Theoretical investigation of intrinsic point defects and the oxygen migration behavior in rare earth hafnates

In this work, the composition-dependent point defect types and formation energies of RE₂Hf₂O₇ (RE = La, Ce, Pr, Nd, Pm, Sm, Eu and Gd) as well as the oxygen diffusion behavior are systematically investigated by first-principles calculations. The possible defect reactions and dominant defect complexes under stoichiometric and non-stoichiometric conditions are revealed. It is found that O Frenkel pairs are the predominant defect in stoichiometric pyrochlore hafnates. Hf-RE cation anti-site defects, accompanied by RE vacancies and/or oxygen interstitials, are stable in the non-stoichiometric case of HfO₂ excess. On the other hand, RE-Hf anti-site defects together with oxygen vacancies and/or RE interstitials are preferable in the case of RE₂O₃ excess. The energy barriers for the migration along the V_O48f - V_O48f pathway of pyrochlore hafnates were calculated to be between 0.81 eV and 0.89 eV. Based on these results, a defect engineering strategy is proposed and the pyrochlore hafnates investigated here are predicted to exhibit potential oxygen ionic conductivity.     

CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, it is also a very labor intensive step, which counteracts the perceived value of the resulting model. The state-of-the-art method for automating cylinder detection can detect cylinders with 62% precision and 70% recall, while other shapes must then be segmented manually and shape segmentation is not achieved. This performance is promising, but it is far from drastically eliminating the manual labor cost. We argue that the use of class segmentation deep learning algorithms has the theoretical potential to perform better in terms of per point accuracy and less manual segmentation time needed. However, such algorithms could not be used so far due to the lack of a pre-trained dataset of laser scanned industrial shapes as well as the lack of appropriate geometric features in order to learn these shapes. In this paper, we tackle both problems in three steps. First, we parse the industrial point cloud through a novel class segmentation solution (CLOI-NET) that consists of an optimized PointNET++ based deep learning network and post-processing algorithms that enforce stronger contextual relationships per point. We then allow the user to choose the optimal manual annotation of a test facility by means of active learning to further improve the results. We achieve the first step by clustering points in meaningful spatial 3D windows based on their location. Then, we apply a class segmentation deep network, and output a probability distribution of all label categories per point and improve the predicted labels by enforcing post-processing rules. We finally optimize the results by finding the optimal amount of data to be used for training experiments. We validate our method on the largest richly annotated dataset of the most important to model industrial shapes (CLOI) and yield 82% average accuracy per point, 95.6% average AUC among all classes and estimated 70% labor hour savings in class segmentation. This proves that it is the first to automatically segment industrial point cloud shapes with no prior knowledge at commercially viable performance and is the foundation for efficient industrial shape modeling in cluttered point clouds.     

Evolution of internal cracks and residual stress during deposition of TBC

Thermal barrier coating (TBCs) are ceramic coatings that are deposited on metallic substrates to provide high thermal resistance. Residual stress is among the critical factors that affect the performance of TBCs. It evolves during the process of coating deposition and in-service loading. High residual stresses result in significant cracking and premature delamination of the TBC layer. In the present study, a hybrid computational approach is used to predict the evolution of internal cracks and residual stress in TBC. Smooth particle hydrodynamics (SPH) is first used to model the deposition of yttria-stabilized zirconia (YSZ) layer that contains various interfaces and micropores on a steel substrate. Then, three-dimensional (3D) finite element analysis is utilized to predict the evolution of internal cracks and residual stress in the ceramic coating layer. It is found that multiple cracks emerge during the solidification of the coating layer due to the development of high tensile (quenching) stresses. The cracking density is higher at regions near the coating interface. It is also found that compressive (residual) stresses are developed when the deposited coating is cooled to room temperature. The residual stress state is equibiaxial and nonlinear across the thickness/width of the TBC layer. The residual stress profile predicted compares well with that of hole drilling experiments.     

Thermal and transport properties of as-grown Ni-rich TiNi shape memory alloys

Electrical resistivity, Seebeck coefficient, specific heat and thermal conductivity measurements on the Ti_50−xNi_50+x (x = 0.0–1.6 at.%) shape memory alloys are performed to investigate their thermal and transport properties. In this study, anomalous features are observed in both cooling and heating cycles in all measured physical properties of the slightly Ni-rich TiNi alloys (x ≤ 1.0), corresponds to the transformation between the B19′ martensite and B2 austenite phases. Besides, the transition temperature is found to decrease gradually with increasing Ni content, and the driving force for the transition is also found to diminish slowly with the addition of excess Ni, as revealed by specific heat measurements. While the signature of martensitic transformation vanishes for the Ni-rich TiNi alloys with x ≥ 1.3, the characteristics of strain glass transition start to appear. The Seebeck coefficients of these TiNi alloys were found to be positive, suggesting the hole-type carriers dominate the thermoelectric transport. From the high-temperature Seebeck coefficients, the estimated value of Fermi energy ranges from ∼1.5 eV (Ti_48.4Ni_51.6) to ∼2.1 eV (Ti₅₀Ni₅₀), indicating the metallic nature of these alloys. In addition, the thermal conductivity of the slightly Ni-rich TiNi alloys with x ≤ 1.0 shows a distinct anomalous feature at the B19′ → B2 transition, likely due to the variation in lattice thermal conductivity.     

Pre-martensitic phenomena in Ti40.7Hf9.5Ni44.8Cu5 shape memory alloy

Pre-martensitic phenomena such as abnormal resistivity growth, diffusion scattering, “tweed” contrast and internal friction peak were observed in Ti_40.7Hf_9.5Ni_44.8Cu₅ alloy prior to the forward martensitic transformation on cooling. It was shown that all the observed phenomena were due to the formation of quasi-static strain nanodomains in the B2 phase prior to the forward martensitic transformation. This led to accumulation of the elastic energy before the phase transition and resulted in the variation in thermodynamic balance for the forward martensitic transformation and, as a result, influenced the parameters of the phase transition. The appearance of elastic energy prior to the forward transformation caused a decrease in the forward and reverse martensitic transformations' start temperatures, a widening of the temperature range of the reverse transformation and an increase in the hysteresis of the transformation.     

Deformation mechanism in NiAl single crystals at low temperatures

Available data on the temperature dependence of yield stress and of associated activation volume of high-purity NiAl single crystals between 76 and 205 K have been analyzed within the framework of a solid-solution hardening model, which is based on the concept of depinning of an edge-dislocation segment from several randomly dispersed, isolated, point defects simultaneously. The vacancies in NiAl single crystals act as point-defect obstacles to the stress-assisted thermally-activated glide of edge dislocations, and their concentration is estimated as about 10 at.%. The product of yield stress and associated activation volume (≈0.146 eV) is found to be independent of temperature and yield stress, as envisaged in the model.     

The native point defects in C14 Mg2Ca Laves phase: A first-principles study

The native point defects in C14 Mg₂Ca Laves phase are studied from the first-principles density functional theory calculations within GGA approximation. The defect formation energies indicate that anti-site defects are energetically favored over vacancies. Under Mg-rich and even general Ca-rich condition, defect Mg_Ca of Mg anti-site on Ca sublattice is favorable owing to the lowest formation energy. The Ca_Mg2 defect of Ca anti-site on Mg2 sublattice is also likely dominant only under extreme Ca-rich environment. The present results could explain reasonably the asymmetric off-stoichiometry of Mg₂Ca. The effective point defect concentrations of Mg₂Ca as a function of composition and temperature at experimental range are also calculated from a canonical statistical model, and the derived results show a linear relationship between the logarithm of defect concentration and T⁻¹. Geometrical factor is further studied, and it is found that atomic size possesses an obvious influence on the structure of point defect in Mg₂Ca. The electronic feature is further studied to reveal underlying mechanism for formation of point defects.     

Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

Structural failures (bridge or building collapses) and geohazards (landslides, ground subsidence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made structures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems.One of the most used techniques for real-time deformation monitoring is the Global Navigation Satellite System (GNSS) real-time procedure, where the relative positioning approach, using a well-known reference station, has been applied.This study was conducted to evaluate the actual quality of the real-time kinematic Precise Point Positioning (PPP) GNSS solution for deformation monitoring, where it can be concluded that a promise tool is under development and should be taken into account on actual and near future real-time deformation monitoring studies and applications.     

基于线特征及迭代最近点算法的地基建筑物点云自动配准方法

为克服迭代最近点(ICP)算法易陷入局部最优的缺陷，提出一种基于线特征及ICP算法的地基建筑物点云自动配准方法。首先，基于法向一致性进行建筑物点云平面分割；接着，采用alpha-shape算法进行点簇轮廓线提取，并拆分和拟合处理得到特征线段；然后，以线对作为配准基元，以线对夹角和距离作为相似性测度进行同名特征匹配，实现建筑物点云的粗配准；最后，以粗配准结果为初值，进一步采用ICP算法完成点云精确配准。利用两组部分重叠的建筑物点云进行配准实验，实验结果表明，采用由粗到精的配准方法能有效改善ICP算法对初值依赖的问题，实现具有部分重叠的建筑物点云的有效配准。     

Defect structure and transport properties in (Co,Cu,Mg,Ni,Zn)O high entropy oxide

The defect structure and chemical diffusion in the (Co,Cu,Mg,Ni,Zn)O high entropy oxide were investigated. The material was synthesized in a form of pellets by means of a solid-state reaction, through sintering the mixture of composing oxides at 1273 K for 20 h, followed by the air quenching. The presence of the single-phase, high entropy solid solution structure was confirmed with the use of SEM + EDS and XRD methods and later confirmed after each of the experimental steps. The modification of the standard marker experiment was applied, to determine the predominantly disordered sublattice, which turned out to be the anionic one. The nonstoichiometry and its dependence on the oxygen partial pressure were investigated by means of the thermogravimetric method. The results allowed establishing the (Co,Cu,Mg,Ni,Zn)O_1-y general formula, with values of y reaching values as high as 0.07 under low oxygen partial pressures. The non-logarithmic character of the obtained pressure dependence suggests the presence of a complex structure of interacting point defects. The chemical diffusion coefficient was also determined, based on the measured re-equilibration kinetics. The obtained values of diffusivity are within the range typical for the transition metal oxides, do not confirm the presence of the sluggish diffusion effect in high entropy oxides. The established strong dependence of the chemical diffusion coefficient on the p(O₂), further confirms the presence of the complex defect structure.