Results 71 to 80 of about 8,109 (228)

Microstructure‐Controlled Crack Propagation and Fracture Resistance in MoSiBTiC Alloy Revealed by Multiscale Extended Finite Element Method Modeling

Advanced Engineering Materials, EarlyView.
A two‐dimensional multiscale finite element analysis framework was established for the first‐generation MoSiBTiC alloy, and the mechanical and fracture‐related parameters of the constituent phases were calibrated through experiments and simulations. The framework provides a basis for analyzing crack propagation behavior in its complex microstructure ...
Junfeng Du, Takahiro Kaneko, Xinyu Yan, Takahito Ohmura, Kyosuke Yoshimi   +4 more
wiley   +1 more source

In Situ Micromechanical Study of Bimodal γ′–γ″ Precipitate Assemblies in Ni–Cr–Al–Nb Superalloy

Advanced Engineering Materials, EarlyView.
A Ni–Cr–Al–Nb superalloy with a bimodal γ′–γ″ precipitate distribution is developed. Composite precipitate assemblies form through heterogeneous nucleation, effectively impeding dislocation motion. Micropillar compression reveals high strength at room and elevated temperatures, governed by precipitate shearing, with coupled faulting mechanisms ...
Ujjval Bansal, Tae‐Hyeok Kang, Pyuck‐Pa Choi, Subin Lee, Christoph Kirchlechner   +4 more
wiley   +1 more source

Hölder continuity of bounded weak solutions to generalized parabolic \(p\)-Laplacian equations. II: Singular case

Electronic Journal of Differential Equations, 2015
This very interesting paper is intended as a companion paper of [Electron. J. Differ. Equ. 2015, Paper No. 287, 32 p. (2015; Zbl 1331.35200)] where the authors proved the Hölder continuity of solutions to degenerate parabolic equations satisfying a generalized \(p\)-Laplacian structure.
Sukjung Hwang, Gary M. Lieberman
openaire   +2 more sources

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

Hölder continuity of bounded weak solutions to generalized parabolic \(p\)-Laplacian equations. I: Degenerate case

Electronic Journal of Differential Equations, 2015
In this very interesting paper, the authors generalize quasilinear parabolic \(p\)-Laplacian-type equations to obtain the prototype equation \[ u_ t - \operatorname{div}( \frac{g(|Du|)} {|Du|}Du)= 0, \] where \(g\) is a nonnegative, increasing, and continuous function trapped in between two power functions \(p_1\) and \(p_2\) greater than 2.
Sukjung Hwang, Gary M. Lieberman
openaire   +2 more sources

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

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

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

Advanced Engineering Materials, EarlyView.
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma, Sarath Menon, Fritz Körmann, Thomas Hammerschmidt, Ralf Drautz   +4 more
wiley   +1 more source