Effect of holding time and pressure on the densification, microstructure and mechanical properties of hot pressed Al2O3-CA6-ZrO2/Ni multi-phase composites

Zhang, Xi; Han, Xiaoyu; Zhang, Yuedan; Liang, Jinglong; Wang, Chuang; Liang, Jinsheng

doi:10.1016/j.jallcom.2020.156783

Cited by 5 publications

(4 citation statements)

References 42 publications

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“…53 Figure 16 shows one of the DTs, which comprises the FS and MI prediction models. The first criteria of classification in the DTs are X [44] and X [21], which refer to F004 in Figure 16A and P022 in Figure 16B. In addition to F004 and P022, many types of materials could be used as the criteria for classification.…”

Section: Discussionmentioning

confidence: 99%

“…The test apparatus has a high maintenance cost and space limitations for installation and use, and it requires a high cost for producing the necessary specimen. 44 The proposed model is therefore expected to help reduce this testing cost. MI refers to the weight of the resin that flows through a capillary for 10 min at a certain load and temperature.…”

Section: Data Setmentioning

confidence: 99%

“…The three‐point bending method is generally used to measure FS. The test apparatus has a high maintenance cost and space limitations for installation and use, and it requires a high cost for producing the necessary specimen 44 . The proposed model is therefore expected to help reduce this testing cost.…”

Section: Prediction Model Developmentmentioning

confidence: 99%

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Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

Joo

Park

Lim

et al. 2021

Int J of Intelligent Sys

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The physical properties required in polypropylene composites (PPCs) vary depending on the purpose of use. In the manufacturing of PPCs, it is crucial to determine the types and quantities of numerous reinforcements to meet the required physical properties. Owing to industrial complexity, most PPC manufacturers produce the composites repeatedly until the desired physical properties are obtained. Hence, to reduce trial and error, we developed prediction models for the physical properties of PPCs based on commercial recipe data. The recipe data included information about five physical properties of composites manufactured using 90 materials. In complex industrial environments, because one recipe is usually composed of 2–12 materials, numerous combinations of data sets are created. It causes the lack of the same material combination data sets and thus makes it difficult to develop a good performance model. Therefore, a novel categorization process is suggested as data preprocessing to overcome the data imbalance problem. The models for predicting the five physical properties (flexural strength, melting index, tensile strength, specific gravity, and flexural modulus) were developed using random forest, and the performance of the prediction models was improved via hyperparameter optimization. Furthermore, the effects of the materials on the performance of the models were numerically described through variable importance analysis. Finally, a software was developed to implement the prediction models in the industry. The software was applied to a commercial composite and achieved high accuracy, demonstrating the effectiveness of this study. Thus, the software suggests decision‐making solutions to save cost and time by reducing the trial and error in the industrial environment with high complexity.

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Section: Discussionmentioning

confidence: 99%

Section: Data Setmentioning

confidence: 99%

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Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

Joo

Park

Lim

et al. 2021

Int J of Intelligent Sys

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“…Appropriate sintering temperature could accelerate the densification process and improve the microstructure and mechanical properties of Fe/FeAl2O4 composites finally. The effect of the sintering temperature on the mechanical properties of the Fe/FeAl 2 O 4 composite can be explained using a dynamical theory for diffusion during mass transfer [24,25]:…”

Section: Discussionmentioning

confidence: 99%

Effect of Sintering Temperature on Microstructure and Mechanical Properties of Hot-Pressed Fe/FeAl2O4 Composite

Zhang

Yan

et al. 2021

Crystals

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An Fe/FeAl2O4 composite was prepared with Fe-Fe2O3-Al2O3 powder by a hot press sintering method. The mass ratio was 6:1:2, sintering pressure was 30 MPa, and holding time was 120 min. The raw materials for the powder particles were respectively 1 µm (Fe), 0.5 µm (Fe2O3), and 1 µm (Al2O3) in diameter. The effect of sintering temperature on the microstructure and mechanical properties of Fe/FeAl2O4 composite was studied. The results showed that Fe/FeAl2O4 composite was formed by in situ reaction at 1300 °C–1500 °C. With the increased sintering temperature, the microstructure and mechanical properties of the Fe/FeAl2O4 composite showed a change law that initially became better and then became worse. The best microstructure and optimal mechanical properties were obtained at 1400 °C. At this temperature, the grain size of Fe and FeAl2O4 phases in Fe/FeAl2O4 composite was uniform, the relative density was 96.7%, and the Vickers hardness and bending strength were 1.88 GPa and 280.0 MPa, respectively. The wettability between Fe and FeAl2O4 was enhanced with increased sintering temperature. And then the densification process was accelerated. Finally, the microstructure and mechanical properties of the Fe/FeAl2O4 composite were improved.

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Microstructure evolution and mechanical properties of 3YSZ/Ni composites with uniform phase distribution prepared by core-shell structure microspheres

Qi,

Liang,

Wang

et al. 2023

Ceramics International

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Effect of holding time and pressure on the densification, microstructure and mechanical properties of hot pressed Al2O3-CA6-ZrO2/Ni multi-phase composites

Cited by 5 publications

References 42 publications

Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

Effect of Sintering Temperature on Microstructure and Mechanical Properties of Hot-Pressed Fe/FeAl2O4 Composite

Microstructure evolution and mechanical properties of 3YSZ/Ni composites with uniform phase distribution prepared by core-shell structure microspheres

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