Zobrazeno 1 - 10
of 2 587
pro vyhledávání: '"Alloy design"'
Publikováno v:
Journal of Materials Research and Technology, Vol 33, Iss , Pp 2672-2682 (2024)
To develop medium-Mn steels with an ultimate tensile strength (UTS) exceeding 2 GPa and excellent ductility, we created a highly accurate UTS prediction machine learning (ML) model using a boosted decision tree model and 1520 dataset of tensile prope
Externí odkaz:
https://doaj.org/article/2961ab15f09c4c1fbeb264a12077d5f2
Publikováno v:
Journal of Materials Research and Technology, Vol 33, Iss , Pp 2216-2225 (2024)
SiCp/Al composite materials are widely used due to their lightweight and high strength. There is no systematic study on the effect of variation of Cu content on the mechanical properties of composites. In order to study the effect of Cu content on th
Externí odkaz:
https://doaj.org/article/62873bdf43e54e079101ac686ed0d7c2
Publikováno v:
Materials Research Letters, Pp 1-9 (2024)
The high ductile brittle transition temperature of tungsten (W) poses challenges like cracking and porosity during its laser-powder bed additive manufacturing (L-PBFAM). Computational alloy design evaluated niobium (Nb) and carbon (C) to activate eut
Externí odkaz:
https://doaj.org/article/6c8771e0f216445ea56a4bc3a1be7572
Publikováno v:
工程科学学报, Vol 46, Iss 10, Pp 1797-1811 (2024)
In materials genetic engineering, data-driven machine learning techniques have garnered significant attention as a powerful new tool in the field of magnesium alloys. Traditional empirical trial-and-error methods and those based on density functional
Externí odkaz:
https://doaj.org/article/4ea6122964854027a1f7268627aee2c5
Publikováno v:
Materials Research Letters, Vol 12, Iss 10, Pp 745-755 (2024)
The strength−ductility tradeoff and composition homogeneity have been the obstacles to obtaining advanced structural alloys. To overcome the limitations, we develop a novel coherently eutectic high-entropy alloy, i.e. Fe30Cr15V15Ni20Al20. By introd
Externí odkaz:
https://doaj.org/article/e6fab24c0fc2421ba8a0e8a44e61e62c
Publikováno v:
Alloys, Vol 3, Iss 3, Pp 190-231 (2024)
Abstract: The refractory complex concentrated alloy (RCCA) 5Al–5Cr–5Ge–1Hf–6Mo–33Nb–19Si–20Ti–5Sn–1W (at.%) was studied in the as-cast and heat-treated conditions. The partitioning of solutes in the as-cast and heat-treated microstr
Externí odkaz:
https://doaj.org/article/1182e5014c5840428079a7751d2993b4
Publikováno v:
Journal of Materials Research and Technology, Vol 32, Iss , Pp 3937-3948 (2024)
This study investigates hybrid stainless steel (SS) 316L/Inconel 625 (IN625) materials via DED for hydrofluoric acid (HF) corrosion resistance. 20% SS 316L + 80% IN625 (20% 316L) exhibits low uniform corrosion (0.35 mm/y) and improved local corrosion
Externí odkaz:
https://doaj.org/article/8a4e7cc48df44d158bbceb5842850ebf
Publikováno v:
Journal of Materials Research and Technology, Vol 32, Iss , Pp 3514-3522 (2024)
High-entropy alloys (HEAs) provide limitless opportunities to enhance material performance while predicting the thermodynamic properties and the structures rapidly within HEAs remain challenging. Herein, a new method (M2FEn) for rapidly predicting th
Externí odkaz:
https://doaj.org/article/a2ba6a1f32f44452b9c7c9257b48c86a
Autor:
Mehran Bahramyan, Reza T. Mousavian, Gopinath Perumal, Gavin Roche Griffin, Yanuar Rohmat Aji Pradana, James G. Carton, David J. Browne, Dermot Brabazon
Publikováno v:
Materials & Design, Vol 246, Iss , Pp 113316- (2024)
The equiatomic face-centred cubic (FCC) CoNiCrFeMn alloy, known as the Cantor alloy, is renowned for its high ductility under extreme conditions, such as cryogenic temperatures. Despite this, it suffers from low hardness and yield strength (YS) and i
Externí odkaz:
https://doaj.org/article/d836b1d5e57047a2aa6b32b6cbcf8b34
Publikováno v:
Materials Genome Engineering Advances, Vol 2, Iss 3, Pp n/a-n/a (2024)
Abstract Conventional trial‐and‐error method is usually time‐consuming and expensive for multi‐objective optimization of Mg alloys. Although machine learning exhibits great potential to accelerate related research studies, machine learning pr
Externí odkaz:
https://doaj.org/article/d427f20ffd604fc5861551f8f59552ac