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This work addresses a novel technique for selecting the best process parameters for the 4H–SiC epitaxial layer in a horizontal hot-wall chemical vapor reactor using a transient multi-physical (thermal-fluid-chemical) simulation model and combined with a machine-learning model. An experiment was performed to validate the feasibility of the numerical model. Secondly, a single-factor analysis was conducted to investigate the effects of process parameters, including the deposition temperature, inlet-flow volume, rotational speed of the susceptor, and cavity pressure, on the quality of the 4H–SiC epitaxial layer. Finally, a machine learning algorithm, the ant colony optimization-back propagation neural network (ACO–BPNN), was employed to develop the input/output model and optimize process parameters for obtaining a high-quality epitaxial layer and reducing the optimization cycle and costs. Notably, the optimized process was validated by real experiments, where the error between calculation and experiment is 4.03 % for deposition rate and 0.49 % for coefficient of variation, respectively. The results highlight the model as reliable and lay the foundation for the CVD growth of the 4H–SiC epitaxial layer.
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This work addresses a novel technique for selecting the best process parameters for the 4H–SiC epitaxial layer in a horizontal hot-wall chemical vapor reactor using a transient multi-physical (thermal-fluid-chemical) simulation model and combined with a machine-learning model. An experiment was performed to validate the feasibility of the numerical model. Secondly, a single-factor analysis was conducted to investigate the effects of process parameters, including the deposition temperature, inlet-flow volume, rotational speed of the susceptor, and cavity pressure, on the quality of the 4H–SiC epitaxial layer. Finally, a machine learning algorithm, the ant colony optimization-back propagation neural network (ACO–BPNN), was employed to develop the input/output model and optimize process parameters for obtaining a high-quality epitaxial layer and reducing the optimization cycle and costs. Notably, the optimized process was validated by real experiments, where the error between calculation and experiment is 4.03 % for deposition rate and 0.49 % for coefficient of variation, respectively. The results highlight the model as reliable and lay the foundation for the CVD growth of the 4H–SiC epitaxial layer.
Journal article(2023)
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Abdullah M. Tawfek, Zhi Ge, Jian Li, Kangkang Zhang, Nengdong Jiang, Yingxuan Shao, Yifeng Ling, Branko Šavija
An engineered cementitious composite (ECC) belongs to a type of high-performance fiber-reinforced materials. Fiber alignment causes the anisotropy of such materials. Herein, the influence of the fiber orientation on water and ion penetration into an ECC was studied. Fiber alignment was achieved using an extrusion approach. Water absorption, sorptivity, chloride penetration resistance, sulfate attack resistance, and freezing–thawing resistance of specimens with fiber aligned horizontally (AH), vertically (AV), and randomly (R), corresponding to the direction of the exposure surface that was studied. The results showed that fibers oriented perpendicular to the water path delayed water migration into the ECC matrix. The sorptivity was significantly affected by the fiber direction. The sorptivity of the AH specimens was 35% and 13% lower than that of the AV and R specimens, respectively. After 180 days of exposure, the chloride penetration depth of the AH specimens was 5.7 mm, which is 13.6% and 20.8% lower than that of the AV and R specimens, respectively. The sulfate ingress profile indicates that the fiber–matrix interface oriented perpendicular to the penetration path can effectively delay sulfate migration. The fiber orientation also influences the compressive strength gain under immersion conditions (Na2SO4 solution, Na2SO4 + NaCl solution, and water). Compared with the AH and R specimens, the AV specimens are more sensitive to the immersion condition. In contrast, the fiber orientation has no significant effect on ECC specimens under freeze–thaw cycles. These findings indicate that controlling the fiber alignment and orientation in an ECC can improve its durability under certain exposure conditions.
...
An engineered cementitious composite (ECC) belongs to a type of high-performance fiber-reinforced materials. Fiber alignment causes the anisotropy of such materials. Herein, the influence of the fiber orientation on water and ion penetration into an ECC was studied. Fiber alignment was achieved using an extrusion approach. Water absorption, sorptivity, chloride penetration resistance, sulfate attack resistance, and freezing–thawing resistance of specimens with fiber aligned horizontally (AH), vertically (AV), and randomly (R), corresponding to the direction of the exposure surface that was studied. The results showed that fibers oriented perpendicular to the water path delayed water migration into the ECC matrix. The sorptivity was significantly affected by the fiber direction. The sorptivity of the AH specimens was 35% and 13% lower than that of the AV and R specimens, respectively. After 180 days of exposure, the chloride penetration depth of the AH specimens was 5.7 mm, which is 13.6% and 20.8% lower than that of the AV and R specimens, respectively. The sulfate ingress profile indicates that the fiber–matrix interface oriented perpendicular to the penetration path can effectively delay sulfate migration. The fiber orientation also influences the compressive strength gain under immersion conditions (Na2SO4 solution, Na2SO4 + NaCl solution, and water). Compared with the AH and R specimens, the AV specimens are more sensitive to the immersion condition. In contrast, the fiber orientation has no significant effect on ECC specimens under freeze–thaw cycles. These findings indicate that controlling the fiber alignment and orientation in an ECC can improve its durability under certain exposure conditions.
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