exhibiting RS characteristics, thus providing a versatile platform specific in-memory computing neuromorphic applications where sustainability is priority. The these emerging based on solution-processed methods at low temperatures onto flexible substrates, some cases, active layer composed natural, environmentally friendly materials replacing expensive deposition critical raw toxic materials. In this Perspective, we provide an overview recent developments field sustainable by insights into fundamental properties mechanisms, categorizing key figures merit while showcasing representative use cases each technology. challenges limitations practical analyzed along suggestions to resolve pending issues.

Language: Английский

Kinetics of Volatile and Nonvolatile Halide Perovskite Devices: The Conductance-Activated Quasi-Linear Memristor (CALM) Model DOI Creative Commons
Agustín Bou, Karl Cedric Gonzales, Pablo P. Boix

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: unknown, P. 69 - 76

Published: Dec. 19, 2024

Memristors stand out as promising components in the landscape of memory and computing. are generally defined by a conductance mechanism containing state variable that imparts effect. The current–voltage cycling causes transitions conductance, which determined different physical mechanisms, such formation conducting filaments an insulating surrounding. Here, we provide unified description set reset processes using conductance-activated quasi-linear memristor (CALM) model with unique voltage-dependent relaxation time variable. We focus on halide perovskite memristors their intersection neuroscience-inspired show modeling approach adeptly replicates experimental traits both volatile nonvolatile memristors. Its versatility extends across various device materials configurations, W/SiGe/a-Si/Ag, Si/SiO2/Ag, SrRuO3/Cr-SrZrO3/Au memristors, capturing nuanced behaviors scan rate upper vertex dependence. also describes response to sequences voltage pulses cause synaptic potentiation effects. This is potent tool for comprehending probing dynamical indicating properties control observable responses.

Language: Английский

Citations

4
Reconfigurable Al2O3-Based Memristor for All-in-One Artificial Synapse and Nociceptor Neurons DOI

Hongshun Du,

Fang Wang, Zewen Li

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 2722 - 2730

Published: March 6, 2025

Multifunctional bionic devices have widespread applications in neuromorphic computing, intelligent sensors, and robotics. The inherent properties of memristors make them suitable for these emerging applications, but different require either volatile or nonvolatile operations a unique device. In this work, we developed novel reconfigurable Ag/Al2O3/ITO memristor, which achieves adjustable switching behavior between by modulating the compliance current. A proposed mechanism controls state conductive filaments device adjusting current, elucidating process states. Additionally, synaptic functionality nociceptor characteristics, including threshold, relaxation, inadaptation, sensitization, been successfully simulated. This integration artificial functions into single is achieved, with single-pulse power consumption reaching as low 0.912 nJ when threshold reached. These results provide insights construction multifunctional demonstrate significant potential future network applications.

Language: Английский

Citations

0
Leveraging Dual Resistive Switching in Quasi-2D Perovskite Memristors for Integrated Non-volatile Memory, Synaptic Emulation, and Reservoir Computing DOI

Zhenwang Luo,

Weisheng Wang, Junhui Wu

et al.

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

The increasing computational demands of artificial intelligence (AI) algorithms are exceeding the capabilities conventional computing architectures, creating a strong need for novel materials and paradigms. Memristors that integrate diverse resistive switching (RS) behaviors provide promising avenue developing architectures. In this study, we achieve coexistence volatile nonvolatile RS in quasi-2D perovskite memristor (Q-2DPM). Q-2DPM exhibits competitive performance as memory. Multiple synaptic functions have been successfully simulated on Q-2DPM, such excitatory postsynaptic currents, paired-pulse facilitation, long-term potentiation/depression. Furthermore, neural networks using synapses high accuracy MNIST image classification tasks. Q-2DPM's inherent characteristics suitable reservoir also demonstrated through its application pulse-stream-based digital experiment, showcasing impressive performance. elucidation dual mechanisms within provides fresh insights into behavior underscores potential achieving units single device. This work paves way implementation physical neuromorphic hardware architectures advancement sophisticated primitives, offering significant step toward next generation technologies.

Language: Английский

Citations

0
Microstructure-modulated conductive filaments in Ruddlesden-Popper perovskite-based memristors and their application in artificial synapses DOI
Fu-Chiao Wu, Zhicheng Su, Yu‐Chieh Hsu

et al.

Materials Today Physics, Journal Year: 2025, Volume and Issue: unknown, P. 101708 - 101708

Published: March 1, 2025

Language: Английский

Citations

0
DFT insights on the chloride double perovskites X2AuBiCl6 (X = K, Rb, and Cs) with semiconductor nature for PV and optoelectronic applications DOI
M. Musa Saad H.-E.,

B. O. Alsobhi

Computational Condensed Matter, Journal Year: 2025, Volume and Issue: unknown, P. e01040 - e01040

Published: April 1, 2025

Language: Английский

Citations

0
Coupling Light into Memristors: Advances in Halide Perovskite Resistive Switching and Neuromorphic Computing DOI Creative Commons

Zijian Feng,

Jintao Wang,

Fandi Chen

et al.

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

Published: April 25, 2025

Abstract Resistive switching memristor is an emerging nonvolatile memory technology designed to overcome the physical limitations of conventional systems and performance bottleneck von Neumann architecture. Notably, halide perovskite (HP)‐based memristors have gained significant attention in recent years due their unique ionic migration behavior exceptional photoelectric properties. This review highlights HP‐based resistive switching, focusing on its developments coupling light into discussing implications for neuromorphic computing. The mechanisms are explored alongside role HP properties enhancing dynamics. advantages applications light‐coupled including reduced voltage, enhanced operation reliability, multilevel capability, development light‐integrated artificial synapses discussed comprehensively. By fully harnessing optoelectronic HPs, this field may pave way innovative approaches technologies light‐responsive systems.

Language: Английский

Citations

0
Electrochemical Doping of Halide Perovskites with Silver Interstitial Ions: Mechanistic Insights and Enhanced Performance in Memristor Applications DOI

Pengtian Liu,

Tingting Dai,

Chao Yan

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 4480 - 4488

Published: April 26, 2025

Halide perovskites have garnered significant attention for their exceptional carrier mobility, balanced bipolar transport properties, and ion-electron mixing conductivity, making them highly promising applications, such as solar cells, photodetectors, memristors. Despite potential, intrinsic ions defects within these materials complicate effective doping, interactions between metal electrodes perovskite can trigger interfacial chemical reactions that compromise device stability performance. This study examines the influence of Ag on devices, specifically investigating n-doping effects Agi+ interstitial in MAPbI3 through an integrated approach combining first-principles density functional theory (DFT) calculations experimental analysis. Findings reveal ions, generated electrochemically at electrodes, penetrate structure migrate under applied electric field, achieving stable controlled bias conditions. Detailed characterization doping process was conducted using current density-time (J-t) measurements, electrochemical AC impedance (EIS), TOF-SIMS/XPS depth profiling, temperature/illumination-dependent studies. Additionally, memristive behavior device, including mechanisms formation metallic conductive filaments, demonstrated, offering insights into its potential applications advanced electronics. These findings elucidate physicochemical metal-perovskite interfaces diode devices.

Language: Английский

Citations

0
A balanced view of ion migration in halide perovskite electronics DOI
Feng Li, Yuhang Liang, Rongkun Zheng

et al.

Newton, Journal Year: 2025, Volume and Issue: 1(3), P. 100096 - 100096

Published: May 1, 2025

Language: Английский

Citations

0
Emerging materials for resistive switching memories: Prospects for enhanced sustainability and performance for targeted applications DOI Creative Commons
Michalis Loizos, Konstantinos Rogdakis, Ashitha Paingott Parambil

et al.

APL Energy, Journal Year: 2024, Volume and Issue: 2(4)

Published: Dec. 1, 2024

Resistive switching (RS) memories are novel devices that have attracted significant attention recently in view of their potential integration deep neural networks for intense big data processing within the explosive artificial intelligence era. While oxide- or silicon-based memristive been thoroughly studied and analyzed, there alternative material technologies compatible with lower manufacturing cost less environmental impact exhibiting RS characteristics, thus providing a versatile platform specific in-memory computing neuromorphic applications where sustainability is priority. The these emerging based on solution-processed methods at low temperatures onto flexible substrates, some cases, active layer composed natural, environmentally friendly materials replacing expensive deposition critical raw toxic materials. In this Perspective, we provide an overview recent developments field sustainable by insights into fundamental properties mechanisms, categorizing key figures merit while showcasing representative use cases each technology. challenges limitations practical analyzed along suggestions to resolve pending issues.

Language: Английский

Citations

0