Results 191 to 200 of about 22,801 (289)

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

On a Problem Concerning Coincidence of Tangent Planes

open access: yesOn a Problem Concerning Coincidence of Tangent Planes
application/pdf ...
openaire  

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

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi   +5 more
wiley   +1 more source

Two-Antenna Gain Measurement Method Using Two UAVs. [PDF]

open access: yesSensors (Basel)
Kandregula VR   +7 more
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy