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InGaN micro-LEDs (μ LEDs) with their potential high-volume applications have attracted substantial research interest in the past years. In comparison to other III–V semiconductors, InGaN exhibits a reduced susceptibility toward non-radiative surface recombination. However, efficiency degradation becomes more prominent as dimensions shrink to a few μ m or less. Due to the high surface-to-volume ratio of the miniaturized devices, the non-radiative recombination increases and reduces the internal quantum efficiency. While many groups focus on surface passivation to mitigate surface defects, the influence of crystallographic orientation of the μ LED sidewall on the efficiency remains unexplored. This study addresses this gap by investigating the impact of crystallographic orientation of the sidewalls on the emission properties of the μ LEDs. Hexagonal and elongated μ LEDs with dimensions as small as 3.5 μ m and sidewalls with crystallographically well-defined m- and a-planes were fabricated. Electrical and optical properties were investigated using photo- and electroluminescence. External quantum efficiency (EQE) is assessed based on well-known carrier recombination models. It can be shown that μ LED performance intrinsically depends on the crystallographic orientation of the sidewalls. Comparing hexagonal μ LED structures with a-plane and m-plane sidewalls, an increase in the EQE by 33 % was observed for structures with a-plane sidewalls, accompanied by reduction in the current density of the peak EQE by a nearly two orders of magnitude compared to structures with m-plane sidewalls. By analyzing the EQE characteristics at the μ LED center and near the sidewalls, the improvements can be directly attributed to the increased radiative recombination from sidewalls with a-plane orientation. [ABSTRACT FROM AUTHOR]

Chiral quantum dots (QDs) are promising materials applied in many areas, such as chiral molecular recognition and spin selective filter for charge transport, and can be prepared by facile ligand exchange approaches. However, ligand exchange leads to an increase in surface defects and reduces the efficiencies of radiative recombination and charge transport, which restricts further applications. Here, we investigate the light-induced photoluminescence (PL) enhancement in chiral L- and D-cysteine CdSe QD thin films, providing a strategy to increase the PL. The PL intensity of chiral CdSe QD films can be significantly enhanced over 100 times by continuous UV laser irradiation, indicating a strong passivation of surface defects upon laser irradiation. From the comparative measurements of the PL intensity evolutions in vacuum, dry oxygen, air, and humid nitrogen atmospheres, we conclude that the mechanism of PL enhancement is photo-induced surface passivation with the assistance of water molecules. [ABSTRACT FROM AUTHOR]

This paper describes a three-step process to remediate surface and sub-surface defects on chemo-mechanically polished SiC surfaces. In this process, a CF4-based inductively coupled plasma with reactive ion etch was used to remove material to a depth, which is unaffected by surface and subsurface polishing damage. This produced a planarized but carbon-rich fluorinated surface. This surface was then exposed to a 2 min rapid thermal oxidation in air at 1000 °C to oxidize and volatilize the excess carbon and fluorinated species, respectively. The resulting surface oxide was then stripped using a dilute hydrofluoric acid in water solution. This process, referred to as plasma assisted remediation, reproducibly yielded planarized, stoichiometric surfaces with low levels of carbon and oxygen contamination suitable for subsequent device fabrication. In the supporting studies described here, 4H- and 6H-SiC(0001) surfaces were remediated and characterized by x-ray photoelectron spectroscopy and atomic force microscopy at each stage of the process. Experimental studies under ion-rich and radical-dominant conditions are also reported which provide greater insight into the underlying chemistry and physics of the process. [ABSTRACT FROM AUTHOR]

In many modern applications, it is important to understand mechanisms of non-equilibrium chemistry and physics that are driven by low energy ion bombardment of solid surfaces. However, the study of these processes has been challenging as it demands a relatively unique balance between chemical fidelity and computational cost. To this end, we have proposed and constructed a new, high-throughput simulation pipeline based on density functional tight binding simulations. Additionally, we have extended the parameter set pbc-0-3 with the addition of Ar, thereby enabling the simulation of Ar bombardment. This pipeline was then applied to study the structural and compositional evolution of silicon nitride (SiN) under Ar bombardment. We identified a possible rate limiting step of bombardment-driven sputtering of SiN and suggested underlying mechanisms of Si and N removal. Damage from the bombardment, including generation of surface defects and Ar implantation, are further discussed. These findings and the newly developed simulation framework will serve as a useful foundation for further research in processes driven by ion bombardment. [ABSTRACT FROM AUTHOR]

MoS2 has generated significant attention due to its unique electronic properties and versatile applications. Being a van der Waals material, MoS2 is expected to exhibit an inert surface due to lack of dangling bond. However, our photoemission study finds MoS2 to be highly sensitive toward residual gases. The position of the valence band maximum (VBM) shifts even in a vacuum of 10−10 Torr. We find this to be due to CO adsorption causing unintentional electron doping. The time evolution of the position of VBM is exponential, and it reaches two different saturation points, depending on whether the sample is exposed to ultraviolet (UV) radiation or not. Our XPS (x-ray photoemission spectroscopy) study shows no time-dependent escape of sulfur, which was in a previous study attributed to a VBM shift. The VBM shift can be reversed by annealing, sputtering, and UV light, which desorb CO gases. The study shows that the MoS2 surface is easily doped, which offers the possibility of using it as a sensor but in many other applications could diminish device performance and needs to be considered. [ABSTRACT FROM AUTHOR]

MoS2 has generated significant attention due to its unique electronic properties and versatile applications. Being a van der Waals material, MoS2 is expected to exhibit an inert surface due to lack of dangling bond. However, our photoemission study finds MoS2 to be highly sensitive toward residual gases. The position of the valence band maximum (VBM) shifts even in a vacuum of 10−10 Torr. We find this to be due to CO adsorption causing unintentional electron doping. The time evolution of the position of VBM is exponential, and it reaches two different saturation points, depending on whether the sample is exposed to ultraviolet (UV) radiation or not. Our XPS (x-ray photoemission spectroscopy) study shows no time-dependent escape of sulfur, which was in a previous study attributed to a VBM shift. The VBM shift can be reversed by annealing, sputtering, and UV light, which desorb CO gases. The study shows that the MoS2 surface is easily doped, which offers the possibility of using it as a sensor but in many other applications could diminish device performance and needs to be considered. [ABSTRACT FROM AUTHOR]

In this work, we studied the impact of environmental constituents such as oxygen (O2) and moisture on halide double perovskite (HDP) films. The transport measurements indicate that an increment in O2 concentration enhances the resistivity of a Cs2AgBiBr6 film by two orders of magnitude. The adsorption of O2 on the film's surface helps in passivation of defects (∼50% reduction in defect density on O2 exposure), which inhibits ion migration and results in an increased resistivity of the film. The process of adsorption and desorption of O2 on the film surface is found to be fully reversible. In contrast, the resistivity of double perovskite films decreases by an order of magnitude in the presence of moisture. This is attributed to the generation of free protons as a result of the dissociation of water molecules at the films' surface, hence exhibiting an increase in current under external bias. The HDP films possess high resistivity (for T < 100 °C) due to the desorption of physisorbed water layers from the surface, which gradually decreases with an increase in the operating temperature. This work demonstrates that O2 and moisture are a good combination for defect passivation in any HDPs, in general. [ABSTRACT FROM AUTHOR]

In this work, expanding cylinder experiments are performed using a gas gun on the aluminum 6061 alloy to understand the dynamic deformation and failure behavior of this material in the presence of surface defects in the form of scratches. The experiments are then modeled with the modified Tepla (for tensile plasticity) model, which is equipped with the damage yield function of Gurson ["Continuum theory of ductile rupture by void nucleation and growth: Part I—Yield criteria and flow rules for porous ductile media," (1977)] and Tvergaard and Needleman [Acta Metall. 32(1), 157–169 (1984)], over-stress viscosity [F. Addessio and J. Johnson, J. Appl. Phys. 74(3), 1640–1648 (1993)], and the underlying viscoplastic model of Preston et al. [J. Appl. Phys. 93(1), 211–220 (2003)] (Preston–Tonks–Wallace model) for the dense material. The Tepla model parameters were calibrated using the Bayesian approach against experimentally measured free-surface velocity data obtained from plate impact experiments on the aluminum 6061 alloy. The evolution of radial expansion and shapes of the deformed cylinder from the simulations on a pristine cylinder wall and a cylinder wall with a longitudinal surface defect shows excellent agreement with the corresponding experimental results. Finally, the role of surface defect size and cylinder wall geometry on the dynamic strength of the cylinder wall was also investigated through a series of simulations. [ABSTRACT FROM AUTHOR]

Nitrogen (N) doping engineering is considered a promising approach to achieve p-type conductivity of Ga2O3 films. However, the defect self-compensation effect has been a major obstacle in this field. In this work, we propose a straightforward and environmentally friendly strategy to obtain a doped surface on β-Ga2O3 films via nonthermal N plasma-based treatment. By substituting nitrogen with oxygen, acceptor impurity levels are formed near the valence band, and self-trapped exciton recombination occurs, thereby enhancing the luminescence effect related to acceptor defects. Meanwhile, although achieving stable p-type conduction with N dopant acceptors remains challenging, the surface conductive properties are enhanced by the defect compensation of oxygen vacancy (VO) donor defects. Therefore, detailed investigations into the surface defect compensation of N-doped Ga2O3 thin films are of great research potential for device applications. [ABSTRACT FROM AUTHOR]

Surface defect detection by machine vision has received increased attention concerning the quality control of universal joint bearings (UJB). The defect distribution and counting information are important for product quality optimisation. However, vision defect detection for UJB remains a challenging task due to the diversity of background textures and defect characters on multiple surfaces. In this study, a multi-surface defect detection (MSDD) method consisting of region segmentation, feature extraction and detection is proposed. First, defect regions are accurately localised by the proposed adaptive defect region segmentation algorithm, which suppresses the inference of background variety. Then, a novel defect feature named multimodal fusion shape descriptor that integrates the global information and local information of defects is constructed to generate the discriminative defect representation. Finally, a defect feature extraction ability transfer strategy based on the transfer learning mechanism is proposed to address the problem of insufficient defect samples. The experimental results show that our method achieves the best accuracy of 94.8% macro-F1 and processes 28 defect images per second. Besides, the application effect in the practical production line indicates that our method meets the accuracy and real-time requirements of MSDD for UJB. [ABSTRACT FROM AUTHOR]

High thermal conductivity graphite films (GFs) have a thermal conductivity, which have attracted much attention in recent years. As the surface of GFs is extremely smooth, the resin matrix and GFs are only connected by van der Waals forces, and it is difficult to produce chemical bonds between them, resulting in poor mechanical properties of the composites. In this study, the composites were prepared by etching defects on the surface of GFs by high‐temperature heat treatment. It was determined that the critical temperature range for effective etching was between 600 and 650°C. The GFs were subjected to high‐temperature heat treatment to create circular, hexagonal, and disordered groove‐like defects, and then combined with prepregs and bismaleimide resins in a single molding process. The composites exhibit a distinct layered "sandwich" structure, where surface‐induced defects enhance the interfacial adhesion between GFs and the resin matrix, creating a "nail‐punched" structure. The thermal conductivity of the S‐650 sample in the X‐direction was up to 1187.93 W/(m·K), and the flexural strength of the S‐800 sample was up to 116.18 MPa. The prepared composites are expected to be widely used in thermal interface fields such as heat exchangers, battery heat dissipation and aerospace thermal control systems. Highlights: High‐temperature treatment was used to successfully introduce defects into GFs.The formation mechanisms of the three types of defects were explained.The thermal conductivity of the composites was increased to over 1000 W/(m·K).Composites reinforced with modified GFs exhibit enhanced mechanical properties. [ABSTRACT FROM AUTHOR]

In this work, we report a simple yet robust strategy for eliminating surface defects in red-emitting fluorides through solid–liquid interface friction under elevated temperature and high pressure. This method is minimally dependent on the solvent type and especially excels at stripping away the abundant surface defects caused by mechanical crushing. [ABSTRACT FROM AUTHOR]

Inverted NiOx‐based perovskite solar cells (PSCs) exhibit considerable potential because of their low‐temperature processing and outstanding excellent stability, while is challenged by the carriers transfer at buried interface owing to the inherent low carrier mobility and abundant surface defects that directly deteriorates the overall device fill factor. Present work demonstrates a chemical linker with the capability of simultaneously grasping NiOx and perovskite crystals by forming a Ni−S−Pb bridge at buried interface to significantly boost the carriers transfer, based on a rationally selected molecule of 1,3‐dimethyl‐benzoimidazol‐2‐thione (NCS). The constructed buried interface not only reduces the pinholes and needle‐like residual PbI2 at the buried interface, but also deepens the work function and valence band maximum positions of NiOx, resulting in a smaller VBM offset between NiOx and perovskite film. Consequently, the modulated PSCs achieved a high fill factor up to 86.24 %, which is as far as we know the highest value in records of NiOx‐based inverted PSCs. The NCS custom‐tailored PSCs and minimodules (active area of 18 cm2) exhibited a champion efficiency of 25.05 % and 21.16 %, respectively. The unencapsulated devices remains over 90 % of their initial efficiency at maximum power point under continuous illumination for 1700 hours. [ABSTRACT FROM AUTHOR]

ABSTRACT The high tensile strength and high resistance of nickel‐based superalloy 686 against high temperatures and corrosion rates have made it a widely used in important applications such as the aerospace industry, high pollution‐ and corrosion‐resistance equipment manufacturing and petrochemical industry. Therefore, the machining of this advanced alloy with its unique properties is extremely important and can be challenging. Significant increase in input parameters levels, reduction of machining costs, improvement of surface and subsurface properties and clean production are among the issues that should be considered in dealing with Inconel 686 turning operations. Simultaneous application of advanced tools such as polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) and optimised minimum quantity lubrication (MQL) method and evaluating the results obtained with a wide range of output parameters related to machining process performance and tribological properties can be proposed as an innovation and a solution to this problem in this article. This study analyses several output parameters with different speeds and feeds to evaluate the effect of cutting insert type on machining process performance and tribological properties. The output parameters include tool wear, residual stress, cutting zone temperature, surface smoothness, machining forces and workpiece surface defects. The results indicated that using the optimised MQL method reduces the size of lubricant droplets and increases the surface covered by cooling. With these changes, the performance of the machining process and the parameters related to the surface integrity increase significantly. Among the parameters associated with the performance of the machining process, the PCD tool reduces the cutting zone temperature by 23%, the tool wear by 19% and the machining forces by 18% compared to the PCBN tool. In the parameters related to surface integrity, this method reduces the residual stress by 19% and the surface roughness by 9% compared to the PCBN tool. From the production index perspective, the PCD tool can significantly increase the cutting speed and feed rate, reducing production time and costs. [ABSTRACT FROM AUTHOR]

In this study, we propose a random cropping augmentation (RCA) based on an optimized YOLOv8 algorithm by introducing a tiny object detection layer to improve the accuracy of surface defect detection on the inner wall of micro-holes of cylindrical high-precision parts. The inner surfaces of cylindrical high-precision parts possess attributes like high smoothness, elongated channels, limited visibility, minute flaws, and challenges capturing image data. These characters impose significant difficulties in automating defect detection for this part type. Taking the automobile fuel injector valve seat as an example, industrial CCD cameras and lenses are combined with a circular light source to acquire magnified image data. The images are preprocessed using tile and adaptive histogram equalization algorithms. Then, the RCA algorithm expands and randomly combines the image data. We compare the proposed algorithm with the original faster RCNN, YOLOv5 and YOLOv8 algorithm for surface defect detection on the inner wall of the automotive fuel injector valve seat. The experimental results demonstrate that after extending the dataset with the RCA algorithm, there have been significant improvements in the mean average precision (mAP) for the faster RCNN, YOLOv5, and YOLOv8 algorithms. The mAP@0.5 for these algorithms has increased from 37.1%, 48.7%, and 62.2% to 60.9%, 72.6%, and 81.1%, respectively. Furthermore, the improved YOLOv8 algorithm, which incorporates tiny object detection module, achieved an mAP@0.5 of 87% on the dataset extended by the RCA algorithm, with precision and recall reaching 89.7% and 80.6%, respectively. The improved YOLOv8 + RCA algorithm performs better than mainstream algorithms in surface defect detection on the inner wall of the fuel injector valve seat while meeting the requirements of industrial production quality inspection for detection speed. [ABSTRACT FROM AUTHOR]

To address the issue of low detection accuracy of steel surface defects due to complex texture background interference and complex defect morphology, this paper proposes an improved YOLOv8 model based on MobileViTv2 and Cross-Local Connection for steel surface defect detection. Firstly, the lightweight MobileViTv2 network is introduced into the backbone network, which enhances the feature extraction capability of the model in complex defect shapes by combining the advantages of CNN and Transformer. Then, the designed CLC method is introduced into the neck network, which connects deep and shallow features through additional convolutional layers, further integrating defect features in the presence of complex texture background interference. Finally, the NET-DET dataset is augmented to improve the model's robustness. Experimental results show that the mAP of the improved model is 74.1%, with a detection speed of 86.2 FPS and model memory usage of 27.5 MB. Compared to YOLOv5 and YOLOv8, the mAP of the improved model is increased by 6.5% and 4%, respectively. Compared to existing object detection models, the improved model has the characteristics of high detection accuracy and fast detection speed, meeting the requirements of industrial production for steel surface defect detection. [ABSTRACT FROM AUTHOR]

Selective catalytic NH 3 -to-N 2 oxidation (NH 3 -SCO) is highly promising for abating NH 3 emissions slipped from stationary flue gas after-treatment devices. Its practical application, however, is limited by the non-availability of low-cost catalysts with high activity and N 2 selectivity. Here, using defect-rich nitrogen-doped carbon nanotubes (NCNT-AW) as the support, we developed a highly active and durable copper-based NH 3 -SCO catalyst with a high abundance of cuprous (Cu+) sites. The obtained Cu/NCNT-AW catalyst demonstrated outstanding activity with a T 50 (i.e. the temperature to reach 50% NH 3 conversion) of 174°C in the NH 3 -SCO reaction, which outperformed not only the Cu catalyst supported on N-free O-functionalized CNTs (OCNTs) or NCNT with less surface defects, but also those most active Cu catalysts in open literature. Reaction kinetics measurements and temperature-programmed surface reactions using NH 3 as a probe molecule revealed that the NH 3 -SCO reaction on Cu/NCNT-AW follows an internal selective catalytic reaction (i -SCR) route involving nitric oxide (NO) as a key intermediate. According to mechanistic investigations by X-ray photoelectron spectroscopy, Raman spectroscopy, and X-ray absorption spectroscopy, the superior NH 3 -SCO performance of Cu/NCNT-AW originated from a synergy of surface defects and N-dopants. Specifically, surface defects promoted the anchoring of CuO nanoparticles on N-containing sites and, thereby, enabled efficient electron transfer from N to CuO, increasing significantly the fraction of SCR-active Cu+ sites in the catalyst. This study puts forward a new idea for manipulating and utilizing the interplay of defects and N-dopants on carbon surfaces to fabricate Cu+-rich Cu catalysts for efficient abatement of slip NH 3 emissions via selective oxidation. [ABSTRACT FROM AUTHOR]

The detection of steel surface defects is of great significance to steel production. In order to better meet the requirements of accuracy, real-time, and lightweight model, this paper proposes a highly efficient and lightweight steel surface defect detection method based on YOLOv5n. Firstly, ODMobileNetV2 composed of MobileNetV2 and ODConv is used as the backbone to improve the defect feature extraction capability. Secondly, GSConv is utilized in the neck to achieve deep information fusion through channel concatenation and shuffling, enhancing the ability of feature fusion. Finally, this paper proposes a spatial-channel reconstruction block (SCRB) designed to suppress redundant features and improve the representation ability of defect features through feature separation and reconstruction. Experimental results show that this method achieves 84.1% mAP and 109 FPS on the NEU-DET dataset, and 72.9% mAP and 110.1 FPS on the GC10-DET dataset, enabling accurate and efficient detection. Furthermore, the number of parameters is only 5.04M, which has a significant lightweight advantage. [ABSTRACT FROM AUTHOR]

Leaf springs, as vital suspension components in trucks, endure various forces such as torsion, compression, tension and impact, rendering them highly susceptible to fatigue and fracture risks, thereby posing a significant threat to vehicle safety. During the production process of leaf springs, surface decarburisation can easily occur, leading to the formation of numerous surface rolling defects. These defects exert varying influences on the initiation of fatigue crack. This study investigates the influence of various forms of rolling defects caused by decarburisation on fatigue crack initiation in 50CrMnMoNbAT leaf spring through experimental and numerical analysis of fatigue fracture behaviour. The results indicate that fracture locations in the leaf springs are predominantly concentrated approximately 297 mm and 698 mm from the ends. Furthermore, the occurrence of surface decarburisation during the rolling process engenders a significant number of surface rolling defects. Surface defects in leaf springs can be categorised into three forms: Parallel defect, Parcel defect and Occlusal defect. In terms of defect propagation rate, rolling defects on the concave surface are most prone to initiate fatigue cracks, with Occlusal defects exhibiting the highest likelihood of developing internal cracks and the fastest crack propagation rate. [ABSTRACT FROM AUTHOR]

Achieving an optimal balance between mechanical properties, dielectric properties, and thermal shock resistance presents a significant challenge in the development of advanced ceramics. This study investigates Si 3 N 4 -BN composite materials, prepared by hot-press sintering with magnesium aluminum silicate (MAS) as the sintering additive, to assess the impact of varying hexagonal boron nitride (h -BN) content on their mechanical and dielectric properties, as well as their thermal shock resistance. At an h -BN content of 20 wt%, the BN layers act as a toughening phase through a pull-out mechanism, minimally impacting the composite's density. This composition results in superior fracture toughness (7.4 MPa m1/2), high strength (598 MPa), low dielectric constants (∼6.8), and dielectric loss (∼7.4 × 10−3). Notably, after a thermal shock at 1000 °C, the composite exhibits a peak residual strength of 621 MPa, surpassing its initial strength. This enhanced performance is attributed to the formation of a dense Mg–Al–Si–B–O oxide glass layer on the surface during thermal shock, which not only repairs surface defects but also induces compressive stress. The development of the Si 3 N 4 -BN-MAS composite, with its outstanding comprehensive performance, marks a significant advancement for materials used in high-temperature wave transmission applications. [ABSTRACT FROM AUTHOR]

This research aims to detect and analyze critical internal and surface defects in metal components manufactured by powder bed fusion of metals using a laser beam (PBF‐LB/M). The aim is to assess their impact on the fatigue behavior. Therefore, a combination of methods, including image processing of micro‐computed tomography (μCT) scans, fatigue testing, and machine learning, was applied. A workflow was established to contribute to the nondestructive assessment of component quality and mechanical properties. Additionally, this study illustrates the application of machine learning to address a classification problem, specifically the categorization of pores into gas pores and lack of fusion pores. Although it was shown that internal defects exhibited a reduced impact on fatigue behavior compared with surface defects, it was noted that surface defects exert a higher influence on fatigue behavior. A machine learning algorithm was developed to predict the fatigue life using surface defect features as input parameters. Highlights: Established workflow for extracting surface and internal features.Developed pore classification ML algorithm with 92.4% accuracy.Effectively developed ML algorithm for predicting fatigue life. [ABSTRACT FROM AUTHOR]

Ball burnishing (BB) is a surface finishing process that involves moving the tool while pressing it against the workpiece under rolling contact. We investigated the effects of BB on the fatigue strength of an aluminum alloy with a semicircular slit simulating an initial surface defect. After performing BB under a typical condition, compressive residual stress was induced to a depth of 0.4 mm, with a reduction in surface roughness by 81%. Consequently, the fatigue strength increased by 22%. BB prevented the fatigue strength reduction caused by the 0.1 mm deep slit. The result indicated that BB could render the below 0.1 mm deep surface defect harmless in terms of fatigue strength. The maximum depth of surface defect that can be rendered harmless is 0.18 mm according to fracture mechanics, which is in agreement with the experimental results. Highlights: Ball burnishing (BB) can introduce large compressive residual stress along with smoothing.BB can render a 0.1 mm deep slit harmless in terms of fatigue strength.Defect size rendered harmless can be estimated based on fracture mechanics.Compressive residual stress is the main factor rendering the surface defect harmless. [ABSTRACT FROM AUTHOR]

Steel surface defect detection poses a significant challenge in the steel industry, aiming to enhance product quality and production efficiency. Traditional mechanical and optical detection methods exhibit relatively low efficiency and poor real-time performance in detecting acceptable defects on the surface of steel strips. This paper proposes a new model named Hyper-YOLO for steel surface defect detection in steel strips. Firstly, the CSP module in the conventional YOLO backbone network is replaced with the Ghost module. The Ghost module, a lightweight convolutional module, enhances model efficiency by reducing parameter count and computational load while maintaining satisfactory performance. Secondly, researchers replace the PAFPN module in YOLO V5 in the bottleneck section with the Hyper FPN module. Hyper FPN, an improved feature pyramid network module, leverages features at different scales for multi-level feature fusion, enhancing the model's capability to detect targets at various scales. Lastly, improvements are made in the loss functions for both training and prediction stages. The α-CIoU loss function is introduced during training to substitute the original CIoU loss function, and the α-DIoU loss function is utilized during prediction instead of the original DIoU loss function. These enhanced loss functions effectively measure the accuracy and position precision of target boxes, thereby improving the detection performance of the model. Through these enhancements, the Hyper YOLO model achieves an overall performance improvement of 4.58% over the baseline model. This indicates that Hyper YOLO performs outstanding surface defect detection in steel strips, providing innovative insights for the YOLO V5 model. These improvements not only elevate the accuracy and efficiency of the model but also hold significant guidance for similar research and applications. [ABSTRACT FROM AUTHOR]

As deep learning advances, neural network technologies are increasingly penetrating the field of steel surface defect detection. To tackle the challenges of low accuracy and inadequate quality, we introduce CMS-YOLOv8s, a defect detection algorithm engineered for superior precision and efficiency. Initially, integrate the CBAM to enhance the network's focus on relevant information, allowing it to leverage multi-dimensional data like spatial and channel dimensions fully. Next, introduce the SPPFCSPC module to fuse feature information from different scales, expanding the model's receptive field and enhancing its feature extraction abilities. Finally, incorporate a small object detection head to boost the model's capability in identifying tiny targets, strengthening its ability to detect targets across different scales. Experimental findings show that CMS-YOLOv8s attains a detection accuracy of 70.4%, registering a significant 3.3% enhancement compared to the original YOLOv8s. This advancement distinctly improves defect detection accuracy across all categories. [ABSTRACT FROM AUTHOR]

Background: The mandible of the rabbit is considered a reliable model to be used to study bone regeneration in defects. The aim of the present study was to evaluate the formation of new bone around implants installed in defects of either 5 or 10 mm in the mandible of rabbits. Materials and methods: In 12 rabbits, 3 mm deep circumferential defect, either 5 or 10 mm in diameter, were prepared bilaterally and an implant was placed in the center. A collagen membrane was placed to close the entrance. After 10 weeks, biopsies were taken, histological slides were prepared, and different regions of the defects were analyzed. Results: Similar amounts of new bone were found in both defects. However, most of the 5 mm defects were filled with new bone. New bone was observed closing the entrance of the defect and laid onto the implant surface. Only in a few cases the healing was incomplete. Despite a similar percentage of new bone found within the 10 mm defects, the healing was incomplete in most of the cases, presenting a low rate of bone formation onto the implant surface within the defect. Only one case presented the closure of the entrance. Conclusions: The dimensions of the defect strongly influenced the healing so that a circumferential marginal defect of 10 mm around an implant in the mandible body should be considered a critical-sized defect. The presence of the implant and of residues of teeth might have strongly influenced the healing. [ABSTRACT FROM AUTHOR]

Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types. [ABSTRACT FROM AUTHOR]

The rise of wire arc additive manufacturing (WAAM) is attributed to the various field applications of additive manufacturing (AM), especially in producing large metal structures. The wire arc additive manufacturing is a process that can produce near-net-shape structures with high deposition rates and relatively lower costs. Due to the nature of the WAAM process, which is based on layer-by-layer fabrication and repeated heating and cooling cycles, surface defects can occur on the deposited layer, such as pores, cracks, oxidation, and geometric deviation. In understanding the factors that can affect the stability and mechanism of the WAAM process, online monitoring systems has been studied by researchers. This paper aims to critically review the different monitoring techniques as well as distinct sensing methods that can be applied in the WAAM process to enhance the quality of the 3D object. In conducting this review paper, the systematic literature review (SLR) method is chosen to enhance a better understanding of the current research works of monitoring systems in the WAAM process. The high heat accumulation and cooling rate process are found to be the most crucial factors that could influence the geometrical accuracy, microstructure, and mechanical properties of the deposited layer. [ABSTRACT FROM AUTHOR]

The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage, impacting the aerodynamic performance of the blades. To address the challenge of detecting and quantifying surface defects on wind turbine blades, a blade surface defect detection and quantification method based on an improved Deeplabv3+ deep learning model is proposed. Firstly, an improved method for wind turbine blade surface defect detection, utilizing Mobilenetv2 as the backbone feature extraction network, is proposed based on an original Deeplabv3+ deep learning model to address the issue of limited robustness. Secondly, through integrating the concept of pre-trained weights from transfer learning and implementing a freeze training strategy, significant improvements have been made to enhance both the training speed and model training accuracy of this deep learning model. Finally, based on segmented blade surface defect images, a method for quantifying blade defects is proposed. This method combines image stitching algorithms to achieve overall quantification and risk assessment of the entire blade. Test results show that the improved Deeplabv3+ deep learning model reduces training time by approximately 43.03% compared to the original model, while achieving mAP and MIoU values of 96.87% and 96.93%, respectively. Moreover, it demonstrates robustness in detecting different surface defects on blades across different backgrounds. The application of a blade surface defect quantification method enables the precise quantification of different defects and facilitates the assessment of risk levels associated with defect measurements across the entire blade. This method enables non-contact, long-distance, high-precision detection and quantification of surface defects on the blades, providing a reference for assessing surface defects on wind turbine blades. Graphic Abstract [ABSTRACT FROM AUTHOR]

Bearing defect detection plays a crucial role in the intelligent production of chemical transmission equipment, where timely identification and handling of defective bearings are essential. However, in practical large-scale industrial production, product surface defects are often complex, diverse, and exhibit significant variations in appearance, posing severe challenges to the discriminative ability and detection efficiency of bearing defect detection algorithms. This paper proposes a real-time bearing surface defect detection algorithm, CAC-YOLOv8, which designs the Channel Attenuation Network (CAN) and Compound Pooling Pyramid Spatial Pyramid Pooling Fast (CPPSPPF) structure. Specifically, the model introduces the Channel Attenuation Network to achieve parallel feature extraction, deep feature processing, and feature fusion under different channel numbers, capturing critical features related to bearing defects and thereby improving the inference speed. Subsequently, based on the concept of overlapped receptive fields, a CPPSPPF structure is constructed, utilizing multiple iterations of max-pooling operations with smaller pooling kernel sizes to prevent information loss while expanding the receptive field, thereby strengthening the capturing ability of features at different scales. The experimental results indicate that the proposed CAC-YOLOv8 bearing surface defect detection algorithm, compared to the YOLOv8 model, achieved a 0.3% improvement in mAP@0.5, reduced model size by 14.4%, and enhanced model inference speed by 33.3%. This enables the CAC-YOLOv8 model to significantly improve the real-time performance of bearing defect detection while maintaining high-precision detection. The performance in practical industrial detection demonstrates that the proposed approach has achieved outstanding results in both speed and accuracy. [ABSTRACT FROM AUTHOR]

ABSTRACT The electrical properties of acid‐treated CNT were investigated in terms of functional group and microstructure. A mixture of HNO3 and H2SO4 was used to acid treatment of CNT, and acid‐treated CNTs were synthesized by the mixture for 0 to 5 h. In crystal structure analysis, as acid treatment time was increased, the intensity of graphite diffraction peak was decreased and shifted to lower angle. It indicates a decrease in the crystallinity of CNT surface and lattice contraction by loss of carbon atoms. The distribution of oxygen on CNT surface was observed by TEM analysis confirming that functional groups and structural defects were formed. ID/IG ratio and average distance between defects (LD) were calculated using Raman spectroscopy to analyze the structural characteristics of CNT, and the greatest decrease was identified from p‐CNT to 2h‐CNT, resulting in the formation of functional groups and the changes in structural defects on CNT surface by acid treatment in the initial stage. Bonding state on CNT surface was analyzed through XPS analysis, and functional groups such as CO and COH were confirmed in acid‐treated CNT. Sheet resistance was measured to analyze the electrical properties of CNT, and 3h‐CNT showed the lowest sheet resistance at 25.28 Ω. [ABSTRACT FROM AUTHOR]

The catalytic efficiency of CeO2 in soot oxidation was significantly affected by its grain morphology and calcination temperature. Nanocube-shaped and nanorod-shaped CeO2 catalysts were synthesized via a hydrothermal method with different calcination temperatures. Activity tests revealed that the nanorod-shaped CeO2 exhibited superior catalytic activity compared to the nanocube-shaped catalysts at equivalent calcination temperatures. Furthermore, an inverse relationship between the catalytic activity and the calcination temperature was observed in the nanorod-shaped CeO2 catalysts, with those calcined at 300 °C exhibiting the most effective low-temperature catalytic performance. Combined characterization techniques and density functional theory calculations showed that the improved catalytic performance can be attributed to the increased abundance of oxygen vacancies, enhanced lattice oxygen mobility and higher surface energy due to their unique surface defect structure and electronic structural feature, in addition to the reduction in grain size. [ABSTRACT FROM AUTHOR]

The nondestructive testing capability of steel surface defects has a significant impact on quality of industrial production. However, the single-stage detection network YOLOv5s model for steel surface defect detection is of insufficient feature extraction ability and susceptibility to noise interference in extracting surface defect images. Accordingly, a steel surface defect detection system based on YOLOv5s-SE-CA model and bi-dimensional empirical mode decomposition (BEMD) image enhancement is proposed. Firstly, the BEMD is used for image threshold denoising to improve the quality of surface defect images and achieve preprocessing of the dataset. Secondly, the squeeze and excitation network (SENet) attention mechanism is introduced into the backbone network of YOLOv5s model to adaptively adjust weights of each feature channel. Meanwhile, the coordinate attention (CA) attention mechanism is integrated to improve network model’s ability to focus on surface defects. Therefore, the YOLOv5s-SE-CA model is designed to enhance detection capability of steel surface defects. Experimental verification was carried out using the NEU-DET noisy dataset with specific evaluation indicators of image enhancement detection system. Results showed the proposed system has superior performance when compared to traditional models trained on noisy and denoising datasets and achieved more accurate detection of surface defects in steel. [ABSTRACT FROM AUTHOR]

The performance and scalability of perovskite solar cells (PSCs) based on 3D formamidinium lead triiodide (FAPbI3) absorber are often hindered by defects at the surface and grain boundaries of the perovskite. To address this, the study demonstrates the use of pyrrolidinium iodide for the in situ formation of an energetically aligned 1D pyrrolidinium lead triiodide (PyPbI3) capping layer over the 3D FAbI3 perovskite. The thermodynamically stable PyPbI3 perovskitoids, formed through cation exchange reactions, effectively reduce surface and grain boundary defects in the FAPbI3 perovskite. In addition to improved phase stability, the resulting 1D/3D perovskite film forms a cascade energy band alignment with the other functional layers in PSCs, enabling a barrier‐free interfacial charge transport. With a maximum power conversion efficiency (PCE) of ≈23.1% and ≈20.7% at active areas of 0.09 and 1.05 cm2, respectively, the 1D/3D PSCs demonstrate excellent performance and scalability. Leveraging this improved scalability, the study has successfully developed a mechanically‐scribed 1D/3D perovskite mini‐module with an unprecedentedly high PCE of ≈20.6% and a total power output of ≈270 mW at an active area of ≈13.0 cm2. The 1D/3D multi‐dimensional perovskite film developed herein holds great promise for producing low‐cost, high‐performance perovskite photovoltaics at both the cell and module levels. [ABSTRACT FROM AUTHOR]

This study presents the Br‐rich in situ synthesis of blue‐emitting 2D CsPbBr3 nanoplatelets (NPLs) with various Br/Pb ratios using ZnBr2 as a Br precursor to enhance Br ion adsorption significantly. This leads to effective passivation of surface defects, particularly Pb−Br bonds, by increasing the positive charge density around Pb atoms, thus creating a stable bonding environment and reducing defect formation. Consequently, the photoluminescence quantum yield (PLQY) improves from 31.15% for a Br/Pb ratio of 2 to 87.2% for a ratio of 6. NPLs with a Br/Pb ratio of 6 also exhibit longer lifetimes (16.69 ns) and slower bleach recovery dynamics, indicating fewer non‐radiative recombination pathways and effective exciton dynamics. Additionally, NPLs with the Br/Pb ratio of 6 demonstrated better thermal stability, with an activation energy of 124.3 meV, indicating stronger exciton binding. These NPLs also exhibited enhanced stability, with UV tolerance at 43.9% and water resistance at 23.8%, making them suitable for displays and lighting. Furthermore, Br‐passivated CsPbBr3 NPLs are used as blue emitters in prototype white LEDs, achieving a wide color gamut, 126.6% of the National Television Standards Committee and 94.5% of Rec. 2020, demonstrating their potential for high‐quality lighting and advanced display technologies. [ABSTRACT FROM AUTHOR]

All-perovskite tandem solar cells have shown great promise in breaking the Shockley–Queisser limit of single-junction solar cells. However, the efficiency improvement of all-perovskite tandem solar cells is largely hindered by the surface defects induced non-radiative recombination loss in Sn–Pb mixed narrow bandgap perovskite films. Here, we report a surface reconstruction strategy utilizing a surface polishing agent, 1,4-butanediamine, together with a surface passivator, ethylenediammonium diiodide, to eliminate Sn-related defects and passivate organic cation and halide vacancy defects on the surface of Sn–Pb mixed perovskite films. Our strategy not only delivers high-quality Sn–Pb mixed perovskite films with a close-to-ideal stoichiometric ratio surface but also minimizes the non-radiative energy loss at the perovskite/electron transport layer interface. As a result, our Sn–Pb mixed perovskite solar cells with bandgaps of 1.32 and 1.25 eV realize power conversion efficiencies of 22.65% and 23.32%, respectively. Additionally, we further obtain a certified power conversion efficiency of 28.49% of two-junction all-perovskite tandem solar cells. The efficiency of all-perovskite tandem solar cells is impacted by the nonradiative recombination loss in Sn–Pb mixed narrow bandgap perovskite films. Here, the authors utilize a surface polishing agent with surface passivator to deliver films with a close-to-ideal stoichiometric ratio surface. [ABSTRACT FROM AUTHOR]

In this study, Ga2O3 blocking layers (BLs) are used to improve the properties of dye-sensitized solar cells (DSSCs) by sputtering. The wide energy bandgap of Ga2O3 BLs not only can passivate the surface defects of TiO2 working electrodes but also can prevent the reverse leakage current from narrow energy bandgap of TiO2 working electrode. Compared with conventional narrow energy bandgap BLs, wide energy bandgap BLs are more effective in enhancing the power generation efficiency of DSSCs. After Ga2O3 BL deposited on TiO2 working electrode, the proportions of Ti3+ and Ti2+ can be reduced and the proportion of stable valence Ti4+ can be increased considerably. Moreover, the efficiency of DSSC with Ga2O3 BL increased from 4.06% to 5.72%. According to the results of electrochemical impedance spectroscopy analysis, the Ga2O3 BL increased the DSSC carrier lifetime from 0.17 to 0.35 ms and charge collection efficiency from 55.28% to 61.77%. Accordingly, the results of this study indicate that wide energy bandgap Ga2O3 BLs effectively prevent the formation of reverse leakage current, passivate working electrode defects in DSSCs, and are suitable for improving the performance of optoelectronic devices. [ABSTRACT FROM AUTHOR]

The notch effect significantly influences the fatigue response of components and is particularly relevant for parts produced with additive manufacturing (AM) processes, characterized by complex geometries and possible geometric discontinuities inducing local and critical peak stresses. Moreover, the low surface quality, as well as manufacturing defects and residual stresses, interacts with the local peak stress induced by geometric discontinuities, complicating the assessment of the notch effect for AM parts and requiring extensive experimental fatigue investigations. In the present paper, the notch sensitivity of as‐built AlSi10Mg specimens produced with the laser beam powder bed fusion in the Very High Cycle Fatigue regime is investigated. Ultrasonic fatigue tests up to 109 cycles have been carried out on rectangular bars and rectangular bars with a central through‐thickness hole. The notch effect has been found to significantly affect the fatigue response of the investigated AlSi10Mg specimens, with surface defects having a main role and pointing out the influence of the surface quality on the crack formation. [ABSTRACT FROM AUTHOR]

MXene quantum dots (MQDs), an emerging zero‐dimensional nanomaterial, have garnered significant attention from researchers due to their distinctive physical and chemical properties. In this study, cysteine‐functionalized Ti3C2 MQDs were synthesized using a facile hydrothermal methods, resulting in the functionalized Ti3C2 MQDs exhibiting intense blue fluorescence attributed to size‐dependent effects and surface defects. Furthermore, the cysteine‐functionalized Ti3C2 MQDs exhibit excitation wavelength‐dependent emission behavior and serve as a highly sensitive fluorescent probe for Ag+ detection with an impressive low limit of detection (LOD) of 0.015 μM. Moreover, they demonstrate exceptional sensitivity and selectivity in determining Ag+. This study presents a novel approach for the detection of Ag+ and highlights the immense potential of cysteine‐functionalized Ti3C2 MQDs in environmental applications. [ABSTRACT FROM AUTHOR]

Amorphous inorganic perovskites have attracted significant attention as efficient electrocatalysts due to their unique structural flexibility and good catalytic activity. In particular, the disordered structure and a surface rich in defects such as oxygen vacancies can contribute to the superior electrocatalytic activity of amorphous oxides compared to their crystalline counterpart. In this work, we report the synthesis of LaCoO3, followed by an amorphization process through urea reduction with tailored modifications. The as‐synthesized catalysts were thoroughly tested for their performance in oxygen evolution reaction (OER), Remarkably, the amorphous LaCoO3 synthesized at 450 °C (referred to as LCO‐4) exhibits excellent OER catalytic activity. At an overpotential of 310 mV, it achieved a current density of 10 mA/cm−2, exceedingly fast to 1 A/cm−2 at an overpotential of only 460 mV. Moreover, LCO‐4 exhibited several advantageous features compared to pristine LaCoO3 and LaCoO3 amorphized at other two temperatures (350 °C, LCO‐3, and 550 °C, LCO‐5). The amorphized LCO‐4 catalyst showed a higher electrochemically active surface area, a key factor in boosting catalytic performance. Additionally, LCO‐4 demonstrated the lowest Tafel slope of 70 mVdec−1, further highlighting its exceptional OER activity. Furthermore, the long‐term stability of LCO‐4 is notably superior than pristine LaCoO3 (LCO‐P) and the other amorphized samples (LCO‐3 and LCO‐5). The enhanced catalytic activity of LCO‐4 can be attributed to its unique disordered structure, small crystallite size, and higher concentration of oxygen vacancies in the final catalyst. [ABSTRACT FROM AUTHOR]

Capacitance spectroscopy techniques have been widely utilized to evaluate the defect properties in perovskites, which contribute to the efficiency and operation stability development for perovskite solar cells (PSCs). Yet the interplay between the charge transporting layer (CTL) and the perovskite on the capacitance spectroscopy results is still unclear. Here, they show that a pseudo‐trap‐state capacitance signal is generated in thermal admittance spectroscopy (TAS) due to the enhanced resistance capacitance (RC) coupling caused by the carrier freeze‐out of the CTL in PSCs, which could be discerned from the actual defect‐induced trap state capacitance signal by tuning the series resistance of PSCs. By eliminating the RC coupling shielding effect on the defect‐induced capacitance spectroscopy, it is obtain the actual defect density which is 4‐folds lower than the pseudo‐trap density, and the spatial distribution of defects in PSCs which reveals that the commonly adopted interface passivators can passivate the defects about 60 nm away from the decorated surface. It is further revealed that phenethylammonium ions (PEA+) possess a better passivation capability over octylammonium ions (OA+) due to the deeper passivation depth for PEA+ on the surface defects in perovskite films. [ABSTRACT FROM AUTHOR]

MXene quantum dots (MQDs), an emerging zero‐dimensional nanomaterial, have garnered significant attention from researchers due to their distinctive physical and chemical properties. In this study, cysteine‐functionalized Ti3C2 MQDs were synthesized using a facile hydrothermal methods, resulting in the functionalized Ti3C2 MQDs exhibiting intense blue fluorescence attributed to size‐dependent effects and surface defects. Furthermore, the cysteine‐functionalized Ti3C2 MQDs exhibit excitation wavelength‐dependent emission behavior and serve as a highly sensitive fluorescent probe for Ag+ detection with an impressive low limit of detection (LOD) of 0.015 μM. Moreover, they demonstrate exceptional sensitivity and selectivity in determining Ag+. This study presents a novel approach for the detection of Ag+ and highlights the immense potential of cysteine‐functionalized Ti3C2 MQDs in environmental applications. [ABSTRACT FROM AUTHOR]

The presence of a high density of defects at the perovskite/electron transport layer (ETL) interface results in significant nonradiative recombination losses, thus impeding the efficiency enhancement of perovskite/silicon tandem solar cells (TSCs). In this investigation, a metallocene‐based molecule, cobalt (III) dichlorophene hexafluorophosphate (CcPF6), is employed for perovskite surface passivation. To maximize its efficacy, the molecule is dissolved in a mixed solvent of acetonitrile and chlorobenzene, leading to the reconstruction of the perovskite surface and effective passivation of surface defects. This modification strategy substantially enhances the overall efficiency of perovskite/silicon tandem solar cells by mitigating the issue of low fill factor resulting from non‐uniform coating of the top perovskite layer on the textured silicon bottom cell. Leveraging a double‐sided textured silicon heterojunction (HJT) bottom cell, a certified power conversion efficiency (PCE) of 30.43% for a monolithic perovskite/silicon TSC (1.00 cm2) is achieved, featuring an open‐circuit voltage (Voc) of 1.93 V and a fill factor (FF) of 78.43%. After storage in the drying cabinet (5% humidity at 20 °C) for 1000 h, the device retains 94.27% of its initial performance. [ABSTRACT FROM AUTHOR]

The mechanical durability and efficiency of all‐inorganic flexible perovskite solar cells (f‐PSCs) still require enhancement for practical applications. In this study, a creative debridement strategy to improve the mechanical durability and photovoltaic performance of all‐inorganic f‐PSCs by pre‐bending the flexible perovskite film and then depositing the passivation agent 2‐mercaptopyridine is proposed. The pre‐bending process induced the generation of microcracks in the perovskite film surface, and 2‐mercaptopyridine can more effectively penetrate the interior of the film through the microcracks, thereby further passivating deep surface defects. These microcracks and defects can be perfectly repaired by 2‐mercaptopyridine. Bidentate coordination sites of S and N in 2‐mercaptopyridine show stronger binding energy with surface defects. The debridement strategy effectively enhanced the crystallization of the film surface and markedly inhibited crack propagation during the film's bending process. The optimized device achieves a champion power conversion efficiency (PCE) of 14.74%. The pre‐bent and passivated all‐inorganic f‐PSC shows 104% of its initial PCE after 15 000 bending cycles at a curvature radius of 3 mm. Remarkably, even after undergoing 70 000 bending cycles at a curvature radius of 5 mm, pre‐bent, and passivated f‐PSC can retain over 93% of its initial PCE, exhibiting excellent mechanical durability. [ABSTRACT FROM AUTHOR]

Passivation materials play a crucial role in a wide range of high-efficiency, high-stability photovoltaic applications based on crystalline silicon and state-of-the-art perovskite materials. Currently, for perovskite photovoltaic, the mainstream passivation strategies routinely rely on crystalline materials. Herein, we have invented a new amorphous (lysine)2PbI2 layer-enhanced halide perovskite. By utilizing a solid phase reaction between PbI2 and lysine molecule, an amorphous (lysine)2PbI2 layer is formed at surface/grain boundaries in the perovskite films. The amorphous (lysine)2PbI2 with fewer dangling bonds can effectively neutralize surface/interface defects, achieving an impressive efficiency of 26.27% (certified 25.94%). Moreover, this amorphous layer not only reduces crystal lattice stress but also functions as a barrier against the decomposition of organic components, leading to suppressed de-structuring of perovskite and highly stable perovskite solar cells. The mainstream passivation strategies routinely rely on crystalline materials for perovskite photovoltaics. Here, authors utilize a solid phase reaction to prepare an amorphous (lysine)2PbI2 layer to neutralize surface and interface defects, achieving device efficiency of over 26% for solar cells. [ABSTRACT FROM AUTHOR]

Pore and crack formation in parts produced by additive manufacturing (AM) processes, such as laser powder bed fusion, is one of the issues associated with AM technology. Surface and subsurface cracks and pores are induced during the printing process, undermining the printed part durability. In-situ detection of defects will enable the real-time or intermittent control of the process, resulting in higher product quality. In this paper, a new eddy current-based probe design is proposed to detect these defects in parts with various defects that mimic pores and cracks in additively manufactured parts. Electromagnetic finite element analyses were carried out to optimize the probe geometry, followed by fabricating a prototype. Artificial defects were seeded in stainless steel plates to assess the feasibility of detecting various flaws with different widths and lengths. The smallest defect detected had a 0.17 mm radius for blind holes and a 0.43 mm notch with a 5 mm length. All the defects were 0.5 mm from the surface, and the probe was placed on the back surface of the defects. The surface roughness of the tested samples was less than 2 µm. The results show promise for detecting defects, indicating a potential application in AM. [ABSTRACT FROM AUTHOR]

Tin dioxide (SnO2), one of the best electron transport layer materials for perovskite solar cells (PSCs), has high electrical conductivity and low photocatalytic activity. However, the defects in its inside and surface result in nonradiative recombination at the SnO2/perovskite interface. Complex and time‐consuming passivation methods are not conducive to the commercialization of PSCs, and simple passivation strategies should be used to improve the photovoltaic performance of the devices. Herein, a facile and efficient method is proposed to simultaneously passivate the inside and surface defects by adding histidine (HIS) to SnO2 colloidal solution. This one‐step doping strategy also modulates carrier dynamics at the SnO2/perovskite interface. HIS reduces suspended hydroxyl groups, oxygen vacancies, and uncoordinated Sn4+ defects on the surface of SnO2, as well as uncoordinated Pb2+ and halogen vacancy defects at the buried interface of perovskite. Surprisingly, HIS can prevent perovskite from decomposition to form PbI2, which further decomposes to photoactive metallic Pb0 and I, causing ion migration in PSC. As a result, the PSC efficiency has significantly improved 23.11% after HIS doping. The efficiency of unencapsulated device with HIS is 94% of the primary efficiency after storage in relative humidity = 70 ± 5% for 1000 h. [ABSTRACT FROM AUTHOR]

The deep-blue emitting 2ML DBSA-CsPbBr 3 NPLs prepared by the ligand-mediated synthesis strategy exhibit a record PLQY value of 81.2% and an ultra-narrow FWHM (11 nm). [Display omitted] • The ligand-mediated synthesis strategy was proposed to prepare deep-blue emitting 2ML CsPbBr 3 NPLs. • The obtained 2ML DBSA-CsPbBr 3 NPLs show a record PLQY of 81.2 % and ultra-narrowFWHMof 11 nm. • A formation mechanism for the preparation of deep-blue emitting 2ML CsPbBr 3 NPLs has been explored. Two-dimensional (2D) CsPbBr 3 nanoplatelets (NPLs) have attracted great attention as one of promising semiconductor nanomaterials due to their large exciton binding energy and narrow emission spectra. However, the labile ionic and weakly bound surfaces of deep-blue emitting CsPbBr 3 NPLs with wide bandgap result in their colloidal instability, thus degrading their optical properties. It is challenging to obtain deep-blue emitting CsPbBr 3 NPLs with excellent optical properties. In this study, high-quality blue-emitting CsPbBr 3 NPLs with tunable thickness were prepared adopting the DBSA-mediated confinement effect based on the hot-injection method. Thanks to the coordination interaction of − SO 3 − of DBSA ligand and the Pb2+ on the surface of the CsPbBr 3 NPLs, as well as the effective passivation of Br vacancy defects on the surface of NPLs by OAm-Br, the obtained pure-blue CsPbBr 3 NPLs and deep-blue CsPbBr 3 NPLs show high photoluminescence quantum yield (PLQY) of 92 % and 81.2 %, respectively. To the best of our knowledge, this is the highest PLQY recorded for deep-blue emitting CsPbBr 3 NPLs with two monolayers [PbBr 6 ]4− octahedra. Furthermore, the agglomeration of CsPbBr 3 NPLs due to ligand loss induced by moisture, oxygen, and irradiation was also suppressed by the dual passivation effect of DBSA and OAm-Br. Our work provided a new approach to developing high-performance and stable deep-blue emitting CsPbBr 3 perovskite nanoplatelets. [ABSTRACT FROM AUTHOR]

The stress corrosion behavior of Ti‐6Al‐3Nb‐2Zr‐1Mo (Ti6321, in wt%) alloy in seawater with different dissolved oxygen (DO) concentrations was investigated using X‐ray photoelectron spectroscopy, energy dispersive spectrometer, electrochemical measurements, and other advanced methodologies. The results indicate that when the DO concentration in seawater is insufficient, the passivation film will preferentially form on the α‐phase surface. Meanwhile, insufficient DO concentration leads to incomplete oxidation of the surface passivation film, resulting in an increase in surface defects. Hydrogen produced by reactions at crack tips is more likely to enter the surface of the titanium alloy through these defects, and under the influence of HEDE and HELP mechanisms, promote crack propagation. [ABSTRACT FROM AUTHOR]

Metal-organic framework (MOF) has gained widespread attention as promising electromagnetic waves (EMWs) absorbent due to its 3D structure, porosity and easier modification. However, the structural instability and impedance mismatch presented a serious challenge in meeting the ultra-strong and ultra-broad absorption requirement for EMWs. Therefore, a facile strategy has been applied to prepare carbon nanotubes modified nitrogen-doped carbon encapsulated Co (Co@CN/CNTs) composites by regulating the mass ratio of Co-ZIF67 and melamine under high-temperature pyrolysis. The in-situ synthesis of CNTs and doping of nitrogen-atoms optimized the impedance matching of Co@CN/CNTs composites. The 3D heterostructure, porosity, surface defects and conductive network enhanced EMWs absorption ability. The ultra-strong reflection loss (RL) for Co@CN/CNTs-1:1 sample of −112.14 dB was reached with only 1.3 mm match thickness and corresponding ultra-broad effective absorption bandwidth (EAB) was up to 8.2 GHz. This research could be expected to provide a novel scheme for design and preparation of MOFs derived EMWs absorption materials. [ABSTRACT FROM AUTHOR]

In this study, we investigated the humidity sensing properties of TiO2-based ceramics doped with tantalum pentoxide (Ta2O5) and indium tin oxide (ITO). Pure TiO2, 1%Ta-doped TiO2 (1%TTO), 1%ITO-doped TiO2 (1%ISTO), and 1%(Ta2O5 + ITO) co-doped TiO2 (1%ISTTO) ceramic samples were obtained by sintering at 1200 °C for 3 h. The rutile phase was observed in all samples. The lattice parameters of the single and co-doped samples were larger than those of pure TiO2, confirming the substitution of dopants. Porosity was observed in all ceramics. The mean grain sizes of all doped samples were significantly reduced compared to undoped TiO2. A homogeneous element dispersion was observed in the 1%TTO and 1%ISTTO ceramics, while segregation particles of related In-rich elements was observed in the 1%ISTO ceramic. Giant dielectric properties were not achieved in any samples due to the porosity. Nevertheless, excluding the undoped TiO2, the dielectric properties of all porous ceramics varied significantly with changes in humidity. The 1%ISTTO ceramic demonstrated superior humidity sensing properties, including a low maximum hysteresis error of 3.6% at 102 Hz. In contrast, the 1% TTO and 1% ISTO ceramics showed higher maximum hysteresis errors of 7.2% and 19.8%, respectively. Notably, the response and recovery times were 7.05 ± 0.18 and 2.48 ± 0.39 min, respectively, with good repeatability. This improvement is likely due to the synergistic effect of oxygen vacancies and Ta Ti · defects on the surface, enhancing the humidity sensing properties of the 1% ISTTO ceramic, coupled with its optimal microstructure due to its lowest porosity and grain size. [ABSTRACT FROM AUTHOR]