Results 131 to 140 of about 11,832,712 (294)

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

Seven novel KIT mutations in horses with white coat colour phenotypes

, 2009
White coat colour in horses is inherited as a monogenic autosomal dominant trait showing a variable expression of coat depigmentation. Mutations in the KIT gene have previously been shown to cause white coat colour phenotypes in pigs, mice and humans. We
Rieder, S., Burger, D., C. Penedo, P.‐A. Poncet, Brooks, S.A., Penedo, C., Tozaki, T., B. Haase, T. Hasegawa, T. Leeb, Hasegawa, T., S. A. Brooks, Leeb, Tosso, T. Tozaki, S. Rieder, Poncet, P.A., D. Burger, Haase, Bianca   +17 more
core   +1 more source

The Dirty White Coat

, 2018
Learning Objectives: Review the potential germs spread by our white coat To think about how we could limit the spread of germs/contamination To review the selected article critically Determine the relevance of our practice and us as physicians To ...
Reaves, MD, Bruce
core   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

Electrochemical Behavior of Flame‐Sprayed Sc‐Doped AlCoCrFeMo High‐Entropy Alloy Coatings in 3.5% Sodium Chloride Solution

Advanced Engineering Materials, EarlyView.
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar, Akash Vyas, Mohammad Aatif Qazi, Nashit Jalal, Maria Ophelia Jarligo, Mostafa Yakout, Jing Liu, André McDonald   +7 more
wiley   +1 more source

Crimplene Coat

, 2010
Blue and beige striped Crimplene coat. Label: Cotsmoor of London. Maker: Cotsmoor of London. Date: 1970 (circa) - from the The Betty Smithers Design Collection at Staffordshire University.
The Betty Smithers Design Collection at Staffordshire University, Staffordshire University   +1 more
core  

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Letter from Herbert White

, 2012
Letters from Herbert White to his ...
White, Herbert Martin
core  

white coat

white aThe young one is the...is the white coat - pup; when 'tis... 'tis pupped 'tis call...'tis called a pup. Well then after she gets nursed a little bit she begins to perk up an' she...she got a beautiful coat on it.

core   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source