Results 221 to 230 of about 252,487 (303)

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Streamlining the MRI-Derived Vertebral Bone Quality Score for Preoperative Osteoporosis and Osteopenia Screening. [PDF]

Global Spine J
Köhli P, Guven AE, Mielke AM, Alschuler DM, Lan R, Hambrecht J, Chiapparelli E, Schönnagel L, Evangelisti G, Duculan R, Shue J, Tsuchiya K, Pumberger M, Burkhard MD, Mancuso CA, Sama AA, Girardi FP, Cammisa FP, Hughes AP.   +18 more
europepmc   +1 more source

Oral cancer screening device [PDF]

Vital, 2012
openaire   +1 more source

Soft Mechanical‐Electrical Logic Using Liquid Metal‐Filled 3D‐Printed Architectures

Advanced Engineering Materials, EarlyView.
We present 3D‐printed soft mechanical–electrical logic elements that use liquid metal–filled silicone tubes actuated by thermoplastic polyurethane/polylactic acid (TPU/PLA) architectures to produce Boolean operations. Complementary normally open and normally closed unit cells perform repeatable binary transitions and can be combined into more complex ...
Christoph Lehmann, Ryan Kalgreen, Laura M. Comella   +2 more
wiley   +1 more source

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

Advanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +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

Efficient and Accurate Modeling of Anisotropic Electrostatic Landscapes in Amorphous Organic Semiconductor Films. [PDF]

J Chem Theory Comput
Kim Y, Son J, Moon G, Choi H, Gil J, Lee JH, Jung Y.   +6 more
europepmc   +1 more source

Experimental Characterization of Mycelium‐Based Composites Under Multiple Loading Conditions

Advanced Engineering Materials, EarlyView.
This study examines the mechanical response of mycelium‐based composites under compression, shear, and tension using mechanical testing and imaging methods. The comparison between unpressed and hot‐pressed specimens shows that hot pressing is associated with higher compression and shear stiffnesses.
Shaghayegh Elahi, Kimiya Tajik, Harvey Shaw, Matti Isakov, Sami Pajunen, Lauri Rautkari   +5 more
wiley   +1 more source

Machine Learning in Non-fullerene Organic Solar Cells: Accelerating Discovery, Design, and Understanding. [PDF]

ACS Omega
Das B, Mondal A.
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