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

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: March 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

Language: Английский

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Understanding negative-bias-stress-induced instability and hump phenomenon in amorphous In–Ga–Zn–O thin-film transistors: Impact of source/drain contacts and carrier diffusion

Journal of Applied Physics, Journal Year: 2025, Volume and Issue: 137(18)

Published: May 8, 2025

Reliability and stability of oxide thin-film transistors (TFT) are a longstanding unsettled research topic critical for practical device applications. This work discussed negative gate bias stress (NBS)-induced instability, including the bias-induced hump phenomenon amorphous In–Ga–Zn–O (a-IGZO)-TFT. To identify key factors contributing to NBS we quantitatively evaluated lateral electron diffusion behavior in a-IGZO channel by transmission line method (TLM) analysis developed length scale model. The effective source/drain (S/D) contact (2LD) was extracted, where carrier distribution (ne) profiles were depicted, showing that nLD ∼6.5 × 1017 cm−3. LD 3%–5% proportional maximum extra-carrier spreading (LC) from S/D extension region into channel, affected >20% each side area, made significant impacts on TFT stability. model successfully explained notable threshold (Vth) roll-off characteristics mobility variations shorter-channel devices. Short-term long-term tests found short-channel devices with 5 μm exhibited large Vth shifts accompanied broadened hysteresis window due LC influence. Based proposed model, NBS-induced instability attributed formation highly conductive back-channel layer originating accumulation extension. study provided quantitative insight microscopic changes understanding bias-instability development stable oxide-TFTs.

Language: Английский

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Neuromorphic Light‐Responsive Organic Matter for in Materia Reservoir Computing

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 13, 2025

Abstract Materials able to sense and respond external stimuli by adapting their internal state process store information, represent promising candidates for implementing neuromorphic functionalities brain‐inspired computing paradigms. In this context, systems based on light‐responsive materials enable the use of light as information carrier, allowing emulate basic functions human retina. work it is demonstrated that optically‐induced molecular dynamics in azopolymers can be exploited neuromorphic‐type data processing analog domain at matter level (i.e., materia ). Besides showing storage, adaptiveness these enables implementation synaptic including short‐term memory, long‐term visual memory. Results show allow event detection motion perception, enabling physical schemes requiring real‐time analysis spatio‐temporal inputs. Furthermore, shown light‐induced unconventional paradigm denoted reservoir computing. This underscores potential developing adaptive, intelligent photo‐responsive mimic some complex abilities biological systems.

Language: Английский

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InGaZnO Optoelectronic Synaptic Transistor for Reservoir Computing and LSTM‐Based Prediction Model

Advanced Optical Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 12, 2025

Abstract This study presents a reservoir computing (RC) system utilizing an indium gallium zinc oxide (IGZO)‐based optoelectronic synaptic transistor (OST) for neuromorphic applications. The proposed IGZO‐based OST harnesses the effects of persistent photoconductivity in IGZO channel and charge trapping at IGZO/tantalum interface to emulate short‐term behavior. By optical stimuli, device achieves dynamic states with nonlinear time‐dependent characteristics, enhancing its capability temporal data processing. Moreover, effectively performs pattern recognition tasks, attaining high classification accuracies 95.75% 85.02% on MNIST Fashion datasets, respectively. Additionally, replicates nociceptive behaviors, such as allodynia hyperalgesia, under stimulation, showcasing potential bio‐inspired sensory An LSTM‐based prediction model is developed using Jena climate data, incorporating method that mimics weight variation assess impact performance. approach demonstrates feasibility hardware‐friendly neural networks via biologically inspired adjustments, outperforming conventional forecasting models. Notably, normalized root mean square error (NRMSE) low 0.0145, highlighting accuracy.

Language: Английский

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A Violet‐Light‐Responsive ReRAM Based on Zn₂SnO₄/Ga₂O₃ Heterojunction as an Artificial Synapse for Visual Sensory and In‐Memory Computing

Advanced Electronic Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 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.

Language: Английский

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All-optically Controlled Memristive Device Based on Cu2O/TiO2 Heterostructure Toward Neuromorphic Visual System

Research, Journal Year: 2024, Volume and Issue: 8

Published: Dec. 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

Language: Английский

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

ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 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.

Language: Английский

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

Materials Chemistry and Physics, Journal Year: 2024, Volume and Issue: 329, P. 130107 - 130107

Published: Nov. 7, 2024

Language: Английский

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

ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 2, 2024

To emulate a visual perception system, bismuth telluride (Bi

Language: Английский

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Emerging materials for resistive switching memories: Prospects for enhanced sustainability and performance for targeted applications

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

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