As protective coatings for the thermal parts of aero-engines, AlCoCrFeNi coatings have good application prospects. In this study, atmospheric plasma spraying (APS) was used to prepare AlCoCrFeNi high-entropy coatings (HECs), which were oxidized from 650 °C to 1000 °C. The mechanism of the oxide layer formation and the internal phase transition were systematically investigated. The results show that a mixed oxide scale with a laminated structure was formed at the initial stage of oxidation. The redistribution of elements and phase transition occurred in the HECs' matrix; the BCC/B2 structure transformed to Al-Ni ordered B2 phase and Fe-Cr disordered A2 phase.
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http://dx.doi.org/10.3390/ma17030550 | DOI Listing |
Materials (Basel)
December 2024
Department of Materials Engineering, Mechanical Engineering Faculty, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland.
High-entropy alloys are of interest to many researchers due to the possibility of shaping their functional properties by, among other things, the use of alloying additives. One approach to improving the wear resistance of the AlCoCrFeNi alloy is modification through the addition of titanium. However, in this study, an alternative solution was explored by adding vanadium, which has a completely different effect on the material's structure compared to titanium.
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December 2024
School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.
To improve the performance of AlCoCrFeNi eutectic high-entropy alloys (EHEA) to meet industrial application requirements, ZrAlCoCrFeNi high-entropy alloys (x = 0, 0.01, 0.05, 0.
View Article and Find Full Text PDFMaterials (Basel)
October 2024
Department of Industrial Engineering, University of Trento, 38122 Trento, Italy.
In the present work, three different AlCoxCrFeNi (x = 1, 0.75, 0.5) alloys were produced through the mechanical milling of powders and spark plasma sintering.
View Article and Find Full Text PDFAdv Sci (Weinh)
December 2024
School of Computer Engineering & Science, Shanghai University, Shanghai, 200444, China.
Small data in materials present significant challenges to constructing highly accurate machine learning models, severely hindering the widespread implementation of data-driven materials intelligent design. In this study, the Dual-Strategy Materials Intelligent Design Framework (DSMID) is introduced, which integrates two innovative methods. The Adversarial domain Adaptive Embedding Generative network (AAEG) transfers data between related property datasets, even with only 90 data points, enhancing material composition characterization and improving property prediction.
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September 2024
School of Materials Science and Engineering, Shenyang Aerospace University, Shenyang 110136, China.
In order to explore the effect of alloying on the microstructures and mechanical properties of AlCoCrFeNi eutectic high-entropy alloys (EHEAs), 0.1, 0.2, and 0.
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