Results 241 to 250 of about 157,436 (316)

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Hybrid Feature Learning for Wearable Stress Detection: Combining Domain Knowledge with Supervised Deep Learning. [PDF]

Sensors (Basel)
Birkenmaier D, Kanuganti SR, Stork W.
europepmc   +1 more source

Carboxylic‐Acid Functionalized Multiwalled Carbon Nanotube‐Alkane‐Based Resistive Temperature Sensor for Cold Chain Applications

Advanced Engineering Materials, EarlyView.
This study presents a reversible temperature sensor with high switching ratio, ∼103. The device is fabricated using PET‐ITO and carbon nanotube dispersions in alkane. Considering its application in cold chain logistics, a proof‐of‐concept with LED is showcased. Thus, a temperature drop below the threshold temperature (crystallization temperature of the
Sunil Kumar Behera, Philippe Marrec, A. Jorge Parola, Madalena Dionísio, Hugo Águas, Andreia F. M. Santos, Hamed Pourkheirollah, Donald Lupo, César A. T. Laia   +8 more
wiley   +1 more source

Fault Detection and Isolation of MEMS IMU Array Based on WOA-MVMD-GLT. [PDF]

Micromachines (Basel)
Li H, Sun F, Tian J, He X, Zhu T.
europepmc   +1 more source

Low‐Cost, Large‐Scale Nanoporous Metals by Mechanical Alloying, Oxide Reduction, and Dealloying of Powders

Advanced Engineering Materials, EarlyView.
Powder metal processing provides scalable advantages in nanoporous (np) metal development. Mechanical alloying is used to produce unique precursors for hybrid nanopore formation by oxide reduction and dealloying. As demonstrated in np Ag, this approach improves process efficiency while promoting smaller ligaments and larger pores, both of which are ...
Mark A. Atwater, Oliver A. Fowler
wiley   +1 more source

A Multi-Scale Edge-Preserving Decomposition and Fusion Framework for Multi-Polarization Passive Millimeter-Wave Imaging. [PDF]

Sensors (Basel)
Chen X, Hu F, Zhu D, Su J, Fang B, Tao J.   +5 more
europepmc   +1 more source

Planar Solid‐State Nanopores Toward Scalable Nanofluidic Integration Based on CMOS Technology

Advanced Engineering Materials, EarlyView.
We present a scalable silicon‐based fabrication strategy for planar solid‐state nanopores to enable their integration with complex nanofluidic systems. Prototype devices demonstrate normal voltage‐current characteristics, good noise performance, and appreciable streaming currents. Our CMOS‐compatible fabrication process offers precise geometric control
Ngan Hoang Pham, Chenyu Wen, Mohammad Hadi Khaksaran, Won‐Yong Lee, Javier Cruz, Klas Hjort, Dongping Wu, Shi‐Li Zhang   +7 more
wiley   +1 more source

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging. [PDF]

Biomed Signal Process Control
Huang L, Yin J, Zhang J, Lok UW, DeRuiter RM, Jin J, Knoll KM, Petersen KE, Krier JD, Zhu XY, Hesley GK, Robinson KA, Bentall AJ, Atwell TD, Rule AD, Lerman LO, Chen S, Huang C.   +17 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced 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, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source