Results 231 to 240 of about 486,719 (307)

Nondestructive Testing of Welded Composite Metal Foams

open access: yesAdvanced Engineering Materials, EarlyView.
X‐ray computed tomography (CT) is used to evaluate welded steel–steel composite metal foam (CMF) joints of two density classes. It reports variation in postweld spatial void distribution and correlates it to weld‐induced changes, mechanical performance, and failure within welded CMF panels.
Chinmaya Prerana Inguva   +2 more
wiley   +1 more source

Understanding Synovial Chondromatosis: A Rare Cause of Shoulder Impingement. [PDF]

open access: yesJ Orthop Case Rep
Kumar A, Nataraj AR, Purushotham L.
europepmc   +1 more source

Encyclopedia of 2D β′‐In2Se3 Growth Using Chemical Vapor Deposition: The Effects of Synthesis Parameters Onto Material Quality

open access: yesAdvanced Engineering Materials, EarlyView.
A distinct semi‐confined inner‐tube chemical vapor deposition geometry enables reproducible, large‐area growth of phase‐pure 2D β′‐In2Se3 from InI + Se precursors. Engineering local vapor transport and optimizing precursor delivery and temperature–time conditions yield uniform continuous films.
Dasun P. W. Guruge   +8 more
wiley   +1 more source

From Shear to Sound: Mechanics–Acoustics Mapping of TPMS Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
Triply periodic minimal surface (TPMS) lattices are mapped across mechanical and acoustic performance, revealing that descriptors validated in compression fail under shear. First‐time comparison with trusses included. A transition from porous to resonance‐driven absorption emerges at 25% density.
Lucía Doyle   +3 more
wiley   +1 more source

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

open access: yesAdvanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele   +2 more
wiley   +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

Simplifying rehabilitation control of lower-limb exoskeletons in five ambulation modes via dataset-driven state-machine calibration. [PDF]

open access: yesJ Neuroeng Rehabil
Lhoste C   +11 more
europepmc   +1 more source

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