High-pressure annealing driven nanocrystal formation in Zr50Cu40Al10 metallic glass and strength increase

Shibazaki, Yuki; Yamada, R.; Saida, Junji; Kono, Yoshio; Wakeda, Masato; Itoh, Keiji; Nishijima, Masahiko; Kimoto, Koji

doi:10.1038/s43246-020-00057-3

Cited by 12 publications

(2 citation statements)

References 43 publications

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“…As can be seen from the RRDFs of the annealed samples, the structures of the M193K and M243K samples become slightly more disordered compared to the as-cast specimens. Contrary to the nanocrystallization of the Zr 50 Cu 40 Al 10 glass annealed under pressure, or the nanodecomposition of Ti 50 Ni 23 Cu 22 Sn 5 upon annealing in its supercooled liquid region, our study shows full homogenization of the chemically decomposed material during long-term heat treatment.…”

Section: Discussioncontrasting

confidence: 58%

Cryo-Casting for Controlled Decomposition of Cu–Zr–Al Bulk Metallic Glass into Nanomaterials: Implications for Design Optimization

Sarac

Kim

Ivanov

et al. 2021

ACS Appl. Nano Mater.

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Cryo-cooled copper-mold suction casting reveals an unexpected phase separation (PS) in Cu46Zr46Al8 bulk metallic glass (BMG) by controlled atomic diffusion. The decomposed alloy cryo-cast to 193 K exhibits a remarkably lower free volume than the alloy cast to room temperature manifested by dilatometry. An unusual endotherm after the onset of relaxation registered by differential scanning calorimetry and compositional homogenization occurring on long time scales upon post-heat treatment even above the glass-transition temperature confirm the stability of the decomposed state against crystallization. As revealed by scanning transmission electron microscopy and energy-dispersive X-ray analysis, single-stage PS (cryo-cast to 193 K) results in distinct and evenly dispersed nanoscale Cu- and Zr-rich regions, whereas two-stage PS (cast to 298 K) involves further decomposition of existing Cu- and Zr-rich regions on a finer scale. Notably, PS accounts for macroscopic compressive plasticity at no expense of fracture strength. This study opens opportunities for the design optimization of homogeneously dispersed amorphous nanostructures of controllable size and composition in BMGs by single- or multistage decomposition through mold temperature control.

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Section: Discussioncontrasting

confidence: 58%

Cryo-Casting for Controlled Decomposition of Cu–Zr–Al Bulk Metallic Glass into Nanomaterials: Implications for Design Optimization

Sarac

Kim

Ivanov

et al. 2021

ACS Appl. Nano Mater.

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show abstract

“…We analyzed a metallic glass Zr50Cu40Al10 specimen subjected to high-pressure (5.5 GPa) and high-temperature (880 K) treatments. The detailed structural and mechanical properties of the specimen are provided in our previous report 26 . We performed a 4D-STEM experiment using an electron microscope (Titan, Thermo Fisher Scientific) at an accelerating voltage of 300 kV.…”

Section: Methodsmentioning

confidence: 99%

Unsupervised machine learning combined with 4D scanning transmission electron microscopy for bimodal nanostructural analysis

Kimoto,

Kikkawa,

Harano

et al. 2023

Preprint

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Unsupervised machine learning techniques have been combined with scanning transmission electron microscopy (STEM) to enable comprehensive crystal structure analysis with nanometer spatial resolution. In this study, we investigated large-scale data obtained by four-dimensional (4D) STEM using dimensionality reduction techniques such as non-negative matrix factorization (NMF) and hierarchical clustering with various optimization methods. We developed software scripts incorporating knowledge of electron diffraction and STEM imaging for data preprocessing, NMF, and hierarchical clustering. Hierarchical clustering was performed using cross-correlation instead of Euclidean distances, resulting in rotation-corrected diffractions and shift-corrected maps of major components. An experimental analysis was conducted on a high-pressure-annealed metallic glass, Zr-Cu-Al, revealing an amorphous matrix and crystalline precipitates with an average diameter of approximately 7 nm, which were challenging to detect using conventional STEM techniques. Combining 4D-STEM and optimized unsupervised machine learning enables comprehensive bimodal (i.e., spatial and reciprocal) analyses of material nanostructures.

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Designing Advanced Amorphous/Nanocrystalline Alloys by Controlling the Energy State

Wang,

Song,

Huo

et al. 2024

Advanced Materials

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Amorphous alloys, also known as metallic glasses, exhibit many advanced mechanical, physical and chemical properties. Owing to the nonequilibrium nature, their energy states can vary over a wide range. However, the energy relaxation kinetics are very complex and composed of various types that are coupled with each other. This makes it challenging to control the energy state precisely and to study the energy‐properties relationship. In this brief review, we introduce the recent progresses on studying the enthalpy relaxation kinetics during isothermal annealing, e.g. the observation of two‐step relaxation phenomenon, the detection of relaxation unit (relaxun), the key role of large activation entropy in triggering memory effect, the influence of glass energy state on nanocrystallization. Based on the above knowledge, a new strategy is proposed to design a series of amorphous alloys and their composites consisting of nanocrystals and glass matrix with superior functional properties by precisely controlling the nonequilibrium energy states. As the typical examples, Fe‐based amorphous alloys with both advanced soft magnetism and good plasticity, Gd‐based amorphous/nanocrystalline composites with large magnetocaloric effect, and Fe‐based amorphous alloys with high catalytic performance are specifically described.This article is protected by copyright. All rights reserved

show abstract

High-pressure annealing driven nanocrystal formation in Zr50Cu40Al10 metallic glass and strength increase

Cited by 12 publications

References 43 publications

Cryo-Casting for Controlled Decomposition of Cu–Zr–Al Bulk Metallic Glass into Nanomaterials: Implications for Design Optimization

Cryo-Casting for Controlled Decomposition of Cu–Zr–Al Bulk Metallic Glass into Nanomaterials: Implications for Design Optimization

Unsupervised machine learning combined with 4D scanning transmission electron microscopy for bimodal nanostructural analysis

Designing Advanced Amorphous/Nanocrystalline Alloys by Controlling the Energy State

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