Results 241 to 250 of about 7,102,101 (318)

Innovative Processing of Compacted Waste Aluminum Alloy Powders via Controlled Remelting and Solidification

open access: yesAdvanced Engineering Materials, EarlyView.
This study demonstrates an efficient recycling route for out‐of‐spec AlSi10Mg atomized powders through compaction and arc remelting followed by suction casting. By correlating compaction load, cooling rate, and resulting microstructure, we show that intermediate pressures (50–80 kN) and rapid cooling refine dendrites, reduce porosity, and enhance ...
Mila Christy de Oliveira   +4 more
wiley   +1 more source

Concordance evaluation of a nutrition self-assessment app and clinical experts in estimating energy requirements and deficits among ONS consumers.

open access: yesAsia Pac J Clin Nutr
Zhu C   +11 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

Thermal Utilization on Chip. [PDF]

open access: yesLight Sci Appl
Zhang Y   +8 more
europepmc   +1 more source

A Compact Spin‐Coated Graphene UWB Antenna for Breast Tumor Detection

open access: yesAdvanced Engineering Materials, EarlyView.
A compact, spin‐coated graphene ultra‐wideband patch antenna designed for breast tumor detection, capable of distinguishing between malignant and benign tumors. This innovative antenna can serve as an effective initial screening tool, particularly in resource‐limited settings such as rural areas, where access to advanced medical equipment like MRI and ...
Raja Rashidul Hasan   +9 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

open access: yesAdvanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky   +5 more
wiley   +1 more source

Home - About - Disclaimer - Privacy