Results 151 to 160 of about 36,624 (293)

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

open access: yesAdvanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

On the number of lines tangent to four convex polyhedra.

open access: yes, 2002
We prove that, under a certain general position assumption, the number of lines tangent to four bounded disjoint convex polyhedra in $\Real^3$ with a total of $n$ edges is $O(n^2)$. Under the same assumption, we show that a set of $k$ bounded disjoint convex polyhedra has at most $O(n^2k^2)$ lines, possibly occluded, that are tangent to four of these ...
Brönnimann, Hervé   +8 more
openaire   +2 more sources

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

open access: yesAdvanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith   +4 more
wiley   +1 more source

Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses

open access: yesAdvanced Electronic Materials, EarlyView.
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol   +7 more
wiley   +1 more source

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

open access: yesAdvanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun   +5 more
wiley   +1 more source

High‐Performance Noble‐Metal‐Free Perovskite Solar Cells Enabled by MoOX/Cr/Al Multilayer Electrodes

open access: yesAdvanced Energy Materials, EarlyView.
Cost‐effective perovskite solar cells (PSCs) are developed using a noble‐metal‐free MoOX/Cr/Al multilayer electrode. The devices achieve a power conversion efficiency (PCE) of 25.6%, competitive with that of Au‐based devices (26.3%), and a 25.5 cm2 mini‐module shows 21.3% PCE.
Wooyeon Kim   +7 more
wiley   +1 more source

Reliable Evaluation of Na‐Ion Battery Materials: Eliminating Na‐Metal Distortions

open access: yesAdvanced Energy Materials, EarlyView.
Na metal is highly reactive in carbonate electrolytes, forming unstable interphases and triggering parasitic reactions that distort measurements and undermine reproducibility. To enable accurate evaluation of materials for Na‑ion batteries, this work suggests that NASICON‑type counter electrodes provide a practical and stable platform for distortion ...
Jinkwang Hwang   +9 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

open access: yesAdvanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour   +5 more
wiley   +1 more source

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