Results 221 to 230 of about 2,690,059 (295)

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

Elinvar Materials: Recent Progress and Challenges

open access: yesAdvanced Engineering Materials, EarlyView.
Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley   +1 more source

Packaging of Macroscopic Material Payloads: Needs, Challenges, Concepts, and Future Directions

open access: yesAdvanced Engineering Materials, EarlyView.
This review introduces a unified framework that decomposes any macroscopic packaging system into the payload, packaging material, and packaging strategy and combines them into a conceptual packaging equation: packaging strategy = payload + packaging material.
Venkata S. R. Jampani, Manos Anyfantakis
wiley   +1 more source

Synthesis of a Novel Thermoresponsive S53P4 Bioactive Glass Extract–Poloxamer 407 Injectable Hydrogels: Assessment of Biocompatibility and Antimicrobial Properties

open access: yesAdvanced Engineering Materials, EarlyView.
This study investigates innovative thermoreversible hydrogels derived from S53P4 bioactive glass extracts to aid in the healing of infected diabetic foot wounds. These injectable gels, which gel at body temperature, release beneficial ions and remain stable over time.
Marian G. Vargas Guerrero   +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

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