Results 241 to 250 of about 9,002 (304)
An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
Hootation: A GUI and API library for ontology validation and verbalization. [PDF]
Amith M +10 more
europepmc +1 more source
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 +6 more
wiley +1 more source
Development and usability evaluation of training equipment for syringe-based wound irrigation education. [PDF]
Han J, Yang B, Lee K.
europepmc +1 more source
Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari +3 more
wiley +1 more source
Unsupervised Classification of English Words Based on Phonological Information: Discovery of Germanic and Latinate Clusters. [PDF]
Morita T, O'Donnell TJ.
europepmc +1 more source
A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
Fall-from-Bed Risk Prediction Using Physics-Based Bed Simulation. [PDF]
Kim J +8 more
europepmc +1 more source
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 +4 more
wiley +1 more source

