Reconfigurable Multifunctional van der Waals Ferroelectric Devices and Logic Circuits

ACS Nano, Journal Year: 2023, Volume and Issue: 17(21), P. 21865 - 21877

Published: Oct. 21, 2023

Emerging reconfigurable devices are fast gaining popularity in the search for next-generation computing hardware, while ferroelectric engineering of doping state semiconductor materials has potential to offer alternatives traditional von-Neumann architecture. In this work, we combine these concepts and demonstrate suitability field-effect transistors (Re-FeFETs) designing nonvolatile logic-in-memory circuits with multifunctional capabilities. Modulation energy landscape within a homojunction 2D tungsten diselenide (WSe2) layer is achieved by independently controlling two split-gate electrodes made copper indium thiophosphate (CuInP2S6) layer. Controlling encoded program gate enables switching between p, n, ambipolar FeFET operating modes. The exhibit on-off ratios exceeding 106 hysteresis windows up 10 V width. can change from Ohmic-like diode behavior large rectification ratio 104. When programmed mode, built-in p-n junction electric field efficient separation photogenerated carriers, making device attractive energy-harvesting applications. implementation Re-FeFET logic functions shows how circuit be reconfigured emulate either polymorphic NAND/AND or electronic XNOR long retention time 104 s. We also illustrate design just Re-FeFETs exhibits high expressivity reconfigurability at runtime implement several key 2-input functions. Moreover, demonstrates compactness, an 80% reduction transistor count compared standard CMOS design. van de Waals therefore promising both More-than-Moore beyond-Moore future electronics, particular energy-efficient in-memory machine learning due their multifunctionality compactness.

Language: Английский

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A ferroelectric fin diode for robust non-volatile memory

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Jan. 13, 2024

Abstract Among today’s nonvolatile memories, ferroelectric-based capacitors, tunnel junctions and field-effect transistors (FET) are already industrially integrated and/or intensively investigated to improve their performances. Concurrently, because of the tremendous development artificial intelligence big-data issues, there is an urgent need realize high-density crossbar arrays, a prerequisite for future memories emerging computing algorithms. Here, two-terminal ferroelectric fin diode (FFD) in which capacitor fin-like semiconductor channel combined share both top bottom electrodes designed. Such device not only shows digital analog memory functionalities but also robust universal as it works using two very different materials. When compared all current cumulatively demonstrates endurance up 10 cycles, ON/OFF ratio ~10 2 , feature size 30 nm, operating energy ~20 fJ operation speed 100 ns. Beyond these superior performances, simple structure self-rectifying ~ 4 permit consider them new electronic building blocks designing passive arrays crucial in-memory computing.

Language: Английский

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Emerging 2D Ferroelectric Devices for In‐Sensor and In‐Memory Computing

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

Published: May 13, 2024

Abstract The quantity of sensor nodes within current computing systems is rapidly increasing in tandem with the sensing data. presence a bottleneck data transmission between sensors, computing, and memory units obstructs system's efficiency speed. To minimize latency units, novel in‐memory in‐sensor architectures are proposed as alternatives to conventional von Neumann architecture, aiming for data‐intensive applications. integration 2D materials ferroelectric has been expected build these due dangling‐bond‐free surface, ultra‐fast polarization flipping, ultra‐low power consumption ferroelectrics. Here, recent progress devices in‐sensing neuromorphic reviewed. Experimental theoretical progresses on devices, including passive ferroelectrics‐integrated active reviewed followed by perception, memory, application. Notably, have used simulate synaptic weights, neuronal model functions, neural networks image processing. As an emerging device configuration, potential expand into sensor‐memory application field, leading new possibilities modern electronics.

Language: Английский

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Non-volatile 2D MoS2/black phosphorus heterojunction photodiodes in the near- to mid-infrared region

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 17, 2024

Abstract Cutting-edge mid-wavelength infrared (MWIR) sensing technologies leverage photodetectors, memory units, and computing units to enhance machine vision. Real-time processing decision-making challenges emerge with the increasing number of intelligent pixels. However, current operations are limited in-sensor capabilities for near-infrared technology, high-performance MWIR detectors multi-state switching functions lacking. Here, we demonstrate a non-volatile MoS 2 /black phosphorus (BP) heterojunction photovoltaic detector featuring semi-floating gate structure design, integrating near- mid-infrared photodetection, (PMC) functionalities. The PMC device exhibits property being able store stable responsivity, which varies linearly stored conductance state. Significantly, weights (stable responsivity) can be programmed power consumption as low 1.8 fJ, blackbody peak responsivity reach 1.68 A/W band. In simulation Faster Region convolution neural network (CNN) based on FLIR dataset, hardware 89% mean Average Precision index feature extraction software weights. This detector, its versatile functionalities, holds significant promise applications in advanced object detection recognition systems.

Language: Английский

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Development of Bio‐Voltage Operated Humidity‐Sensory Neurons Comprising Self‐Assembled Peptide Memristors

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(33)

Published: June 15, 2024

Biomimetic humidity sensors offer a low-power approach for respiratory monitoring in early lung-disease diagnosis. However, balancing miniaturization and energy efficiency remains challenging. This study addresses this issue by introducing bioinspired humidity-sensing neuron comprising self-assembled peptide nanowire (NW) memristor with unique proton-coupled ion transport. The proposed shows low Ag

Language: Английский

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New-Generation Ferroelectric AlScN Materials

Nano-Micro Letters, Journal Year: 2024, Volume and Issue: 16(1)

Published: June 25, 2024

Ferroelectrics have great potential in the field of nonvolatile memory due to programmable polarization states by external electric manner. However, complementary metal oxide semiconductor compatibility and uniformity ferroelectric performance after size scaling always been two thorny issues hindering practical application devices. The emerging ferroelectricity wurtzite structure nitride offers opportunities circumvent dilemma. This review covers mechanism domain dynamics AlScN films. optimization films grown different techniques is summarized their applications for memories in-memory computing are illustrated. Finally, challenges perspectives regarding commercial avenue discussed.

Language: Английский

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In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 7, 2025

In-sensor computing has emerged as an ultrafast and low-power technique for next-generation machine vision. However, in situ training of in-sensor systems remains challenging due to the demands both high-performance devices efficient programming schemes. Here, we experimentally demonstrate artificial neural network (ANN) based on ferroelectric photosensors (FE-PSs). Our FE-PS exhibits self-powered, fast (<30 μs), multilevel (>4 bits) photoresponses, well long retention (50 days), high endurance (109), write speed (100 ns), small cycle-to-cycle device-to-device variations (~0.66% ~2.72%, respectively), all which are desirable training. Additionally, a bi-directional closed-loop scheme is developed, achieving precise weight update FE-PS. Using this scheme, ANN FE-PSs trained recognize traffic signs commanding prototype autonomous vehicle. Moreover, operates 50 times faster than von Neumann vision system. This study paves way development with capability, may find applications new data-streaming tasks. in-situ capability promising applications, yet their implementation challenge. authors using photosensors.

Language: Английский

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Reconfigurable and nonvolatile ferroelectric bulk photovoltaics based on 3R-WS2 for machine vision

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 2, 2025

Hardware implementation of reconfigurable and nonvolatile photoresponsivity is essential for advancing in-sensor computing machine vision applications. However, existing essentially depends on the photovoltaic effect p-n junctions, which photoelectric efficiency constrained by Shockley-Queisser limit hinders achievement high-performance photoresponsivity. Here, we employ bulk rhombohedral (3R) stacked/interlayer sliding tungsten disulfide (WS2) to surpass this realize highly reconfigurable, with a retinomorphic device. The device composed graphene/3R-WS2/graphene all van der Waals layered structure, demonstrating wide range from positive negative ( ± 0.92 A W−1) modulated polarization 3R-WS2. Further, integrate system convolutional neural network achieve high-accuracy (100%) color image recognition at σ = 0.3 noise level within six epochs. Our findings highlight transformative potential effect-based devices efficient systems. Gong et al. report in WS2 develop processing based two-terminal 2D layers vertical

Language: Английский

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Two-Dimensional Materials for Brain-Inspired Computing Hardware

Chemical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Recent breakthroughs in brain-inspired computing promise to address a wide range of problems from security healthcare. However, the current strategy implementing artificial intelligence algorithms using conventional silicon hardware is leading unsustainable energy consumption. Neuromorphic based on electronic devices mimicking biological systems emerging as low-energy alternative, although further progress requires materials that can mimic function while maintaining scalability and speed. As result their diverse unique properties, atomically thin two-dimensional (2D) are promising building blocks for next-generation electronics including nonvolatile memory, in-memory neuromorphic computing, flexible edge-computing systems. Furthermore, 2D achieve biorealistic synaptic neuronal responses extend beyond logic memory Here, we provide comprehensive review growth, fabrication, integration van der Waals heterojunctions optoelectronic devices, circuits, For each case, relationship between physical properties device emphasized followed by critical comparison technologies different applications. We conclude with forward-looking perspective key remaining challenges opportunities applications leverage fundamental heterojunctions.

Language: Английский

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Low-power edge detection based on ferroelectric field-effect transistor

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 10, 2025

Language: Английский

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