Results 101 to 110 of about 7,731 (250)

Electrically Coded Retinomorphic Spectrophotodetector

Advanced Materials, EarlyView.
Self‐powered retinomorphic pyro‐photodetector is demonstrated that avoids machine‐learning post‐processing and covers 365–940 nm. Electrostatic balancing of built‐in potential produces an electrical wavelength code, delivering <3 nm wavelength decoding accuracy with ∼46 µs response.
Mohit Kumar, Hyunmin Dang, Hyungtak Seo
wiley   +1 more source

Charge‐Encoded Sidechains Enable Deterministic Ion Ingress and Memory Retention in Organic Electrochemical Synaptic Transistors

Advanced Materials, EarlyView.
Organic electrochemical synaptic transistors based on sidechain‐engineered conjugated polyelectrolytes reveal that cationic sidechains enable efficient volumetric ion penetration and dense backbone doping, leading to enhanced transconductance and long‐term synaptic retention.
Haim Kwon, Jihyeon You, Chaeyeon Park, Dong Gue Roe, Ji Hyun Jung, Jeong Ho Cho, Han Young Woo   +6 more
wiley   +1 more source

Metal Oxide Nano‐Interface Boosting the Deep Ultraviolet Adjustable Noise‐Filtering In‐Sensor Computing

Advanced Materials, EarlyView.
We show that sol‐gel‐fractured indium–magnesium oxide combines deep‐ultraviolet responsivity, high carrier mobility, and an excellent memory dynamic range. This unique materials platform enables deep‐ultraviolet long‐afterglow light‐emitting devices with multifunctional integration.
Zhongshi Ju, Peng Li, Jingsong Yuan, Boyuan Yu, Bin Han, Yusheng Chen, Jiangang Ma, Haiyang Xu, Yichun Liu, Paolo Samorì   +9 more
wiley   +1 more source

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Chemically Engineered GaN Thin Films for Light‐Stimulated Artificial Synapses

Advanced Photonics Research
The conventional von Neumann architecture is increasingly losing the capacity to satisfy the urgent demand for high‐speed parallel computing, energy efficiency, and ultralow power consumption owing to the rapid growth of information.
Xiaoqin Yang, Jiawen Lu, Luyu Zhao, Xiaorui Han, Zhongwei Bai, Peiwen Quan, Liangshuai Xie, Liang Li, Haoxuan Sun, Mark Hermann Rummeli, Bingcheng Luo, Hong Gu   +11 more
doaj   +1 more source

Understanding Interfacial Photoswitching Mechanisms in Atomically‐Thin TMD‐Spiropyran Hybrids

Advanced Materials Technologies, EarlyView.
Photochromic molecules can effectively modulate the optoelectronic properties of atomically thin transition metal dichalcogenide semiconductors. Spiropyran that switches its chemical configuration upon alternating UV and visible irradiation enables light‐programmable optoelectronic devices.
Sewon Park, Jaehoon Ji, Michael Brophy, John Audi, Jean Rouillon, Carlos Benitez‐Martin, Joakim Andréasson, Jeong Ho You, Jong Hyun Choi   +8 more
wiley   +1 more source

2D Materials Powering Neuromorphic Intelligence

Nano-Micro Letters
Highlights Two-dimensional materials enable energy-efficient neuromorphic computing through gate tuneable bandgaps, fast switching kinetics, and compatibility with spiking neural networks for adaptive learning.
Jamal Kazmi, Waqas Ahmad, Muhammad Naqi, Yawar Abbas, Aumber Abbas, Peijian Wang, Mohd Ambri Mohamed, Federico Rosei, Zhiming M. Wang, Hongwei Song   +9 more
doaj   +1 more source

Stochastic Computing for Neuromorphic Applications [PDF]

IEEE Design & Test, 2021
openaire   +1 more source

Neuromorphic Photonic On-chip Computing

Chips
Drawing inspiration from biological brain&#039;s energy-efficient information-processing mechanisms, photonic integrated circuits (PIC) have facilitated the development of ultrafast artificial neural networks. This in turn is envisaged to offer potential solutions to the growing demand for artificial intelligence employing machine learning in ...
Sujal Gupta, Jolly Xavier
openaire   +1 more source