Superior ductility Mg-Mn extrusion alloys at room temperature obtained by controlling Mn content

Li, C.C.; Xia, Zehua; Qiao, Xiaoguang; Golovin, I.S.; Zheng, M.Y.

doi:10.1016/j.msea.2022.144508

Cited by 9 publications

(3 citation statements)

References 50 publications

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“…The Al and Zn elements are the key compositions in the commercial Mg alloys. The Mn element plays important roles in precipitation strengthening, [69] grain refinement, [69–71] improving ductility, [69] and inhibiting the Fe‐caused magnesium corrosion [72] in wrought Mg alloys. A small amount of Ca can produce a good strengthening and toughening effect, which has recently attracted widespread attention [27,73,74] .…”

Section: Resultsmentioning

confidence: 99%

“…However, since Ca leads to a reduction in ductility, the Ca content is reduced in the strength–ductility balanced target. In high‐ductility alloys, the content of other alloying elements is further reduced, with only the Mn content being retained due to its promoting effect on grain boundary sliding and room temperature dynamic recrystallization [69] . Additionally, the changes in extrusion ratio and extrusion temperature are not significant, but the variation in extrusion speed is substantial.…”

Section: Resultsmentioning

confidence: 99%

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Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning

Li,

Dong,

Jin

et al. 2024

Materials Genome Engineering Advances

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In this study, a small dataset of 370 datapoints of Mg alloys are selected for machine learning (ML), in which each datapoint includes five rare‐earth‐free alloying elements (Ca, Zn, Al, Mn and Sn), three extrusion parameters (extrusion speed, temperature and ratio), and three mechanical properties (yield strength [YS], ultimate tensile strength [UTS] and elongation [EL]). The ML algorithms, including support vector machine regression (SVR), artificial neural network, and other three methods, are employed, and the SVR has the best performance in predicting mechanical properties based on the components, and process parameters, with the mean absolute percentage error of YS, UTS, and EL being 6.34%, 4.19%, and 13.64% in the test set, respectively. The SVR model combined with multi‐objective genetic algorithm are successfully used to optimize mechanical properties of four extruded alloys from Mg‐Ca, Mg‐Ca‐Zn, Mg‐Ca‐Mn‐Sn, and Mg‐Ca‐Al‐Zn‐Mn series alloys, respectively, and the corresponding experimental results are in good agreement with the designed ones. Furthermore, new composition schemes are proposed from a wider range of elements and processing features to match the objectives of high‐strength, strength–ductility balanced, and high‐ductility Mg alloys, and the four‐, five‐ and six‐element alloying schemes are provided for the candidates of new‐generation wrought Mg alloys.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning

Li,

Dong,

Jin

et al. 2024

Materials Genome Engineering Advances

View full text Add to dashboard Cite

show abstract

“…New alloys have increased strength, ductility, heat resistance, corrosion resistance, variable crystal size in the matrix, and other properties. These magnesium materials include additives of manganese [ [4], [5], [6], [7], [8], and [9]], zirconium [ [10], [11], [12], [13], [14], [15], [16], [17], and [18]] and beryllium [ [19], [20], [21], [22], [23], [24], and [25]].…”

Section: Introductionmentioning

confidence: 99%

Recycling of beryllium, manganese, and zirconium from secondary alloys by magnesium distillation in vacuum

Volodin,

Abdulvaliyev,

Trebukhov

et al. 2024

KIMS/CUMR/MShKP

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One of the methods for processing secondary magnesium raw materials containing rare refractory metals can be a distillation with the extraction of magnesium into condensate and the accumulation of rare metals in the distillation residue. The residue can be used as a master alloy for special alloys. To justify the possibility of this process, we calculated the boundaries of the vapor-liquid equilibrium fields for the regions of liquid solutions existence in the Mg – Be, Mg – Mn, and Mg – Zr systems at atmospheric pressure (101.33 kPa) and in vacuum (1.33 kPa). The value of the vacuum is due to the fact that a further increase in rarefaction will lead to the magnesium crystallization from the melt, and it will complicate the technology.We established that in the distillation process of magnesium removal from Mg – Be and Mg – Zr alloys, the vapor phase will be represented by more than 99.95 of magnesium. The presence of 0.45 mass.% Mn is possible in the Mg – Mn system at 1000 °C in thevapor phase – condensate . However, results of preliminary tests of the evaporation intensity established that the process conducted at 850-900 °C provides an acceptable evaporation rate of the volatile component (Mg) for technological conditions.Thus, we confirmed the possibility of the proposed method to process secondary light alloys containing beryllium, manganese, and zirconium, which can be involved in the main process intended to produce special alloys in the form of a master alloy with magnesium.

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Prediction of high temperature mechanical and thermodynamic properties of W-Mn alloys based on first principles method

Wu,

Liu,

Lai

et al. 2024

Fusion Engineering and Design

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Superior ductility Mg-Mn extrusion alloys at room temperature obtained by controlling Mn content

Cited by 9 publications

References 50 publications

Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning

Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning

Recycling of beryllium, manganese, and zirconium from secondary alloys by magnesium distillation in vacuum

Prediction of high temperature mechanical and thermodynamic properties of W-Mn alloys based on first principles method

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