Effect of twin boundary segregation on damping properties in magnesium alloy

Somekawa, Hidetoshi; Watanabe, Hiroyuki; Basha, Dudekula Althaf; Singh, Alok; Inoue, Tatsuo

doi:10.1016/j.scriptamat.2016.10.019

Cited by 64 publications

(11 citation statements)

References 34 publications

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“…Such segregation induces a strong pinning effect on twin boundaries, preventing further twin growth during subsequent loading (Nie et al, 2013). In a similar way, Somekawa et al (2017) also observed that the segregation of yttrium to twin boundaries led to a decrease in the damping capacity of binary Mg-Y alloys.…”

Section: Introductionmentioning

confidence: 65%

Evolución microestructural y envejecimiento dinámico por deformación en la aleación Mg-6%Gd- 1%Zn durante ensayos a tracción y compresión a temperaturas intermedias

et al. 2018

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La aleación Mg-6%Gd-1%Zn muestra el fenómeno de serrado durante la deformación a temperaturas intermedias debido al proceso de envejecimiento dinámico provocado por la presencia de átomos de soluto en solución sólida y dislocaciones móviles. Aunque la aleación tiene una textura al azar, se observa un comportamiento diferente en tracción y en compresión. El límite elástico y el endurecimiento es mayor cuando la aleación se ensaya en compresión. Durante la deformación a temperaturas intermedias se ha observado la activación de dislocaciones tipo < a > y maclas de tensión, independientemente del signo de la carga. Sin embargo, la fracción en volumen de maclas es siempre mayor cuando el material se somete a compresión. A temperaturas intermedias, los átomos de Gd y Zn anclan tanto las dislocaciones como las maclas. Por encima de 250 ºC, el fenómeno de serrado desaparece y la presencia de precipitados g´ y g´´ en el plano basal aumenta el endurecimiento.

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Section: Introductionmentioning

confidence: 65%

Evolución microestructural y envejecimiento dinámico por deformación en la aleación Mg-6%Gd- 1%Zn durante ensayos a tracción y compresión a temperaturas intermedias

et al. 2018

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“…When accounting for their observations, Abaspour and Cáceres (2015) disputed any role of the mechanisms, such as pinning of edge dislocations with mobile solute atoms, atomic size effect on the diffusivity, or dynamic precipitation of thermally stable precipitates. However, there exist atomic resolution imaging studies, explaining the temperature resistance of the strength on the basis of solute segregation (said to be driven by the need to reduce the twin boundary strain energy minimization) to mechanical twin boundaries in Mg-Gd, Mg-Gd-Zn (Nie et al, 2019), Mg-Y (Somekawa et al, 2017), Mg-Ca, and Mg-Zn (Somekawa et al, 2014) systems. Such solute segregations themselves were shown to be ordered along the twin boundaries and to have occurred in short annealing times.…”

Section: Assessment Of Interatomic Bonding In Solid Solutions Of Mg-tmentioning

confidence: 99%

A Review on Developments in Magnesium Alloys

Kaya

2020

Front. Mater.

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In order to facilitate the understanding of the current research efforts and directions, this article first introduces the anomalous/problematic features of magnesium (Mg) and presents the recent approach of stacking fault energy (SFE)-based alloying element selection to lessen or eliminate this problem. Stacking fault energy computations via ab initio techniques necessitate an understanding of the free electron density distribution around atoms in a solid solution. Therefore, the assessment of the role of atoms by also considering the possibility of short range order (SRO) formation rather than a random solid solution has been revisited. Two possible types of SRO have been indicated. The relevant electronic interactions between the host Mg and the alloying element atoms are more clearly incorporated in a generally less known model by Miedema based on atomic-level thermodynamics rather than in Hume-Rothery rules. This more successful approach has also been addressed here. An evaluation founded on these premises, introducing the relatively more recent Mg alloy systems, has been given in terms of their achievements toward healing the problematic features of Mg alloys. The spectrum of alloy systems discussed ranges from doping of Mg to dilute alloy systems and to some rich alloy systems that offer remarkable properties. Among the first category, an unorthodox addition, doping with oxygen, and its implications, has been presented. The dilute alloy systems and their compositional design based on SRO and SFE together with their potentials have been reviewed. Among the rich alloy compositions, the most interesting precipitate systems, that is, the ones involving order and intermetallic formations, long-period stacking order phases, and quasi-crystals, have been discussed. Among all the alloying elements, one that deserves particular attention, calcium, with its implications such as being economical, offering environmentally friendly Mg metallurgy, and remedial effects on the shortcomings of engineering properties, and a closely related issue of calcium oxide (CaO) addition have been scrutinized. This article also makes an attempt to point out the future directions throughout the text, whenever possible.

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“…These possible variations in chemistry lead to a vast material space for magnesium alloys. More importantly, the mobility of crystalline defects, such as dislocations and twin boundaries, depends on environmental variables, such as frequency ( 𝑓 ), strain amplitude (𝜀), and temperature (𝑇), resulting in different damping capacities [33][34][35][36][37] . These variables form the service space for the damping capacity.…”

Section: Introductionmentioning

confidence: 99%

Estimating the performance of a material in its service space via Bayesian active learning: a case study of the damping capacity of Mg alloys

Shi¹,

Zhou²,

Fang³

et al. 2022

J Mater Inf

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In addition to being determined by its chemical composition and processing conditions, the performance of a material is also affected by the variables of its service space, including temperature, pressure, and frequency. A rapid means to estimate the performance of a material in its service space is urgently required to accelerate the screening of materials with targeted performance. In the present study, a materials informatics approach is proposed to rapidly predict performance within a service space based on existing data. We utilize an active learning loop, which employs an ensemble machine learning method to predict the performance, followed by a Bayesian experimental design to minimize the number of experiments for refinement and validation. This approach is demonstrated by predicting the damping properties of a ZE62 magnesium alloy in a service space defined by frequency, strain amplitude, and temperature based on the available data for other magnesium alloys. Several utility functions that recommend a particular experiment to refine the estimates of the service space are used and compared. In particular, the standard deviation is found to reduce the prediction error most efficiently. After augmenting the database with nine new experimental measurements, the uncertainties associated with the predicted damping capacities are largely reduced. Our method allows us to forecast the properties in the service space of a given material by rapid refinement of the predictions via experiment measurements.

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Effect of twin boundary segregation on damping properties in magnesium alloy

Cited by 64 publications

References 34 publications

Evolución microestructural y envejecimiento dinámico por deformación en la aleación Mg-6%Gd- 1%Zn durante ensayos a tracción y compresión a temperaturas intermedias

Evolución microestructural y envejecimiento dinámico por deformación en la aleación Mg-6%Gd- 1%Zn durante ensayos a tracción y compresión a temperaturas intermedias

A Review on Developments in Magnesium Alloys

Estimating the performance of a material in its service space via Bayesian active learning: a case study of the damping capacity of Mg alloys

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