Theoretical prediction and experimental evaluation of glass forming ability, density and equilibrium point of Ta based bulk metallic glass alloys

Bharath, Katti; Chelvane, J. Arout; Kumawat, Mahesh K.; Nandy, T.K.; Majumdar, Bhaskar

doi:10.1016/j.jnoncrysol.2019.03.001

Cited by 14 publications

(2 citation statements)

References 23 publications

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“…Many recent studies have reported on developing Tantalum-based materials for a broad spectrum of engineering and functional applications [31]. Compared to other materials, Tantalum (Ta) is an element exceptionally having a density of g cm 16.65 .…”

Section: Introductionmentioning

confidence: 99%

On the structure and icosahedral interconnectivity in Tantalum monatomic glass produced under pressure

Kbirou,

Atila,

Hasnaoui

2024

Phys. Scr.

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Proper processing of bulk metallic glasses (BMGs) under pressure is a promising approach to tailor their properties. However, to fully understand how pressure processing affect the final glass properties, a clearer understanding of how the pressure affects the structure of the glass at both short- and medium range levels is required. Accordingly, using molecular dynamics simulations, we study the effect of cooling under pressure on the local structure and the medium-range connectivity in a model Tantalum monatomic metallic glass. Crystalline grains form in the Ta sample with increasing the pressure under which the sample was cooled. These observations were confirmed by decreasing the fivefold symmetry with increasing pressure. The connectivity type between the perfect icosahedra was determined and showed that when cooled under pressure, intercross sharing is favored in the higher pressure. This work gives insights into understanding local structural changes induced by the pressure in metallic glasses.

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Section: Introductionmentioning

confidence: 99%

On the structure and icosahedral interconnectivity in Tantalum monatomic glass produced under pressure

Kbirou,

Atila,

Hasnaoui

2024

Phys. Scr.

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“…Bharath et al showed the utility of this parameter by screening the compositional space of several ternary and quaternary Ta-(TM)-Ni-B alloys (TM = transition metal), finding reasonable agreement between P HSS and experimental measurements of GFA [17]. While this parameter is applicable to quaternary and higher-order multi-component compositions, screening a significant portion of compositional space is difficult.…”

Section: Introductionmentioning

confidence: 99%

Predicting multi-component, high-temperature metallic glasses by coupling empirical models, CALPHAD, and a genetic algorithm

Howard,

Carlson,

Mushongera

2023

Modelling Simul. Mater. Sci. Eng.

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Metallic glasses (MGs) are an emerging class of materials possessing multiple desirable properties including high strength, hardness, and corrosion resistance when compared to their crystalline counterparts. However, most previously studied MGs are not useful in high temperature environments because they undergo the glass transition phenomenon and crystallize below the melting point. In addition, bulk MGs are typically found in multi-component systems, meaning that searching compositional space with a reasonable resolution using computational or experimental methods can be costly. In this study, an in-house developed genetic algorithm-based tool was used to locate alloy compositions with high glass forming ability (GFA) and high-temperature stability in the Ta–Ni–Co–(B) and Ta–Ni–Co–Nb alloy systems. GFA was predicted using an empirical predictive parameter known as P HSS. High-temperature stability was predicted using the CALPHAD method to calculate liquidus temperature. Justification for the use of P HSS to predict GFA of high-temperature MGs, as well as the use of liquidus temperature as a predictor of general high-temperature stability, is given in the form of a meta-analysis of previously reported MG compositions. The predictions made using this algorithm were analyzed and are presented herein. While high-temperature stability was the property of interest for this research, this framework could be used in the future to locate alloys with other application-specific material properties. This genetic algorithm-based tool enables the coupling of empirical parameters and CALPHAD to efficiently search multi-component space to locate glass-forming alloys with desirable properties.

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Identifying key features for predicting glass-forming ability of bulk metallic glasses via interpretable machine learning

Zeng,

Tian,

Zheng

et al. 2024

J Mater Sci

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Theoretical prediction and experimental evaluation of glass forming ability, density and equilibrium point of Ta based bulk metallic glass alloys

Cited by 14 publications

References 23 publications

On the structure and icosahedral interconnectivity in Tantalum monatomic glass produced under pressure

On the structure and icosahedral interconnectivity in Tantalum monatomic glass produced under pressure

Predicting multi-component, high-temperature metallic glasses by coupling empirical models, CALPHAD, and a genetic algorithm

Identifying key features for predicting glass-forming ability of bulk metallic glasses via interpretable machine learning

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