Results 191 to 200 of about 15,638,936 (259)

Metasurface‐Based Multidimensional Light‐Field Manipulation: From Technologies to Applications

open access: yesAdvanced Science, EarlyView.
Multidimensional metasurfaces enable versatile manipulation of multiple optical degrees of freedom, including phase, amplitude, polarization, wavelength, and orbital angular momentum. This review summarizes their fundamental mechanisms, emerging strategies for multidimensional light‐field control, and key applications in optical computing, imaging ...
Heliang Yin   +6 more
wiley   +1 more source

Advances in Josephson Junction Materials and Processes Toward Practical Quantum Computing

open access: yesAdvanced Science, EarlyView.
Emerging materials for quantum computing, including crystalline materials, two‐dimensional van der Waals materials, two‐dimensional electron gas systems, ferromagnets, and unconventional (e.g., d‐wave) superconductors, offer opportunities to engineer next‐generation Josephson junctions.
Hyunseong Kim   +11 more
wiley   +1 more source

Highly Linear Perovskite Synapses for Neuromorphic Computing

open access: yesAdvanced Science, EarlyView.
Voltage spikes applied to an Au/ACI‐phase perovskite/ITO memristor emulate the ionic signaling of a biological synapse, generating a tunable postsynaptic current. The vertically aligned perovskite film confines iodide‐vacancy migration, enabling highly linear, and symmetric conductance updates with 100 states and 5.5 aJ per event. Such synapses sustain
Zhongwen Sun   +7 more
wiley   +1 more source

Illumination‐Dependent Interfacial Recombination in Perovskite Photovoltaics Driven by Trap States in Metal Oxide Electron Transport Layers

open access: yesAdvanced Science, EarlyView.
Changes in light intensity impact trap states introduced at the metal oxide/perovskite interface. Comparing SnO2, TiO2 and ZnO electron transport layers reveals high interfacial trapping and recombination under high‐light, while bulk defects become more dominant under low‐light.
Tianhao Lan   +6 more
wiley   +1 more source

Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons

open access: yesAdvanced Science, EarlyView.
Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
wiley   +1 more source

Home - About - Disclaimer - Privacy