Results 121 to 130 of about 2,424,657 (202)
Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen +9 more
wiley +1 more source
Retina‐Inspired Bi‐Based Terahertz Photonic Neuromorphic Devices
Combined with effective band alignment and substrate engineering, bismuth materials are introduced to form terahertz photonic bio‐inspired devices with picosecond short‐term plasticity to enable multi‐scene visual perception. Thus obtained hardware through the terahertz optical neural network (THz‐ONN) demonstrates high recognition accuracy, providing ...
Pujing Zhang +14 more
wiley +1 more source
WS2‐based in‐memory sensing reservoir computing integrates sensing, memory, and computation in one compact device. It achieves ∼94% N‐MNIST, ∼93% eye motion perception, and ∼89% speech recognition with ultra‐low energy (∼25.5 fJ/spike). The system shows stability at 95% humidity, endurance over 1.5M cycles, and supports synaptic plasticity, enabling ...
Dayanand Kumar +9 more
wiley +1 more source
Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley +1 more source
Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung +7 more
wiley +1 more source
Neuromorphic engineering in wetware: the state of the art and its perspectives
P. Gentili, Maria Zurlo, Pasquale Stano
semanticscholar +1 more source
Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh +8 more
wiley +1 more source
Unconventional Hysteretic Charge Filling in Moiré‐Reconstructed Helical Trilayer Graphene
In helical trilayer graphene, sequential twisting reconstructs the moiré landscape into periodic domains separated by aperiodic boundaries. Longitudinal transport reveals sweep‐direction‐dependent hysteresis, while the Hall response traces this behavior to hysteretic charge filling at the aperiodic boundaries.
Hangyeol Park +9 more
wiley +1 more source
Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates
ABSTRACT Biological plasticity refers to the ability of synapses to strengthen or weaken over time. These adaptive properties play a fundamental role in learning and memory, spanning many orders of magnitude in timescales. Short‐term plasticity (STP) arises from rapid correlative activity, while long‐term plasticity (LTP) is governed by slower ...
Ranjan Kumar Patel +8 more
wiley +1 more source
Reconfigurable Selector‐Only Memory (SOM) for Scalable Neuromorphic Computing
ABSTRACT Highly scalable reconfigurable neuromorphic devices are critical for addressing continual‐learning challenges in artificial intelligence. However, the scalability of existing reconfigurable devices is severely constrained by limited operating margins and insufficient process maturity.
Jin‐Yu Wen +7 more
wiley +1 more source

