Grain size distribution analysis of MgO and VC inhibited zirconia toughened alumina ceramics using digital image processing

Sarkar, Moumita; Dutta, Samik; Chakraborty, Shitanshu Shekhar; Mandal, Nilrudra

doi:10.1016/j.mtcomm.2024.108665

Materials Today Communications

2024

DOI: 10.1016/j.mtcomm.2024.108665

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Grain size distribution analysis of MgO and VC inhibited zirconia toughened alumina ceramics using digital image processing

Moumita Sarkar,

Samik Dutta,

Shitanshu Shekhar Chakraborty

et al.

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2024

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Cited by 2 publications

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Hydraulic modeling of slag cover surface in top-blown molten bath smelting processes assisted by machine learning

Yang,

Yu,

Pan

et al. 2024

Physics of Fluids

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Variation of the slag cover surface (SCS) in the oxygen-enriched top-blown molten bath smelting process is critical for the smelting efficiency of a complex Cu–S concentrate. However, capturing these variation characteristics is difficult because of the high temperature inside the molten bath and the dynamic complexity of the smelting process. In this work, machine learning (i.e., U-net algorithm and support vector machine) is combined with a skillful hydraulic model (i.e., gas–liquid two-phase top-blown agitated vessel) and an experimental measurement strategy to quantitatively explore the variation characteristics of the SCS in an oxygen-enriched top-blown molten bath smelting process. Results showed that a minimum of 30 images, with the smallest size being 900 × 600 pixels, was sufficient for the training process. The data accuracy of the training procedure ranged from 93.20% to 96.23% for identifying the SCS at the laboratory scale. The highest average height of 2.23 cm for the SCS occurred under the operational condition, with a flow rate of 160 L/h, a liquid temperature of 60 °C, and a liquid depth of 0.4 m. The chaotic systems of SCS in industry were deterministic. It was found that the proposed strategy could be used to accurately identify the variation characteristics of the SCS in the gas–liquid two-phase top-blown agitated vessel. The variation of the SCS in the industrial process could be roughly grasped by magnifying the height of the SCS obtained from the experimental data in the laboratory. Quantification of the variation characteristics of the SCS is useful to increase the smelting efficiency of the oxygen-enriched top-blown molten bath smelting process. This also provides insights for multiphase measurements in other studies related to efficient utilization of complex Cu–S concentrates.

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Hydraulic modeling of slag cover surface in top-blown molten bath smelting processes assisted by machine learning

Yang,

Yu,

Pan

et al. 2024

Physics of Fluids

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Improving the Mechanical Properties and Microstructure of 12 mol% Ceria-Stabilized Tetragonal Zirconia Polycrystal Ceramics with Low-Content Nd2O3

Sun,

Li,

Xing

et al. 2024

Materials

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In this study, 12 mol% ceria-stabilized tetragonal zirconia polycrystal ceramics with xNd2O3 (where x equals 0, 0.1, 0.2, 0.3, 0.4, 0.5, and 0.7) were synthesized via the solid-state method, and the effects of Nd2O3 doping amounts on the mechanical properties and microstructure were studied. The results show that with an increase in the Nd2O3 doping amount, the grain size of the ceramics was reduced from 2.93 μm to 0.69 μm. The hardness and strength of the ceramics increased significantly, while the fracture toughness decreased. The reduction in fracture toughness was attributed to the reduction in tetragonal grain size, which suppressed the tetragonal–monoclinic phase transformation caused by stress. Additionally, as the content of Nd2O3 increased, the formation of cubic zirconia accelerated, but no second phase was observed. Most importantly, when the doping amount of Nd2O3 reached 0.3 mol%, the comprehensive mechanical characteristics of the ceramics were optimal. This provides a research basis for the preparation of nanoscale 12 mol% ceria-stabilized tetragonal zirconia polycrystal ceramics.

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Grain size distribution analysis of MgO and VC inhibited zirconia toughened alumina ceramics using digital image processing

Cited by 2 publications

References 41 publications

Hydraulic modeling of slag cover surface in top-blown molten bath smelting processes assisted by machine learning

Hydraulic modeling of slag cover surface in top-blown molten bath smelting processes assisted by machine learning

Improving the Mechanical Properties and Microstructure of 12 mol% Ceria-Stabilized Tetragonal Zirconia Polycrystal Ceramics with Low-Content Nd2O3

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