In-sensor computing using Ti3C2Tx MXene memristor crossbar arrays for wearable electronics DOI
Jeny Gosai, Mansi Patel,

Anjalee Gosai

et al.

Flexible and Printed Electronics, Journal Year: 2024, Volume and Issue: 9(4), P. 045013 - 045013

Published: Dec. 1, 2024

Abstract The potential of memristor systems in sensing, storing, and processing signals make them highly efficient ideal for power-efficient, comfortable wearable in-sensor computing applications. In this work, we demonstrate a 3 × crossbar array based on Ti C 2 T x MXene with non-volatile characteristics, exhibiting an ON/OFF ratio ∼10 . This -based also showcases remarkable synaptic properties. Additionally, achieve near perfect accuracy pattern training after just 9 epochs as well retaining ability even 24 h. A notable feature these arrays is their to integrate storage, capabilities, demonstrated real-time muscle monitoring healthcare device. multi-channel surface electromyography data was recorded using the MXene-based track forearm movements during series distinct hand gestures. These findings open up exciting possibilities development adaptable flexible memristive arrays, which hold great promise advanced neuromorphic computing,

Language: Английский

Physical reservoir computing-based online learning of HfSiOx ferroelectric tunnel junction devices for image identification DOI
Seungjun Lee, Gaoyun An,

Gimun Kim

et al.

Applied Surface Science, Journal Year: 2025, Volume and Issue: unknown, P. 162459 - 162459

Published: Jan. 1, 2025

Language: Английский

Citations

1
An innovative biomimetic technology: Memristors mimic human sensation DOI
Kun Wang,

Mengna Wang,

Bai Sun

et al.

Nano Energy, Journal Year: 2025, Volume and Issue: unknown, P. 110698 - 110698

Published: Jan. 1, 2025

Language: Английский

Citations

0
Lead-Free Halide Perovskite-Based Flexible Memristor for an Artificial Mechano-nociceptive System DOI
Yuchan Wang, Qian Ran, Ting Chen

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 3177 - 3184

Published: March 20, 2025

Herein, novel lead-free Cs3Bi2I9 nanocrystals (NCs) were preferred through first-principles calculations and crystal orbital Hamilton population (COHP). An artificial nociceptor was designed using the halide perovskite (HP) NCs doped into poly(methyl methacrylate) (PMMA). The resulting composite material memristor demonstrated remarkable resistive switching performance conductive atomic force microscopy (C-AFM). PMMA&Cs3Bi2I9-based memristors show an ultrafast speed of 30 ns low threshold voltage ≈0.6 V with little variation, which attributed to synergistic effect active metal electrodes vacancy filaments. Impressively, high mechanical bending stability (bending times = 1000) still exhibit excellent resistance state (RS) properties multilevel storage after days exposed ambient conditions. More importantly, fundamental nociceptive functions fully demonstrated. Furthermore, a mechano-nociceptor system simulate mechanism biological pain perception, could selectively react mild harmful stimuli. Our study provides new strategies for developing efficient neuromorphic materials devices.

Language: Английский

Citations

0
Deciphering Mechanisms of Oxygen Vacancy Conducting Channel-Based LiSiOx Artificial Nociceptors DOI

Z.Y. Li,

Yao Shi,

Dianyou Song

et al.

Vacuum, Journal Year: 2025, Volume and Issue: unknown, P. 114296 - 114296

Published: March 1, 2025

Language: Английский

Citations

0
Recent Developments on Novel 2D Materials for Emerging Neuromorphic Computing Devices DOI Creative Commons

Muhammad Hamza Pervez,

Ehsan Elahi,

Muhammad Asghar Khan

et al.

Small Structures, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 8, 2024

The rapid advancement of artificial intelligent and information technology has led to a critical need for extremely low power consumption excellent efficiency. capacity neuromorphic computing handle large amounts data with garnered lot interest during the last few decades. For applications, 2D layered semiconductor materials have shown pivotal role due their distinctive properties. This comprehensive review provides an extensive study recent advancements in materials‐based devices especially multiterminal synaptic devices, two‐terminal neuronal integration devices. Herein, wide range potential applications memory, computation, adaptation, intelligence is incorporated. Finally, limitations challenges based on novel are discussed. Thus, this aims illuminate design fabrication van der Waals (vdW) heterostructure materials, leveraging promising engineering techniques excel hardware implementations.

Language: Английский

Citations

2
A zinc oxide-based threshold switching memristor for simulating synaptic plasticity and artificial nociceptor DOI
Xiaoqi Li, Jianbo Jiang, Guangyu Liu

et al.

Journal of Materials Science Materials in Electronics, Journal Year: 2024, Volume and Issue: 35(24)

Published: Aug. 1, 2024

Language: Английский

Citations

1
In-sensor computing using Ti3C2Tx MXene memristor crossbar arrays for wearable electronics DOI
Jeny Gosai, Mansi Patel,

Anjalee Gosai

et al.

Flexible and Printed Electronics, Journal Year: 2024, Volume and Issue: 9(4), P. 045013 - 045013

Published: Dec. 1, 2024

Abstract The potential of memristor systems in sensing, storing, and processing signals make them highly efficient ideal for power-efficient, comfortable wearable in-sensor computing applications. In this work, we demonstrate a 3 × crossbar array based on Ti C 2 T x MXene with non-volatile characteristics, exhibiting an ON/OFF ratio ∼10 . This -based also showcases remarkable synaptic properties. Additionally, achieve near perfect accuracy pattern training after just 9 epochs as well retaining ability even 24 h. A notable feature these arrays is their to integrate storage, capabilities, demonstrated real-time muscle monitoring healthcare device. multi-channel surface electromyography data was recorded using the MXene-based track forearm movements during series distinct hand gestures. These findings open up exciting possibilities development adaptable flexible memristive arrays, which hold great promise advanced neuromorphic computing,

Language: Английский

Citations

0