All-optically Controlled Memristive Device Based on Cu2O/TiO2 Heterostructure Toward Neuromorphic Visual System DOI Creative Commons
Jun Xie, Xuanyu Shan,

Nanzhi Zou

и другие.

Research, Год журнала: 2024, Номер 8

Опубликована: Дек. 27, 2024

The optoelectronic memristor integrates the multifunctionalities of image sensing, storage, and processing, which has been considered as leading candidate to construct novel neuromorphic visual system. In particular, memristive materials with all-optical modulation complementary metal oxide semiconductor (CMOS) compatibility are highly desired for energy-efficient perception. As a p-type material, Cu

Язык: Английский

Enhanced In-Sensor Computing with Spike Number-Dependent Plasticity Characteristics in an InGaSnO Optical Neuromorphic Device for Accelerating Machine Vision DOI
Min Ho Park,

Yeo Jin Kim,

Min Jung Choi

и другие.

ACS Nano, Год журнала: 2025, Номер unknown

Опубликована: Март 27, 2025

In-sensor computing systems based on optical neuromorphic devices have attracted increasing attention to improve the efficiency and accuracy of machine vision systems. However, most materials used in exhibit spike timing-dependent plasticity (STDP) behavior response input light signals, leading complex in-sensor reduced accuracy. To address this issue, we introduce an indium gallium tin oxide (IGTO) semiconductor designed enhance number-dependent (SNDP) signals while eliminating STDP behavior. Here, IGTO-based device shows enhanced SNDP characteristics, which are attributed strong Sn–O bonding, as verified by photoemission spectroscopy (PES) analysis. The consistently reaches same conduction state after 8 pulses regardless pulse timing also achieves a number even when 15 different sets applied. These results characteristics device. Notably, with SNDP-enhanced reduces multilayer perceptron (MLP) training time 87.7% achieving high classification This study demonstrates that significant potential accelerate learning for highly efficient

Язык: Английский

Процитировано

0

A Violet‐Light‐Responsive ReRAM Based on Zn2SnO4/Ga2O3 Heterojunction as an Artificial Synapse for Visual Sensory and In‐Memory Computing DOI Creative Commons
Saransh Shrivastava,

Wei‐Sin Dai,

Stephen Ekaputra Limantoro

и другие.

Advanced Electronic Materials, Год журнала: 2024, Номер unknown

Опубликована: Окт. 9, 2024

Abstract Due to the imitation of neural functionalities human brain via optical modulation resistance states, photoelectric resistive random access memory (ReRAM) devices attract extensive attraction for synaptic electronics and in‐memory computing applications. In this work, a ReRAM (PSR) structure ITO/Zn 2 SnO 4 /Ga O 3 /ITO/glass with simple fabrication process is reported imitate plasticity. Electrically induced long‐term potentiation/depression (LTP/D) behavior indicates fulfillment fundamental requirement artificial neuron devices. Classification three‐channeled images corrupted different levels (0.15–0.9) Gaussian noise achieved by simulating convolutional network (CNN). The violet light (405 nm) illumination generates excitatory post current (EPSC), which influenced persistent photoconductivity (PPC) effect after discontinuing excitation. As an device, PSR able some basic functions such as multi‐levels linearly increasing trend, learning‐forgetting‐relearning behavior. same device also shows emulation visual persistency optic nerve skin‐damage warning. This executes high‐pass filtering function demonstrates its potential in image‐sharpening process. These findings provide avenue develop oxide semiconductor‐based multifunctional advanced systems.

Язык: Английский

Процитировано

0

A novel approach for tool-narayanaswamy-moynihan model parameter extraction using multi-scale neural model DOI Creative Commons

Marek Pakosta,

Petr Doležel, Roman Svoboda

и другие.

Materials Chemistry and Physics, Год журнала: 2024, Номер 329, С. 130107 - 130107

Опубликована: Ноя. 7, 2024

Язык: Английский

Процитировано

0

Visible-Light-Stimulated Optoelectronic Neuromorphic Transistor Based on Indium–Gallium–Zinc Oxide via Bi2Te3 Light Absorption Layer DOI

Hyung Tae Kim,

Dong Hyun Choi, Min Seong Kim

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер unknown

Опубликована: Дек. 2, 2024

To emulate a visual perception system, bismuth telluride (Bi

Язык: Английский

Процитировано

0

Pseudologic Optical Circuit Method for Advanced Color Sensing in IGZO Phototransistor Arrays with Chlorophyll Absorption Layers DOI

Hyunji Son,

Dong Hyun Choi, Kyung-Ho Park

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер unknown

Опубликована: Дек. 2, 2024

Recently, the elimination of color filters has become a key focus in photodetector research because potential to create more compact and cost-effective sensor systems. In this study, novel concept filter-free color-discrimination photosensor using an indium gallium zinc oxide (IGZO, In/Ga/Zn = 3.1:2.6:1.0)-based phototransistor with integrated chlorophyll absorption layer (CAL) solution-processed (SAL) was developed. Chlorophyll, known for its role photosynthesis as natural light absorber, offers distinct characteristics compared conventional photodetectors (i.e., SAL/IGZO), whereby photoresponsivity decreases increasing wavelength. Using ability absorb blue red light, proposed CAL/IGZO exhibited higher than green light. The device achieved 1570 A/W 681 photosensitivity 8.35 × 105 8.96 104 detectivity 8.47 1011 6.80 1010 Jones, respectively, under illumination intensity 1 mW/mm2. Furthermore, by integrating SAL/IGZO phototransistor, which different order photoresponse across RGB wavelengths, innovative pixel pseudologic circuit successfully capability distinguish colors various intensities validated through experimental data SPICE simulations, output voltage ranges confirmed −2.61 −3.51 V red, 1.56 2.69 green, −0.22 −0.68 over from 0.1 3 This approach allows effective detection without filters, providing advanced solution photodetection technologies.

Язык: Английский

Процитировано

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

и другие.

APL Energy, Год журнала: 2024, Номер 2(4)

Опубликована: Дек. 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.

Язык: Английский

Процитировано

0

All-optically Controlled Memristive Device Based on Cu2O/TiO2 Heterostructure Toward Neuromorphic Visual System DOI Creative Commons
Jun Xie, Xuanyu Shan,

Nanzhi Zou

и другие.

Research, Год журнала: 2024, Номер 8

Опубликована: Дек. 27, 2024

The optoelectronic memristor integrates the multifunctionalities of image sensing, storage, and processing, which has been considered as leading candidate to construct novel neuromorphic visual system. In particular, memristive materials with all-optical modulation complementary metal oxide semiconductor (CMOS) compatibility are highly desired for energy-efficient perception. As a p-type material, Cu

Язык: Английский

Процитировано

0