Results 171 to 180 of about 224,898 (299)

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

open access: yesAdvanced Engineering Materials, EarlyView.
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

Precipitation Simulations of the O‐Phase in Ti2AlNb Alloys Processed by Laser Powder Bed Fusion

open access: yesAdvanced Engineering Materials, EarlyView.
Simulated and experimental evolution of the O‐phase volume fraction during postprocessing of a Ti‐21Al‐25Nb (at.%) alloy processed by laser powder bed fusion. With results of sensitivity to input parameters from a thorough and quantified analysis, the interfacial energy matrix/precipitate is the most relevant input parameter for the simulation of the O‐
Silvana Tumminello   +7 more
wiley   +1 more source

Interpretable, physics-informed learning reveals sulfur adsorption and poisoning mechanisms in 13-atom icosahedra nanoclusters. [PDF]

open access: yesSci Rep
Monteiro RF   +9 more
europepmc   +1 more source

A Dislocation Perspective on Strength and Toughness in Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
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

Atomic Physics [PDF]

open access: yesAmerican Journal of Physics, 1951
Wolfgang Finkelnburg, Ralph B. Bowersox
openaire   +2 more sources

A Novel MSPLL-Based Method for Frequency Synthesis in Hydrogen MASER. [PDF]

open access: yesSensors (Basel)
Simariya D   +7 more
europepmc   +1 more source

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

A prototype differential atom interferometer for fundamental physics. [PDF]

open access: yesNature
Baynham CFA   +92 more
europepmc   +1 more source

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