Journal Articles

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Browsing Journal Articles by browse.metadata.impactarea "Advanced Materials Engineering"

Now showing 1 - 4 of 4
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    Influence of SN on the microstructure and mechanical properties of TI-MO-NB alloys for orthopaedic applications
    (2022-11) Muchavi, Noluntu S; Raganya, Mampai L; Machaka, R; Motsi, Glenda T; Makhatha, E
    Metastable ß-Ti alloys intended for orthopaedic implants typically possess undesirable a', a", precipitates, which increase the elastic modulus. Non-toxic Sn was reported as an effective suppressor of a', a" and precipitates. Furthermore, increasing Sn content was reported to decrease the elastic modulus. In this study, the cluster plus glue atom (CPGA) model was used to develop structurally stable ß-Ti alloys through the addition of Sn. Arc melting was conducted to fabricate the alloys. The effect of substituting Mo atoms with 0.4 and 0.5 Sn atoms on the microstructure and mechanical properties of [(Mo,Sn)(Ti)14](Nb)1 alloys was investigated. The microstructure of the alloys exhibited large equiaxed beta grains with the [(Mo0.6Sn0.4)(Ti)14](Nb)1 and [(Mo0.5Sn0.5)(Ti)14](Nb)1 alloys showing substructures. The XRD results showed that the alloys consisted of the ß phase; however, the presence of a” was observed in the [(Mo0.6Sn0.4)(Ti)14](Nb)1 alloy. The study showed that substitution of 0.5 Mo atoms with 0.5 atoms of Sn to form the [(Mo0.5Sn0.5)(Ti)14](Nb)1 cluster resulted in an elastic modulus of 49 GPa.
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    Machine learning-based prediction of phases in high-entropy alloys: A data article
    (2021-10) Machaka, Ronald; Motsi, Glenda T; Raganya, Mampai L; Radingoana, Precious M; Chikosha, Silethelwe
    A systematic framework for choosing the most determinant combination of predictor features and solving the multiclass phase classification problem associated with high-entropy alloy (HEA) was recently proposed [1]. The data associated with that research paper, titled “Machine learning-based prediction of phases in high-entropy alloys”, is presented in this data article. This dataset is a systematic documentation and comprehensive survey of experimentally reported HEA microstructures. It contains microstructural phase experimental observations and metallurgy-specific features as introduced and reported in peer-reviewed research articles. The dataset is provided with this article as a supplementary file. Since the dataset was collected from experimental peer-reviewed articles, these data can provide insights into the microstructural characteristics of HEAs, can be used to improve the optimization HEA phases, and have an important role in machine learning, material informatics, as well as in other fields.
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    Spheroidisation of stainless steel powder for additive manufacturing
    (2021-06) Chikosha, Silethelwe; Tshabalala, Lerato C; Bissett, H; Lesufi, M; Mnguni, Khulekani N; Motsai, Tebogo M; Manama, T; Hoosain, S
    In additive manufacturing, powder characteristics play an important role in terms of flowability and densification, which can be improved by the use of spherical powders. In this study, irregular powder was spheroidised by plasma treatment, and the powder properties were measured. Powder characterisation was conducted to determine the morphology, particle size and distribution as well as the flowability. Spherical AISI 304 stainless steel powders were produced by plasma spheroidization, and the efficiency of the spheroidisation process was evaluated. The spheroidisation process resulted in 93% efficiency with a decrease of fine particles (<63 µm) by 22%, while the all the flowability parameters of the powder improved significantly.
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    Using the Cluster-Plus-Glue-Atom model to design the composition of low Young’s modulus β-Ti alloys for orthopaedic applications
    (2024-12) Muchavi, Noluntu S; Raganya, Mampai L; Makhatha, E
    The design and development of metastable β-type Ti alloys with low Young’s moduli (E) requires the use of multiple β-phase stabilising alloying elements. The most commonly used alloy development design strategies do not provide accurate composition design. Moreover, the process of developing alloys is still based on empirical exploration, which is costly and time consuming. In this study, the cluster-plus-glue-atom (CPGA) model was employed in the composition design and interpretation of low-E, β-type Ti based alloys. Microstructure, phase analysis, Young’s modulus (mechanical testing and nano-indentation testing) of the as-cast alloys were investigated. The results demonstrated that the CPGA model was effective in formulating compositions which were able to simultaneously achieve high β-phase stability and low-E as exemplified by the [(Mo0.4Sn0.6) (Ti)14] (Nb)1 alloy which obtained a Young’s modulus of 59 GPa.