Results 181 to 190 of about 73,671 (260)

Optimizing Wood-Hemp-Sodium Silicate Composites for Strength, Extrudability, and Cost in Additive Manufacturing Applications. [PDF]

Materials (Basel)
Tanikella NG, McDonald AG, Maughan MR.
europepmc   +1 more source

Experimental Characterization and Constitutive Modeling of the Effect of Prior Inelastic Strain on the Viscoplastic Behavior of AD730 at 700 °C

Advanced Engineering Materials, EarlyView.
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca, Patrick Villechaise, Malik Durand, Arnaud Longuet, Florent Coudon, Loïc Signor, Julien De Jaeger, Dominique Eyidi, Nathalie Bozzolo, Jonathan Cormier   +9 more
wiley   +1 more source

The utility of a composite endpoint for tracking disease progression in Lewy body dementia. [PDF]

Alzheimers Dement (N Y)
Matar E, White SR, Taylor JP, Thomas A, McKeith I, Kane J, Lewis S, Surendranathan A, O'Brien J.   +8 more
europepmc   +1 more source

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

Beyond classical metrics: Generalizability theory across psychophysiological modalities. [PDF]

Int J Psychophysiol
Rocha HA, Holbrook A, Hajcak G, Keil A, Rast P, Thayer JF, Verona E, Vispoel WP, Clayson PE.   +8 more
europepmc   +1 more source

Modeling Dislocation Cutting of γ′ Precipitates in Ni‐Base Superalloys: Linking Atomistic and Dislocation Dynamics Simulations

Advanced Engineering Materials, EarlyView.
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé, Siwen Gao, Marc Fivel, Anxin Ma, Daria Smirnova, Sriram Anand, Arun Prakash, Julien Guénolé, Alexander Hartmaier, Erik Bitzek   +9 more
wiley   +1 more source

A Review of Modeling Electrical Conductivity in Carbon-Filled Polymer Composites. [PDF]

Polymers (Basel)
Mohseni A, Hrymak AN.
europepmc   +1 more source

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Circadian-immune-related gene signature for lung squamous cell carcinoma: machine learning and multi-omics analysis. [PDF]

Transl Cancer Res
Lu Y, Li H, Wang S, Yang F, Xiao S, Liu Y, Liu Q, Han X, Hu Y.   +8 more
europepmc   +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