Results 141 to 150 of about 2,775,539 (295)

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

Advanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Vincenzo Galdi   +4 more
wiley   +1 more source

The Cartesian Product and Join Graphs on Edge-Version Atom-Bond Connectivity and Geometric Arithmetic Indices. [PDF]

Molecules, 2018
Zhang X, Jiang H, Liu JB, Shao Z.
europepmc   +1 more source

Broadband Near‐Field Computational Microwave Imaging Enabled by Nonperiodic Dispersive Unit‐Cell Loading in a Passive Metasurface

Advanced Electronic Materials, EarlyView.
A compact passive engineered surface converts changes in microwave frequency into many distinct illumination patterns, allowing nearby objects to be imaged without mechanical scanning, active tuning, or a large antenna array. Operating from 18 to 28 GHz, the single‐port system uses measured field patterns to reconstruct metallic targets and distinguish
Mohammed H. Arif, Firas Slewa Dawod, Henrik Jansen, Caner Kadıoğlu, Sayan Roy, Dirk Heberling, Renato Negra   +6 more
wiley   +1 more source

Investigation on the Impact of Memristive Device Variability on Uncoupled Memristive Cellular Nonlinear Networks

Advanced Electronic Materials, EarlyView.
Memristors, nanoscale devices that compute and store data in the same place, promise compact, energy‐efficient image‐processing hardware, yet no two devices behave exactly alike. Simulations based on real device measurements show that a 256‐cell memristive cellular nonlinear network (M‐CellNN) detects image edges perfectly despite this variability and ...
Salwa Yasmeen Neyaz, Kristoffer Schnieders, Yongmin Wang, Alon Ascoli, Ioannis Messaris, Ronald Tetzlaff, Vasileios Ntinas, Ricardo Carmona Galán, Stefan Wiefels, Vikas Rana, Stephan Menzel   +10 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

On the δ-chromatic numbers of the Cartesian products of graphs

Open Mathematics
In this work, we study the δ\delta -chromatic number of a graph, which is the chromatic number of the δ\delta -complement of a graph. We give a structure of the δ\delta -complements and sharp bounds on the δ\delta -chromatic numbers of the Cartesian ...
Tangjai Wipawee, Pho-on Witsarut, Vichitkunakorn Panupong   +2 more
doaj   +1 more source

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

Advanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho, Siwar Ben Hadj Ali, Maxence Desnoyers, Francisco Fernandez, Nassima Benammar, Alejandro A. Franco   +5 more
wiley   +1 more source

Quadrilateral embeddings of cartesian product graphs [PDF]

, 2016
Quadrilateral embeddings of cartesian product graphs were first investigated by White and others as part of work on representing groups in surfaces using their Cayley graphs. Later the problem was studied in more generality. A number of important results
Ellingham, Mark
core  

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source