Results 111 to 120 of about 15,132,342 (300)

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

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

Corrosion behavior of Al2CrFeCoxCuNiTi high-entropy alloy coating in alkaline solution and salt solution

Results in Physics, 2019
The Al2CrFeCoxCuNiTi high-entropy alloy coatings were prepared by laser cladding. The microstructure of the coatings was tested by micro analysis instrument.
Xing-wu Qiu
doaj   +1 more source

Electrochemical Behavior of Flame‐Sprayed Sc‐Doped AlCoCrFeMo High‐Entropy Alloy Coatings in 3.5% Sodium Chloride Solution

Advanced Engineering Materials, EarlyView.
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar, Akash Vyas, Mohammad Aatif Qazi, Nashit Jalal, Maria Ophelia Jarligo, Mostafa Yakout, Jing Liu, André McDonald   +7 more
wiley   +1 more source

High Strength and Deformation Mechanisms of Al_0.3CoCrFeNi High-Entropy Alloy Thin Films Fabricated by Magnetron Sputtering

, 2019
Recently, high-entropy alloy thin films (HEATFs) with nanocrystalline structures and high hardness were developed by magnetron sputtering technique and have exciting potential to make small structure devices and precision instruments with sizes ranging ...
Liao, Wei Bing, Yu, Chun Yan, Yang Lu, Li, Pei Feng, Lu, Yang, Hongti Zhang, Pei-Feng Li, Jian-Jun Huang, Wei-Bing Liao, Zhang, Hongti, Huang, Jian Jun, Zhi-Yuan Liu, Liu, Zhi Yuan, Chun-Yan Yu   +13 more
core   +1 more source

Physical Properties of High Entropy Alloys [PDF]

Entropy, 2013
The majority of studies on high-entropy alloys are focused on their phase, microstructure, and mechanical properties. However, the physical properties of these materials are also encouraging. This paper provides a brief overview of the physical properties of high-entropy alloys. Emphasis is laid on magnetic, electrical, and thermal properties.
openaire   +3 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

Wide-temperature-range perfect superelasticity and giant elastocaloric effect in a high entropy alloy

Materials Research Letters, 2019
The high entropy alloy concept offers unique opportunities for the design of advanced materials with unprecedented properties. However, hitherto most of the research efforts are focused on structural materials.
Shaohui Li, Daoyong Cong, Xiaoming Sun, Yong Zhang, Zhen Chen, Zhihua Nie, Runguang Li, Fuqiang Li, Yang Ren, Yandong Wang   +9 more
doaj   +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