Results 151 to 160 of about 3,191,545 (316)

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

Substrate Stress Relaxation Regulates Cell‐Mediated Assembly of Extracellular Matrix

open access: yesAdvanced Functional Materials, EarlyView.
Silicone‐based viscoelastic substrates with tunable stress relaxation reveal how matrix mechanics regulates cellular mechanosensing and cell‐mediated matrix remodelling in the stiff regime. High stress relaxation promotes assembly of fibronectin fibril‐like structures, increased nuclear localization of YAP and formation of β1 integrin‐enriched ...
Jonah L. Voigt   +2 more
wiley   +1 more source

Magnetic Control of Chiral Hybridized Phonon Magnetic Moments in Ferrimagnets Fe2‐xZnxMo3O8

open access: yesAdvanced Functional Materials, EarlyView.
Helicity‐resolved magneto‐Raman spectroscopy reveals magnetic control of chiral phonon magnetic moments in polar ferrimagnet (ZnxFe2−xMo3O₈). Large spontaneous zero‐field phonon splittings, selective phonon–magnon coupling, and asymmetric Zeeman responses demonstrate that phonon chirality is governed by magnon‐phonon coupling and magnetization.
Youngsu Choi   +8 more
wiley   +1 more source

THE CONLEY ATTRACTORS OF AN ITERATED FUNCTION SYSTEM

open access: yesBulletin of the Australian Mathematical Society, 2013
M. Barnsley, A. Vince
semanticscholar   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

ON A CERTAIN GENERALISATION OF THE ITERATED FUNCTION SYSTEM

open access: yesBulletin of the Australian Mathematical Society, 2012
F. Strobin, J. Swaczyna
semanticscholar   +1 more source

Slight Truncation Changes in Iron Oxide Nanocubes Strongly Affect Their Magnetic Properties

open access: yesAdvanced Functional Materials, EarlyView.
Subtle variations in nanoparticle morphology can lead to significant changes in functional properties. An automated shape‐fitting method captures minor differences in corner truncation between iron oxide nanocubes of similar sizes synthesized under identical conditions, revealing pronounced disparities in their magnetic and hyperthermia behavior ...
Kingsley Poon   +7 more
wiley   +1 more source

Circular‐Polarization‐Sensitive Organic Photodetectors with a Chiral Nanopatterned Electrode Inverse‐Designed by Genetic Algorithm

open access: yesAdvanced Functional Materials, EarlyView.
A chiral photodetector capable of selectively distinguishing left‐ and right‐handed circularly polarized light is experimentally demonstrated. The device, which features a nanopatterned electrode inverse‐designed by a genetic algorithm within a metal–dielectric–metal nanocavity that incorporates a vacuum‐deposited small‐molecule multilayer, exhibits ...
Kyung Ryoul Park   +3 more
wiley   +1 more source

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