Results 161 to 170 of about 2,073,401 (194)
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
Interlayer sliding in the RuO2Zn2F2 bilayer induces ferroelectricity and enables reversible valley polarization switching. The electric dipole and valley‐resolved band edges are intimately coupled, revealing sliding ferroelectricity as a powerful mechanism for electrical control of valley degrees of freedom in 2D materials.
Djamel Bezzerga +3 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
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
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
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
Two‐dimensional CuInP2S6 nanosheets are incorporated into a P(VDF‐TrFE) matrix to induce polarization‐cooperative ferroelectric coupling. The resulting P(VDF‐TrFE)/CuInP2S6 hybrid film exhibits reinforced ferroelectric ordering and reduced coercive electric fields compared with pristine P(VDF‐TrFE).
Yeonsu Jeong +10 more
wiley +1 more source
Conjugated poly(imide dioxime)‐based microspheres establish a radiometal coordination‐driven conformational interlocked network with ultra‐high radiostability. This platform enables low‐temperature, multi‐radionuclide labeling for SPECT/PET/MRI imaging and radionuclide therapy. Mechanistic insights from EXAFS and DFT reveal enhanced stability, while in
Xiao Xu +10 more
wiley +1 more source
Continuous‐Flow Microfluidic Synthesis Enhances C2+ Selectivity for Cu2O Catalysts
Microfluidic devices are used to prepare Cu2O nanoparticles under laminar flow conditions, which exhibit enhanced selectivity in the CO2‐to‐C2+ reaction due to their nanoporosity and high defect concentration. Cu2O prepared using standard solution methods displays decreased CO2‐to‐C2+ selectivity due to the absence of similar properties. Altogether, we
Carlota Casas +16 more
wiley +1 more source
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen +12 more
wiley +1 more source

