8 research outputs found

    Effect of thermal cycling frequency on the durability of Yb-Gd-Y-based thermal barrier coatings

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    The effects of thermal cycling frequency and buffer layer on the crack generation and thermal fatigue behaviors of Yb–Gd–Y-stabilized zirconia (YGYZ)-based thermal barrier coatings (TBCs) were investigated through thermally graded mechanical fatigue (TGMF) test. TGMF tests with low- (period of 10 min) and high-frequency (period of 2 min) cycling were performed at 1100 °C with a 60 MPa tensile load. Different cycling frequencies in TGMF test generate two kinds of crack propagation modes. The sample with low-frequency cycling condition shows penetration cracks in the YGYZ top coat, and multiple narrow vertical cracks are generated in high-frequency cycling. To enhance the thermomechanical properties, different buffer layers were introduced into the TBC systems, which were deposited with the regular (RP) or high-purity 8 wt% yttria stabilized zirconia (HP-YSZ) feedstock. The purity of the feedstock powder used for preparing the buffer layer affected the fracture behavior, showing a better thermal durability for the TBCs with the HP-YSZ in both frequency test conditions. A finite element model is developed, which takes creep effect into account due to thermal cycling. The model shows the high stresses at the interfaces between different layers due to differential thermal expansion. The failure mechanisms of YGYZ-based TBCs in TGMF test are also proposed. The vertical cracks are preferentially created, and then the vertical and horizontal cracks will be propagated when the vertical cracks are impeded by pores and micro-cracks

    Crack-Growth Behavior in Thermal Barrier Coatings with Cyclic Thermal Exposure

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    Crack-growth behavior in yttria-stabilized zirconia-based thermal barrier coatings (TBCs) is investigated through a cyclic thermal fatigue (CTF) test to understand TBCs’ failure mechanisms. Initial cracks were introduced on the coatings’ top surface and cross section using the micro-indentation technique. The results show that crack length in the surface-cracked TBCs grew parabolically with the number of cycles in the CTF test. Failure in the surface-cracked TBC was dependent on the initial crack length formed with different loading levels, suggesting the existence of a threshold surface crack length. For the cross section, the horizontal crack length increased in a similar manner as observed in the surface. By contrast, in the vertical direction, the crack did not grow very much with CTF testing. An analytical model is proposed to explain the experimentally-observed crack-growth behavior

    Crack-Resistance Behavior of an Encapsulated, Healing Agent Embedded Buffer Layer on Self-Healing Thermal Barrier Coatings

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    In this work, a novel thermal barrier coating (TBC) system is proposed that embeds silicon particles in coating as a crack-healing agent. The healing agent is encapsulated to avoid unintended reactions and premature oxidation. Thermal durability of the developed TBCs is evaluated through cyclic thermal fatigue and jet engine thermal shock tests. Moreover, artificial cracks are introduced into the buffer layer’s cross section using a microhardness indentation method. Then, the indented TBC specimens are subject to heat treatment to investigate their crack-resisting behavior in detail. The TBC specimens with the embedded healing agents exhibit a relatively better thermal fatigue resistance than the conventional TBCs. The encapsulated healing agent protects rapid large crack openings under thermal shock conditions. Different crack-resisting behaviors and mechanisms are proposed depending on the embedding healing agents

    Fracture behavior and thermal durability of lanthanum zirconate-based thermal barrier coatings with buffer layer in thermally graded mechanical fatigue environments

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    The effects of buffer layer on the fracture behavior and lifetime performance of lanthanum zirconate (La2Zr2O7; LZO)-based thermal barrier coatings (TBCs) were investigated through thermally graded mechanical fatigue (TGMF) tests, which are designed to simulate the operating conditions of rotating parts in gas turbines. To improve the thermal durability of LZO-based TBCs, composite coats consisting of two feedstock powders of LZO and 8 wt% yttria-doped stabilized zirconia (8YSZ) were prepared by mixing different volume ratios (50:50 and 25:75, respectively). The composite coat of 50:50 volume ratio was employed as the top coat, and two types of buffer layers were introduced (25:75 volume ratio in LZO and 8YSZ, and 8YSZ only). These TBC systems were compared with a reference TBC system of 8YSZ. The TGMF tests with a tensile load of 60 MPa were performed for 1000 cycles, at a surface temperature of 1100 °C and a dwell time of 10 min, and then the samples were cooled at room temperature for 10 min in each cycle. For the single-layer TBCs, the composite top coat showed similar results as for the reference TBC system. The triple-layer coating (TLC) showed the best thermal cycle performance among all samples, suggesting that the buffer layer was efficient in improving lifetime performance. Failure modes were different for the TBC systems. Delamination and/or cracks were created at the interface between the bond and top coats or above the interface in the single-layer TBCs, but the TBCs with the buffer layer were delaminated and/or cracked at the interface between the buffer layer and the top coat, independent of buffer layer species. This study allows further understanding of the LZO-based TBC failure mechanisms in operating conditions, especially in combined thermal and mechanical environments, in order to design reliable TBC systems

    Experimental and Modeling Studies of Bond Coat Species Effect on Microstructure Evolution in EB-PVD Thermal Barrier Coatings in Cyclic Thermal Environments

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    In this work, the effects of bond coat species on the thermal barrier coating (TBC) microstructure are investigated under thermal cyclic conditions. The TBC samples are prepared by electron beam-physical vapor deposition with two species of bond coats prepared by either air-plasma spray (APS) or high-velocity oxygen fuel (HVOF) methods. The TBC samples are evaluated in a variety of thermal cyclic conditions, including flame thermal fatigue (FTF), cyclic furnace thermal fatigue (CFTF), and thermal shock (TS) tests. In FTF test, the interface microstructures of TBC samples show a sound condition without any delamination or cracking. In CFTF and TS tests, the TBCs with the HVOF bond coat demonstrate better thermal durability than that by APS. In parallel with the experiments, a finite element (FE) model is developed. Using a transient thermal analysis, the high-temperature creep-fatigue behavior of the TBC samples is simulated similar to the conditions used in CFTF test. The FE simulation predicts a lower equivalent stress at the interface between the top coat and bond coat in bond coat prepared using HVOF compared with APS, suggesting a longer cyclic life of the coating with the HVOF bond coat, which is consistent with the experimental observation

    Non-invasive biomarkers for liver inflammation in non-alcoholic fatty liver disease: present and future

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    Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD
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