Search

Although a high-quality homoepitaxial layer of 4H‑silicon carbide (4H-SiC) can be obtained on a 4° off-axis substrate using chemical vapor deposition, the reduction of defects is still a focus of research. In this study, several kinds of surface defects in the 4H-SiC homoepitaxial layer are systemically investigated, including triangles, carrots, surface pits, basal plane dislocations, and step bunching. The morphologies and structures of surface defects are further discussed via optical microscopy and potassium hydroxide-based defect selective etching analysis. Through research and analysis, we found that the origin of surface defects in the 4H-SiC homoepitaxial layer can be attributed to two aspects: the propagation of substrate defects, such as scratches, dislocation, and inclusion, and improper process parameters during epitaxial growth, such as in-situ etch, C/Si ratio, and growth temperature. It is believed that the surface defects in the 4H-SiC homoepitaxial layer can be significantly decreased by precisely controlling the chemistry on the deposition surface during the growth process.

We demonstrate the surface defect type, density and related electrical modification of graphene sheet generated by 193-nm ArF excimer laser irradiation on n-type 4H-SiC. The charge density difference and partial density of states (PDOS) carried out by density functional theory (DFT) calculations predict the graphene with lattice imperfection can induce virtual bound states at the vacancy sites and Fermi level shift compared to perfect graphene. The surface defects density of laser generated graphene is characterized by nanoscale electrical measurements using the conductive atomic force microscope (c-AFM). The corresponding current–voltage (I–V) curves show that the electronic charge transfers, thereby electrical conductivities of laser generated graphene, are influenced by the lattice defects. The defect densities are tunable by change laser fluence and pulse number. This research provides an understanding of the interfacial transport properties between laser generated graphene and 4H-SiC through a detailed analysis of surface defects.

Microscopic morphologies of reticular cracks in Nb-bearing pipeline surfaces are shown in this work. A decarburization layer, oxidized round spots, and the distributions of residual elements are each detected to better understand the mechanisms of reticular crack formations. The results show that reticular cracks are discontinuously distributed and filled with iron oxide. The oxidized round spots near the crack sides are larger and more intensive than steel matrix, with primary chemical compositions of Fe, Mn, and Si oxides. There is no obvious enrichment of Cu, Cr, or Sn near the crack zones. The formation of reticular cracks occurs prior to both decarburization and the formation of oxidized round spots. The ferrite potential (FP) of the examined pipeline steel is 1.05, which leads to a higher relative crack susceptibility. It is concluded that reticular cracks are generated during the continuous casting solidification process due to the extension of intergranular microcracks along grain boundaries under the abnormal conditions of the continuous casting process.

Among diamond-like carbon (DLC) coatings, tetrahedral amorphous carbon (ta-C) coatings show particularly high thermal stability and oxidation resistance due to their high sp3 content and hydrogen-free structure. On the other hand, it is well known that high-temperature annealing leads to degradation of the ta-C structure, resulting in a release of stress, decrease of hardness, increase in surface roughness, and transformation of the coating nature. Although optical observation is a powerful candidate for imaging the surface conditions of ta-C coatings, strong light emission due to high temperature prevents the acquisition of clear images. In this paper, we establish a novel in situ observation method using environment scanning electron microscopy (ESEM), which allows us to view ta-C surface defects and droplets at 650 °C. A heater embedded in the ESEM increased the temperature on ta-C coatings to 650 °C at gas pressure of 120 Pa. Using a variety of gas conditions including ambient air, dry nitrogen, or dry oxygen, we clarified the effect of the gases on the degradation of the defects. In a dry oxygen atmosphere, defects grew dramatically with annealing time, whereas nitrogen caused no significant transformation to ta-C surfaces. Raman spectroscopy analysis revealed significant structural change in one type of defect, while no noticeable Raman shift was detected in the other type. A focused ion beam created a cross-section of an annealed defect on the ta-C coating. Subsequently, energy dispersive X-ray spectroscopy (EDS) revealed the characteristics of defect growth; one type of defect was associated with a droplet on the interlayer, and the other with graphitization due to oxidization of ta-C on the droplets., ファイル公開：2021-03-25

Nanoindentation on a platinum thin film with surface defects in a rectangular shape and triangular shape was simulated using the quasicontinuum method to study the shape effect of surface defects on nanohardness. The results show that the nanohardness of thin film with triangular defects is basically larger than those with rectangular defects, which is closely related to the height of the surface defects at the boundary near to the indenter. Moreover, the triangular defect might have an enhancement effect on nanohardness by a certain size of the defects and the boundary orientation of the defect, where such an enhancement effect increases as the defect grows. Furthermore, the nanohardness decreases when the defect is folded from wide to narrow in the same atom cavity, and particularly expresses a more obvious drop when the height of the defects increases. In addition, larger sizes of the rectangular defect induce more reduction in nanohardness, while the nanohardness of the triangular surface defect is sensitive to the periodic arrangement of atoms changed by the boundary orientation of the defect, which is well explained and demonstrated by the calculation formula theory of necessary load for dislocation emission.

Metal matrix composites (MMCs) are promising alternatives to metallic alloys. Their high strength-to-weight ratios; high temperature stabilities; and unique thermal, electrical, and chemical properties make them suitable for automotive, aerospace, defense, electrical, electronic, energy, biomedical, and other applications. The wide range of potential combinations of materials allows the properties of MMCs to be tailored by manipulating the morphology, size, orientation, and fraction of reinforcement, offering further opportunities for a variety of applications in daily life. This Special Issue, “Metal Matrix Composites”, addresses advances in the material science, processing, material modeling and characterization, performance, and testing of metal matrix composites.

This paper addresses a comprehensive and further insight into the sensitivity of material removal and the surface defect formation mechanism to scratch depth during single-grit scratch tests of 50 vol% SiCp/Al composites. The three-dimensional (3D) finite element model with more realistic 3D micro-structure, particle-matrix interfacial behaviors, particle-particle contact behaviors, particle-matrix contact behaviors and a Johnson-Holmquist-Beissel (JHB) model of SiC was developed. The scratch simulation conducted at scratch velocity 10 mm/min and loading rate 40 N/min revealed that the scratch depth plays a crucial role in material removal and the surface forming process. Brittle fracturing of SiC particles and surface defects become more deteriorative under a large scratch depth ranging from 0.0385 to 0.0764 &mu, m. The above phenomenon can be attributed to the influence of scratch depth on SiC particles&rsquo, transport, the increase in the amount of SiC particle transport resulting from an increase of scratch depth raises the occurrence of particle-particle collision which provides hard support and shock for the scratched particles, therefore, brittle fracturing gradually becomes the major removal mode of SiC particles as the scratch depth increases. On the deteriorative surface, various defects are observed, i.e., lateral cracks, interfacial debonding, cavies filled with residually broken particles, etc. The von Mises stress distribution shows that SiC particles bear vast majority of load, and thus present greater stress than the surrounding Al matrix. For example: their ratio of 3 to 30 under the scratch depth of 0.011 mm. Namely, SiC particles impede stress diffusion within the Al matrix. Finally, the SEM images of the scratched surface obtained from the single-grit scratch experiments verify the numerical analysis&rsquo, s results.

Defective shafts need to be classified because some defective shafts can be reworked to avoid replacement costs. Therefore, the detection and classification of shaft surface defects has important engineering application value. However, in the factory, shaft surface defect inspection and classification are done manually, with low efficiency and reliability. In this paper, a deep learning method based on convolutional neural network feature extraction is used to realize the object detection and classification of metal shaft surface defects. Through image segmentation, the system methods setting of a Fast-R-CNN object detection framework and parameter optimization settings are implemented to realize the classification of 16,384 &times, 4096 large image little objects. The experiment proves that the method can be applied in practical production and can also be extended to other fields of large image micro-fine defects with a high light surface. In addition, this paper proposes a method to increase the proportion of positive samples by multiple settings of IOU values and discusses the limitations of the system for defect detection.

It is necessary in factories to assess the severity of the surface defects of castings, as a slight surface defect will be taken as qualified when it brings no bad effect or it can be removed by the subsequent processing. In practical production, professional technicians visually inspect the surface defect severity according to their individual experience. Therefore, it is difficult for them to maintain the same standard and accuracy in the subjective, tedious and labor-intensive work. Recently, image processing techniques based on optical images have been applied to achieve better accuracy and high efficiency. Unfortunately, optical images cannot directly quantify surface depth, which works as a crucial factor in the practical assessment of surface defect severity. The surface roughness evaluation algorithm, which takes into account of both area and depth information of the assessed surface, was applied to directly characterize surface defect severity based on surface asperity rather than optical image. The results using standard casting pieces show that surface defect severity has no apparent dependence on surface roughness. However, the subsequent results show that the root-mean-squared-deviation (RMSD) of surface gradient of flow line defects positively correlates with the increase of defect severity. The other types of defect do not present such tendency. Thus, practical workpieces with flow line defects on the surface were used to verify the universality of this tendency. The results show that surface roughness of an unqualified workpiece is larger than that of a qualified workpiece after surface slope adjustment, but presents no obvious coincidence before the adjustment. In contrast, the RMSD of an unqualified workpiece, no matter before or after the adjustment, is larger than that of a qualified one.

Time-resolved photoluminescence investigation on SiO 2 nanoparticles was carried out in controlled atmosphere, with the aim to discern the effects induced on the typical blue luminescence band by high power UV Nd:YAG laser photons (4.66 eV) and by some selected molecular species of the air (O 2 , N 2 , CO 2 , H 2 O). These factors ultimately determine both the brightness and photostability of the emitting defect, so as to limit the unique and attracting potentialities offered by this system in many applicative fields. Here it is highlighted that the effects due to photons and molecules, singularly considered, are not additive, the radiation being more dramatic in reducing the emission efficiency. Moreover, by analyzing the kinetics to convert the defects in a non-luminescent configuration both by the direct (photon-defect) and indirect (photon-molecule-defect) interactions, the threshold bleaching fluence is derived, ranging between 5000 J/cm 2 (in a vacuum) and 60 J/cm 2 (in air). These results indicate that an outstanding enhancement of the defect photostability is gained by passing from ambient atmosphere to vacuum condition, leading to foresee an immediate and relevant improvement in the field of the single-emitter spectroscopy based on the visible emission of SiO 2 nanoparticles.

Many metal components in automotive industry are surface-protected using the electrophoretic cathode metal coating (KTL). As surface defects can occur in this process, the components need to be 100% inspected, especially if the manufacturers are committed to delivering zero-defect products. Due to complicated 3D curved shapes and black shiny colour of the coating, inspection is typically carried out manually. To avoid labour-intensive manual inspection in serial production, an automated visual inspection system is developed. The paper presents the implementation of a control device for mass inspection of the products, typical KLT coating defects, and the visual inspection method for the detection of coating defects. A difference image acquisition method is implemented in order to reveal the defects on the black shiny colored parts. An image processing algorithm for the recognition of light patterns and a clustering approach for the recognition of defects are presented.

Highlights The TTC layer was efficiently deposited at the grain boundary of the perovskite, which passivated the grain surface and grain boundary, thereby decreasing the interfacial recombination of the perovskite solar cells.The hydrophobic small molecule TTC on the perovskite films forms a water-resistant layer that protects the perovskite from water damage. Electronic supplementary material The online version of this article (10.1007/s40820-019-0282-0) contains supplementary material, which is available to authorized users., The advancement of perovskite solar cells (PVSCs) technology toward commercialized promotion needs high efficiency and optimum stability. By introducing a small molecular material such as tetratetracontane (TTC, CH3(CH2)42CH3) at the fullerene (C60)/perovskite interface of planar p-i-n PVSCs, we significantly reduced the interfacial traps, thereby suppressing electron recombination and facilitating electron extraction. Consequently, an improved efficiency of 20.05% was achieved with a high fill factor of 79.4%, which is one of the best performances for small molecular-modified PVSCs. Moreover, the hydrophobic TTC successfully protects the perovskite film from water damage. As a result, we realized a better long-term stability that maintains 87% of the initial efficiency after continuous exposure for 200 h in air. Electronic supplementary material The online version of this article (10.1007/s40820-019-0282-0) contains supplementary material, which is available to authorized users.

A set of defining parameters for modeling stages of a surface defect propagation in the outer surface of a metal pipeline taking into consideration fatigue strength has been formed. For a section of a pipeline with a surface defect, it was proposed to use an algorithm of forecasting polarization potentials using means of neural networks. A procedure of functioning of the testing set was elaborated for estimating efficiency of neural networks. The procedure includes appropriate training methods. According to the results of analysis of interconnected deformation and corrosion processes, elements of a methodology of formation of information support for forecasting service life of a linear part of underground metal pipelines taking into consideration corrosion fatigue have been developed. Known results of estimation of service life of underground metal pipelines assumed linear nature of corrosion rate. Relevant information was presented in international and national standards. Recent experimental studies have shown that it is advisable to take into consideration nonlinear nature of corrosion rate in the outer surface of underground metal pipelines (BMP). A BMP section was inspected with the aid of a polarization potential meter together with a contactless current meter and principles of using neural networks for processing experimental results were formulated. An example of actual BMP was considered and analyzed for metal of a pipe of 17G1S grade steel with a corrosion defect in its outer surface. This analysis has resulted in estimation of metal service life and revealed nonlinearity characterized by magnitude of d=1.136. A control method and procedures for estimating polarization potentials with the help of neural networks were proposed. They make it possible to describe the process of corrosion defect propagation into the depth of the pipe wall physically sound and mathematically more correct in contrast to the standard procedures. The information presented is important for improving methods of control of underground metal pipelines operated by oil and gas enterprises, in particular, methods of correct measurement and evaluation of polarization potentials and anode currents in insulation defects taking into consideration nonlinearity of informative parameters

The effects of needle peening (NP) on the bending fatigue limit of a high tensile steel (HTS) HT780 (JIS-SHY685)-welded joint containing an artificial semicircular slit on the weld toe were investigated. Three-point bending fatigue tests were conducted at a stress ratio of R = 0.05 for NP-treated welded specimens with and without a slit. The fatigue limits of all specimens increased by 9&ndash, 200% due to the NP treatment. Furthermore, NP-treated specimens with slit depths of a = 1.0 mm exhibited high fatigue limits that were equal to those of NP-treated specimens without a slit. Therefore, a semicircular slit of less than a = 1.0 mm could be rendered harmless through NP treatment. This result indicates that the reliability of HTS-welded joints can be significantly improved via NP for surface defects with depths that are less than 1 mm, which are not detected through non-destructive inspection (NDI). Therefore, the problem regarding the reliability of HTS-welded joints that restricts the industrial utilization of HTS can be solved by performing both NDI and NP. The dominant factor that contributed to the improvement of the fatigue limit and increase in the acceptable defect size was the introduction of large and deep compressive residual stress with non-propagating cracks.

Surface defects decrease the fatigue limit of metals. In this study, the effects of surface defects on the fatigue limit of high-strength spring steel specimens were investigated. Several equations to predict the fatigue limit of specimens with surface defects were evaluated. Specimens with a semicircular slit with depths ranging from 30 to 400 µm were prepared. The Vickers hardness of the specimen was approximately 470 HV. Bending fatigue tests were performed at stress ratios ranging from −2 to 0.4. The fatigue test results showed that the fatigue limit decreased with an increase in the slit depth. Moreover, the maximum defect size that resulted in a decrease in the fatigue limit was dependent on the stress ratio. On comparing the predicted fatigue limits with the experimental results, it was confirmed that the predictions made based on the modified El-Haddad model were in good agreement with the experimentally obtained data. Thus, this model can be used to evaluate the fatigue limit of high-strength steels containing small surface defects with different stress ratios.

In this paper, an analytical model is proposed to predict magnetic flux leakage (MFL) signals from the surface defects in ferromagnetic tubes. The analytical expression consists of elliptic integrals of first kind based on the magnetic dipole model. The radial (Bz) component of leakage fields is computed from the cylindrical holes in ferromagnetic tubes. The effectiveness of the model has been studied by analyzing MFL signals as a function of the defect parameters and lift-off. The model predicted results are verified with experimental results and a good agreement is observed between the analytical and the experimental results. This analytical expression could be used for quick prediction of MFL signals and also input data for defect reconstructions in inverse MFL problem.

The gloss transition defect of injection-molded surfaces should be mitigated because it creates a poor impression of product quality. Conventional approaches for the suppression of the gloss transition defect employ a trial-and-error approach and additional equipment. The causes of the generation of a low-gloss polymer surface and the surface change during the molding process have not been systematically analyzed. This article proposes the causes of the generation of a low-gloss polymer surface and the occurrence of gloss transition according to the molding condition. The changes in the polymer surface and gloss were analyzed using gloss and topography measurements. The shrinkage of the polymer surface generates a rough topography and low glossiness. Replication to the smooth mold surface compensates for the effect of surface shrinkage and increases the surface gloss. The surface stiffness and melt pressure influence the degree of mold surface replication. The flow front speed and mold temperature are the main factors influencing the surface gloss because they affect the development rate of the melt pressure and the recovery rate of the surface stiffness. Therefore, the mold design and process condition should be optimized to enhance the uniformity of the flow front speed and mold temperature.

Silicon nanowires (SiNWs) with excellent light trapping properties have been widely applied in photovoltaic devices, which provide opportunities for boosting the photons harvested by Si. However, the photoexcited carriers are easily trapped and recombined by high-density surface defects due to higher surface area prolonging to depth of nanowire. In this work, in order to reduce the surface defects and recombination rate of SiNWs, a simple solution process is used to modify the surface structure. Applying the tetramethyl ammonium hydroxide (TMAH) treatment leads to smooth and taper Si NW surface, which improves the open-circuit voltage (V oc) and fill factor (FF) obviously. Thus, a champion PCE of 14.08% is achieved for the nanostructured Si/PEDOT:PSS hybrid device by 60-s TMAH treatment. It also indicates that TMAH treatment promises a simple and effective method for enhancing Si NW-based devices.

Construction of ordered electron acceptors is a feasible way to solve the issue of phase separation in polymer solar cells by using vertically-aligned ZnO nanorod arrays (NRAs). However, the inert charge transfer between conducting polymer and ZnO limits the performance enhancement of this type of hybrid solar cells. In this work, a fullerene derivative named C60 pyrrolidine tris-acid is used to modify the interface of ZnO/poly(3-hexylthiophene) (P3HT). Results indicate that the C60 modification passivates the surface defects of ZnO and improves its intrinsic fluorescence. The quenching efficiency of P3HT photoluminescence is enhanced upon C60 functionalization, suggesting a more efficient charge transfer occurs across the modified P3HT/ZnO interface. Furthermore, the fullerene modified hybrid solar cell based on P3HT/ZnO NRAs displays substantially-enhanced performance as compared to the unmodified one and the devices with other modifiers, which is contributed to retarded recombination and enhanced exciton separation as evidenced by electrochemical impedance spectra. Therefore, fullerene passivation is a promising method to ameliorate the connection between conjugated polymers and metal oxides, and is applicable in diverse areas, such as solar cells, transistors, and light-emitting dioxides.

The effects of partial surface shot peening on the fatigue crack growth behaviour of a ferritic steel have been experimentally investigated in this paper. Dog-bone specimens fabricated from Optim700QL were tested under tension-tension fatigue loads. Three distinct extents of partial shot peening, with respect to the crack tip and specimen symmetry line, were tested. The fatigue crack growth results from these experiments have been compared with those obtained from the same specimen geometry but with no peening. The results show that the residual stress fields formed ahead of the initial notch tip due to the partial peening process play a significant role in the fatigue crack growth behaviour of the material and effectively result in accelerated crack propagation at the midwidth of the specimens. It has been shown in this study that partial peening can lead to a fatigue crack growth rate around twice as fast as that of the unpeened specimen.

Nowadays, surface defect detection systems for steel strip have replaced traditional artificial inspection systems, and automatic defect detection systems offer good performance when the sample set is large and the model is stable. However, the trained model does work well when a new production line is initiated with different equipment, processes, or detection devices. These variables make just tiny changes to the real-world model but have a significant impact on the classification result. To overcome these problems, we propose an evolutionary classifier with a Bayes kernel (BYEC) that can be adjusted with a small sample set to better adapt the model for a new production line. First, abundant features were introduced to cover detailed information about the defects. Second, we constructed a series of support vector machines (SVMs) with a random subspace of the features. Then, a Bayes classifier was trained as an evolutionary kernel fused with the results from the sub-SVM to form an integrated classifier. Finally, we proposed a method to adjust the Bayes evolutionary kernel with a small sample set. We compared the performance of this method to various algorithms; experimental results demonstrate that the proposed method can be adjusted with a small sample set to fit the changed model. Experimental evaluations were conducted to demonstrate the robustness, low requirement for samples, and adaptiveness of the proposed method.

Part 5: Industrial Management and Other Applications; International audience; The accuracy of detecting the orange skin surface defect in lacquered furniture elements was tested. Textural features and an SVM classifier were used. Features were selected from a set of 50 features with the bottom-up feature selection strategy driven by the Fisher measure. The features selected were the Kolmogorow-Smirnow-based features, some of the Hilbert curve-based features, some of the maximum subregions features and also some of the thresholding-based features. The Otsu thresholding and percolation-based features were all rejected. The images of size $$300\,\times \,300$$300×300 pixels cut from the original, larger images were treated as objects. There were three quality classes: very good, good and bad. In the cross-validation process where the testing sets consisted of 90 and the training sets of 910 objects the accuracies ranged from 90% to 98% and the average accuracy was 94%. The tests revealed that more research should be done on the choice of features for this problem.

Environmental pollution from human and industrial activities has received much attention as it adversely affects human health and bio-diversity. In this work we report efficient visible light photocatalytic degradation of phenol using supported zinc oxide (ZnO) nanorods and explore the role of surface defects in ZnO on the visible light photocatalytic activity. ZnO nanorods were synthesized on glass substrates using a microwave-assisted hydrothermal process, while the surface defect states were controlled by annealing the nanorods at various temperatures and were characterized by photoluminescence and X-ray photoelectron spectroscopy. High performance liquid chromatography (HPLC) was used for the evaluation of phenol photocatalytic degradation. ZnO nanorods with high surface defects exhibited maximum visible light photocatalytic activity, showing 50% degradation of 10 ppm phenol aqueous solution within 2.5 h, with a degradation rate almost four times higher than that of nanorods with lower surface defects. The mineralization process of phenol during degradation was also investigated, and it showed the evolution of different photocatalytic byproducts, such as benzoquinone, catechol, resorcinol and carboxylic acids, at different stages. The results from this study suggest that the presence of surface defects in ZnO nanorods is crucial for its efficient visible light photocatalytic activity, which is otherwise only active in the ultraviolet region.

As an important part of the electric locomotive in railway transportation, the sensing and inspection of the pantograph has a significant effect on the safe operation of the train. In general, the pantograph carbon slip detection items include slide wear detection, slip strip crack detection, carbon slip fall-block detection and slip strip wear detection. The emergence and development of structured light measurement technology with 3D sensors provide new technical means for the acquisition of spatial 3D information. The three-dimensional data can not only obtain more information but also reduce the data deviation, thereby improving the measurement accuracy and work efficiency. At present, few studies have been conducted on the slide block and partial wear of the carbon slide. Therefore, this paper studies the detection of the pantograph slide block based on 3D sensor measurement technology. The experimental results indicate that it is feasible to adopt 3D measurement technology to detect the fall-block of the pantograph slide. In addition, a sound detection effect can also be obtained.

Microscopic properties of nanocrystal aluminum thin film have been investigated using the quasicontinuum method in order to study the influence of surface defects in nanoindentation. Various distances between the surface defect and indenter have been taken into account. The results show that as the distance between the pit and indenter increases, the nanohardness increases in a wave pattern associated with a cycle of three atoms, which is closely related to the crystal structure of periodic atoms arrangement on {1 1 1} atomic close-packed planes of face-centered cubic metal, when the adjacent distance between the pit and indenter is more than 16 atomic spacing, there is almost no effect on nanohardness. In addition, the theoretical formula for the necessary load for elastic-to-plastic transition of Al film has been modified with the initial surface defect size, which may contribute to the investigation of material property with surface defects.

The aim of this study was to clarify the effects of micro surface defects introduced by the focused ion beam (FIB) technique on the fracture strength of ceramics. Three-point bending tests on alumina-silicon carbide (Al2O3/SiC) ceramic composites containing crack-like surface defects introduced by FIB were carried out. A surface defect with a r e a in the range 19 to 35 µm was introduced at the center of each specimen. Test results showed that the fracture strengths of the FIB-defect specimens depended on a r e a . The test results were evaluated using the evaluation equation of fracture strength based on the process zone size failure criterion and the a r e a parameter model. The experimental results indicate that FIB-induced defects can be used as small initial cracks for the fracture strength evaluation of ceramics. Moreover, the proposed equation was useful for the fracture strength evaluation of ceramics containing micro surface defects introduced by FIB.

International audience; This article introduces an innovative method for the multi-scale analysis of high value-added surfaces, which consists of applying a method based on a new parameterization. This kind of surface parameterization refers to natural modes of vibration, and is therefore named modal para-meterization. It allows us to characterize the form, waviness and roughness defects of a surface. This parameterization opens up new fields of analysis, such as the appearance quality of surfaces. It is thereby possible to decompose a measured surface in a vector basis, of which vectors are represented by plane natural eigenmodes sorted by frequency and complexity. Different filtering operations can then be produced, such as extracting the primary form of the surface. To analyze the perceived quality of surfaces, these investigations focus on two approaches: that appearance defects have small periodicity, and that there is a link between curvatures and the visual impact of an anomaly. This methodology is applied to two prestige lighters, whose surfaces were measured by extended field confocal microscopy. Moreover, a prospect of this work is to develop an augmented-reality-type monitoring tool for sensory experts.

In this paper, an orthogonal cutting simulation on machining 45% SiC/Al composites is presented for develop an in-depth understanding of surface defects in micro milling of the SiCp/Al composites and the associated machining parameters. PCD micro end mill is used with the value of the cutting edge radius close to the SiC particle size. The material removal mechanism and the surface defect formation at three typical cases are analysed. The results indicate the main machined surface defect is affected by the tool-particle interaction location. The half interaction location might lead to the best surface quality, which is proved by cutting trials and experimental observation. Partial funding support from the State Key Lab of Digital Manufacturing Equipment & Technology (Project No.: DMETKF2015004)

This paper proposes a framework to automatic extract structural elements of reinforced concrete buildings from laser scanning data, which can be used in dimensional quality control and surface defect identification. The framework deploys both spatial information of a point cloud and contextual knowledge of building structures to extract the structural elements in a sequential order: floors and ceilings, walls, columns and beams. The method starts to extract a subset data containing candidate points of the structural elements and segmentation methods and filtered based contextual knowledge subsequently apply to obtain the final points of the elements. In this framework, a combination between kernel density estimation and a cell-patch-based region growing are to extract the floors, ceilings and walls, while the points of the columns and beams are achieved through a voxel-based region growing. 23.5 million data points of one story of the building is used to test a performance of the proposed framework. Results showed all structural components are successfully extracted. Moreover, completeness, correctness, and quality indicated through point-based performance report larger than 96.0%, 96.9% and 93.0%, respectively while overlap rates of the floors, ceilings and walls are no less than 95.3%. Interestingly, an executing time of the proposed method is about 7.7seconds per a million point.

Lead halide perovskite nanocrystals (NCs) are emerging as optically active materials for solution-processed optoelectronic devices. Despite the technological relevance of tracing rational guidelines for optimizing their performances and stability beyond their intrinsic resilience to structural imperfections, no in-depth study of the role of selective carrier trapping and environmental conditions on their exciton dynamics has been reported to date. Here we conduct spectro-electrochemical (SEC) experiments, side-by-side to oxygen sensing measurements on CsPbBr3 NCs for the first time. We show that the application of EC potentials controls the emission intensity by altering the occupancy of defect states without degrading the NCs. Reductive potentials lead to strong (60%) emission quenching by trapping of photogenerated holes, whereas the concomitant suppression of electron trapping is nearly inconsequential to the emission efficiency. Consistently, oxidizing conditions result in minor (5%) brightening due to suppressed hole trapping, confirming that electron traps play a minor role in nonradiative decay. This behavior is rationalized through a model that links the occupancy of trap sites with the position of the NC Fermi level controlled by the EC potential. Photoluminescence measurements in controlled atmosphere reveal strong quenching by collisional interactions with O2, which is in contrast to the photobrightening effect observed in films and single crystals. This indicates that O2 acts as a scavenger of photoexcited electrons without mediation by structural defects and, together with the asymmetrical SEC response, suggests that electron-rich defects are likely less abundant in nanostructured perovskites than in the bulk, leading to an emission response dominated by direct interaction with the environment.