Results 131 to 140 of about 1,005,453 (288)

Recycling of NiTi Shape Memory Alloys: Fundamental and Technological Aspects of a Vacuum Induction Melting Processing Route

Advanced Engineering Materials, EarlyView.
The present study investigates recycling of NiTi shape memory alloys via vacuum induction melting. An ingot was synthesized from elemental Ni and Ti and subjected to three subsequent remelting cycles. Remelting increases process durations and impurity levels and adversely affects microstructures and functional properties.
Sakia Sophia Noorzayee, Son Tung Mai, Sarath Menon, Braulio Gadiel Sánchez Ortega, Ralf Drautz, Alexander Kauffmann, Gunther Eggeler, Jan Frenzel   +7 more
wiley   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
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

FSSM: Frequency-Enhanced State Space Modeling with FFT-Based Two-Sided Non-Causal Convolution for Image Dehazing. [PDF]

J Imaging
Zeng L, Huang Y.
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

Frequency-Guided Cross-Modal Interaction for Multimodal Yeast Classification Based on Light-Scattering and Microscopy Images. [PDF]

J Imaging
Cheng Z, Liu X, Shankarnarayan S, Gupta M, Rozmus W, Tsui YY, Charlebois DA, Mandal M.   +7 more
europepmc   +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

Dual-Branch Graph Learning with Frequency Gating for Industrial Sensor Anomaly and Cyberattack Detection. [PDF]

Sensors (Basel)
Zhao T, Yang W, Yao Y.
europepmc   +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

Tunable acoustic rotation for deep biophysical phenotyping of preclinical Alzheimer's disease. [PDF]

Mater Today Bio
Wang Y, Quan Y, Zhou S, Zhou Y.
europepmc   +1 more source