The effect of Cr impurity to superconductivity in electron-doped BaFe2-xNixAs2

We use transport and magnetization measurements to study the effect of Cr-doping to the phase diagram of the electron-doped superconducting BaFe2-xNixAs2 iron pnictides. In principle, adding Cr to electron-doped BaFe2-xNixAs2 should be equivalent to the effect of hole-doping. However, we find that Cr doping suppresses superconductivity via impurity effect, while not affecting the normal state resistivity above 100 K. We establish the phase diagram of Cr-doped BaFe2-x-yNixCryAs2 iron pnictides, and demonstrate that Cr-doping near optimal superconductivity restore the long-range antiferromagnetic order suppressed by superconductivity.Comment: 10 pages, 5 figure

SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data

Manually annotating complex scene point cloud datasets is both costly and error-prone. To reduce the reliance on labeled data, a new model called SnapshotNet is proposed as a self-supervised feature learning approach, which directly works on the unlabeled point cloud data of a complex 3D scene. The SnapshotNet pipeline includes three stages. In the snapshot capturing stage, snapshots, which are defined as local collections of points, are sampled from the point cloud scene. A snapshot could be a view of a local 3D scan directly captured from the real scene, or a virtual view of such from a large 3D point cloud dataset. Snapshots could also be sampled at different sampling rates or fields of view (FOVs), thus multi-FOV snapshots, to capture scale information from the scene. In the feature learning stage, a new pre-text task called multi-FOV contrasting is proposed to recognize whether two snapshots are from the same object or not, within the same FOV or across different FOVs. Snapshots go through two self-supervised learning steps: the constrstive learning step with both part contrasting and scale contrasting, followed by a snapshot clustering step to extract higher level semantic features. Then a weakly-supervised segmentation stage is implemented by first training a standard SVM classifier on the learned features with a small fraction of labeled snapshots. Then trained SVM is further used to predict labels for input snapshots and predicted labels are converted into point-wise label assignments for semantic segmentation of the entire scene using a voting procedure. The experiments are conducted on the Semantic3D dataset and the results have shown that the proposed method is capable of learning effective features from snapshots of complex scene data without any labels. Moreover, the proposed weakly-supervised method has shown advantages when comparing to the state of the art method on weakly-supervised point cloud semantic segmentation

Thermal properties of La2Zr2O7 double-layer thermal barrier coatings

La2Zr2O7 is a promising thermal barrier coating (TBC) material. In this work, La2Zr2O7 and 8YSZ-layered TBC systems were fabricated. Thermal properties such as thermal conductivity and coefficient of thermal expansion were investigated. Furnace heat treatment and jet engine thermal shock (JETS) tests were also conducted. The thermal conductivities of porous La2Zr2O7 single-layer coatings are 0.50–0.66 W m−1 °C−1 at the temperature range from 100 to 900°C, which are 30–40% lower than the 8YSZ coatings. The coefficients of thermal expansion of La2Zr2O7 coatings are about 9–10 × 10−6 °C−1 at the temperature range from 200 to 1200°C, which are close to those of 8YSZ at low temperature range and about 10% lower than 8YSZ at high temperature range. Double-layer porous 8YSZ plus La2Zr2O7 coatings show a better performance in thermal cycling experiments. It is likely because porous 8YSZ serves as a buffer layer to release stress

Microstructural non-uniformity and mechanical property of air plasma-sprayed dense lanthanum zirconate thermal barrier coating

Lanthanum zirconate is a promising thermal barrier coating material. In this work, imaging technique was used to characterize the microstructural non-uniformity of the coating. The imaging analyses revealed that, along the thickness of the coating, the cracks were primarily horizontal in the top and middle regions, while vertical cracks became dominant in the bottom region. The calculated porosities showed a non-uniformity (4.8%, 5.3%, and 5.5% in the top, middle, and bottom regions, respectively). They were lower than the experimentally measured one, 7.53%, using the Archimedes method. This is because imaging analysis does not take internal porosity into account. Additionally, the measured Vickers hardness was 5.51±0.25 GPa, nanoindentation hardness was 8.8±2.1 GPa, and Young's modulus was 156.00±10.03 GPa

Lanthanum Zirconate Based Thermal Barrier Coatings: A Review

This review article summarizes the latest information about the manufacturing techniques of lanthanum zirconate (La2Zr2O7, LZ) powder and La2Zr2O7 based thermal barrier coatings (TBCs). Lanthanum zirconate is a promising candidate material for TBC applications, due to its lower thermal conductivity and higher thermal stability compared to other traditional TBC systems. In this work, the physical, thermal, and mechanical properties of the powder and coatings are evaluated. The durability experiments of the TBCs in various thermal, mechanical, and corrosive conditions are also reviewed. In addition, theoretical studies on the powder and coatings properties are presented. Finally, future research directions of lanthanum zirconate as TBC applications are proposed

STUDY OF THE THERMAL AND MECHANICAL PROPERTIES OF LA2ZR2O7 USING FIRST PRINCIPLE METHOD

poster abstractAs an advanced thermal barrier coating, Lanthanum zirconia (La2Zr2O7) has been studied in this paper using first principle calculations. La2Zr2O7 crystal bulk was used in this calculation. The lattice parameter, mechanical and thermal properies of La2Zr2O7 were investigated by means of density functional theory (DFT). Hydrostatic pressure-dependent elasticity constant, bulk modulus were calculated. The thermal conductivity was calculated based on fick’s law using a 20 layers supercell. La2Zr2O7 coating samples were spraied by APS equipment, the coating samples were identified by XRD and observed by optical microscope. The thermal effect of Ce doping of the La2Zr2O7 were studied by ab initial calculations. The calculated properties have considerable good agreement with others experimental and calculation results

Study About the Minimum Value at Risk of Stock Index Futures Hedging Applying Exponentially Weighted Moving Average - Generalized Autoregressive Conditional Heteroskedasticity Model

What investors often wish to insure is that the maximum possible loss of their portfolios falling below a certain value. Namely, the maximum possible loss that a portfolio will lose under normal market fluctuations, with a given confidence level, over a certain time horizon, it is known shortly as “value at risk (VaR).” However, when it comes to the hedging strategy taking in the derivative markets for the minimum VaR, many investors simply thinking it is a hedging ratio in one at beginning, then a lot of effective model came out from both academia and industry over the years.We pioneer deriving a combined and dynamic hedging model- exponentially weighted moving average-generalized autoregressive conditional heteroskedasticity (GARCH) (1,1)-M applicable to the real financial markets based on previous studies. The results in this paper turn out that the model we build is not only excellent for the pursuit for the minimum VaR but also practical for the actual situation where the variances of financial price data are time-varying.In this paper we calculate the optimal decay factor 0.93325 which is the best match to the Hu-Shen 300 stock index market, withdraw uniform 0.9400, and use the Cornish-Fisher function to correct the quantile of the normal distribution, get the final hedging ratios and the minimum VaR. Keywords: Minimum Value At Risk, Hedging Model, Decay Factor, Cornish-Fisher, Exponentially Weighted Moving Average -Generalized Autoregressive Conditional Heteroskedasticity (1,1)-M Model JEL Classification: G1

Ideal tensile strength and shear strength of ZrO2(111)/Ni(111) ceramic-metal Interface: A first principle study

The ideal mechanical strengths of ZrO2(111)/Ni(111) ceramic-metal (C-M) interface are calculated through simulated tensile and shear deformations using the first principles calculations. The structures of ZrO2(111)/Ni(111) interfaces with 1- and 3-layer Ni thicknesses are optimized and the mechanical properties are investigated. For tensile deformation in [111] direction, the Young's moduli of the 1-layer Ni and 3-layer Ni M-C models are 139.9 GPa and 60.2 GPa, respectively; and ultimate tensile strengths are 11.6 GPa and 7.9 GPa, respectively. For shear deformation in {111} 〈110〉 system, the shear moduli of the 1-layer Ni and 3-layer Ni M-C models are 43.9 GPa and 30.4 GPa, respectively; and ultimate shear strengths are 7.0 GPa and 3.0 GPa, respectively. For shear deformation in {111} 〈11View the MathML source〉 system, the shear moduli of the 1-layer Ni and 3-layer Ni M-C models are 30.9 GPa and 17.3 GPa, respectively; and ultimate shear strengths are 6.0 GPa and 1.8 GPa, respectively. Overall, 1-layer Ni C-M interface models have better mechanical properties than those of 3-layer models. The observed strengths are explained by using charge distribution, electron localization function, and Bader charge transfer analyses. The results are important for designing robust thermal barrier coating through optimizing bond coat thickness

Doping evolution of antiferromagnetism and transport properties in the non-superconducting BaFe2-2xNixCrxAs2

We report elastic neutron scattering and transport measurements on the Ni and Cr equivalently doped iron pnictide BaFe$_{2-2x}$Ni$_{x}$Cr$_{x}$As$_{2}$. Compared with the electron-doped BaFe$_{2-x}$Ni$_{x}$As$_{2}$, the long-range antiferromagnetic (AF) order in BaFe$_{2-2x}$Ni$_{x}$Cr$_{x}$As$_{2}$ is gradually suppressed with vanishing ordered moment and N\'{e}el temperature near $x= 0.20$ without the appearance of superconductivity. A detailed analysis on the transport properties of BaFe$_{2-x}$Ni$_{x}$As and BaFe$_{2-2x}$Ni$_{x}$Cr$_{x}$As$_{2}$ suggests that the non-Fermi-liquid behavior associated with the linear resistivity as a function of temperature may not correspond to the disappearance of the static AF order. From the temperature dependence of the resistivity in overdoped compounds without static AF order, we find that the transport properties are actually affected by Cr impurity scattering, which may induce a metal-to-insulator crossover in highly doped BaFe$_{1.7-y}$Ni$_{0.3}$Cr$_{y}$As$_{2}$.Comment: 10 pages, 12 figure