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The task of utilizing machine vision for the detection of casting surface defects is characterized by small targets, real-time performance, and ease of mobility. The direct application of current mainstream object detection networks for defect detection presents issues of low accuracy and efficiency. Consequently, in this paper, we introduce Casting-DETR, an end-to-end network designed for casting surface defect detection. To assess and validate the model's performance, 554 images of casting samples with surface defects were employed. Casting-DETR achieved an impressive detection rate of 98.97% on the test set, with a single image detection time of 91.5ms. Furthermore, a real-time detection system, built using PyQT6, was tested in four different environments. Casting-DETR exhibited exceptional performance, maintaining a single-frame detection time of approximately 90 ms, demonstrating the model's high robustness and suitability for real-time detection. The Casting-DETR network proposed in this paper is an end-to-end solution with rapid convergence, superior detection accuracy, and swift detection speeds, offering a fresh perspective for similar detection tasks within the industry. [ABSTRACT FROM AUTHOR]

The natural non-penetrated openings in natural rock masses due to weathering and erosion and the artificial non-penetrated openings formed in deep mining and tunneling have significant effects on the stability and safety of rock engineering. Hence, the uniaxial compression test, 3D particle flow code (PFC3D) simulation, and digital image correlation (DIC) method are used to systematically investigate the influence of the opening penetration ratio (OPR) on the mechanical behaviors and fracture characteristics of rocks containing the non-penetrated opening. Further, the maximum principal strain/stress distributions around the opening on both sides of the specimen are compared to quantitatively analyze the effect of OPR on the crack initiation mechanism from the microscopic perspective. The results show that as OPR increases, the uniaxial compressive strength (UCS) and elastic modulus (E) of sandstone/numerical specimens show a linearly decrease law, and the failure mode exhibits a law of shear failure to tensile-shear mixed failure and then to shear failure. The fracture process analyses show that the two sides of specimens containing non-penetrated opening have different cracking characteristics and belong three-dimensional failure, while the specimen containing penetrated opening are two-dimensional failure. The stress/strain distribution around the opening is altered by the support effect in the non-opening part of specimens. Therefore, as the OPR increases, the crack initiation stress level decreases and the crack initiation crack type around the opening changes from the tensile-shear to tensile. Finally, implications of the study for fracture prevention in underground excavation engineering and early warning of instability in rock engineering are given. These findings enrich the study on the failure mechanism of rock masses containing defects, which is of great importance for rock engineering safety. Highlights: The uniaxial compression strength and elastic modulus of sandstones decrease linearly with increasing opening penetration depth. The cracking behaviors of sandstone with non-penetrated opening are three-dimensional. The pre-existing defect surface of sandstone with non-penetrated opening is cracking first and failure first. The changes in stress/strain distribution around the opening on both sides make differences in the crack initiation mechanism and initiation stresses. The findings are instructive for fracture prevention in underground excavation engineering and early warning of instability in rock engineering. [ABSTRACT FROM AUTHOR]

Carbon quantum dots (CQDs), as a novel type of carbon nanomaterial, are widely used in fields such as drug delivery, biosensing, fluorescent probes, and photocatalysis, benefiting from their excellent photostability, water solubility, biocompatibility, fluorescence, low-cost, and green non-toxicity. Meanwhile, due to the conjugated π structure of CQDs and surface defects generated by sp2 hybridization, they possess unique optoelectronic properties, including tunable fluorescence, good upconversion photoluminescence, and efficient photoelectron transfer. These properties are key to the role of CQDs in the field of photocatalysis. This review summarises CQDs' research progress and reaction mechanisms in photocatalysis, including their optical properties and synthesis strategies. Emphasis was placed on the application of CQDs in the field of photocatalysis, including photocatalytic CO2 conversion, degradation of organic and heavy metal pollutants, hydrogen production, and nitrogen fixation. In addition, the challenges and prospects of CQDs in the field of photocatalysis are discussed, providing new ideas for studying CQDs photocatalytic materials. [ABSTRACT FROM AUTHOR]

Strand surface defects originate from the initial solidification of molten steel in continuous casting mold. This article investigates the initial solidification behavior during the continuous casting of 55SiCr spring steel billet using a novel mold simulator. First, the high‐frequency responding temperatures and high‐frequency heat fluxes across the mold corner and hot face are calculated by the 2D‐inverse heat conduction program mathematical model and the fast Fourier transformation, and the results indicate that the temperature variations and heat flux fluctuations around mold corner are stronger than those at mold hot face. Then, the characteristic heat fluxes around the meniscus at mold corner and hot face are analyzed, and their four corresponding signals are discussed with the help of power spectral density analysis. The average solidification factor K for shell corner is greater than shell face, which indicates that the cooling intensity of shell at corner is stronger due to the two‐dimensional heat transfer near mold corner, as demonstrated by heat transfer and dendrite structure analysis. Finally, the interrelations between the shell profile, mold oscillation, heat flux change rate, high‐frequency heat flux, temperature change rate, and high‐frequency temperature for the two cases are discussed. [ABSTRACT FROM AUTHOR]

Host‐guest complexation offers a promising approach for mitigating surface defects in perovskite solar cells (PSCs). Crown ethers are the most widely used macrocyclic hosts for complexing perovskite surfaces, yet their supramolecular interactions and functional implications require further understanding. Here we show that the dipole moment of crown ethers serves as an indicator of supramolecular interactions with both perovskites and precursor salts. A larger dipole moment, achieved through the substitution of heteroatoms, correlates with enhanced coordination with lead cations. Perovskite films incorporating aza‐crown ethers as additives exhibited improved morphology, reduced defect densities, and better energy‐level alignment compared to those using native crown ethers. We report power‐conversion efficiencies (PCEs) exceeding 25 % for PSCs, which show enhanced long‐term stability, and a record PCE of 21.5 % for host–guest complexation‐based perovskite solar modules with an active area of 14.0 cm2. [ABSTRACT FROM AUTHOR]

Good lubrication performance plays a vital role in reducing friction and ensuring stable operation of machine tool spindles. The performance of traditional lubricants has reached its limit and cannot meet the needs of the high-speed development of advanced equipment, and nanomaterials have attracted much attention due to their small size and excellent ability to repair defects on metal surfaces. Different nanomaterials, influencing factors, and surface modification methods have been extensively investigated for an in-depth understanding of the tribological performance of nano-lubricants. However, a comprehensive examination of the thorough classification of nano-additives, the revelation of nanoscale lubrication mechanisms, and their potential employs on bearings is lacking. This systematic review comprehensively investigates the types of nano-lubricants, tribological properties, and lubrication mechanisms. Recent advances in various numerical and experimental studies of different nano-lubricants for improving the performance of sliding bearings are summarized. The importance of utilizing nano-lubricants in bearing-rotor systems is emphasized and the limitations and main challenges in applications are analyzed. Future research should be devoted to the development of high-performance nano-lubricants to improve spindle performance and work stability. [ABSTRACT FROM AUTHOR]

This research paper presents an innovative approach to fabricating enhanced-quality hierarchical surface micro-textures on Ti6Al4V alloy by synergistically employing in situ electrical discharge machining (EDM) and electrochemical machining (ECM) processes. The hierarchical structure encompasses three levels: a primary level at a few hundred micrometers, a secondary level at a few tens of micrometers, and a ternary level at sub-micrometer scales. Despite the precision achieved in generating the primary-level texture through EDM using a chemically patterned tool, inherent thermal damages and surface defects, such as micro-craters and irregularities, pose challenges. Unlike usual ex situ chemical or electrochemical post-processing methods, this study introduces in situ ECM post-processing (ECM) with the same patterned tool. This approach enhances the quality of EDMed surfaces without compromising geometrical accuracy, offering anisotropic dissolution along the feature depth. To ensure geometrical accuracy, an experimentally validated finite element method-based transient numerical simulation model is developed. This model accurately predicts the evolution of the feature profile during the ECM operation. Furthermore, ECM with a fluoride ion–containing electrolyte introduces additional secondary and ternary levels of hierarchical textures. Fluoride ions play a pivotal role in augmenting material removal during ECM, particularly in areas around micro-crevices and pores, shaping the secondary-level texture. [ABSTRACT FROM AUTHOR]

Low-operating temperature gas sensors play a pivotal role in environmental and health safety. Here, we investigate the performance of hexagonal ZnO nanostructures for detecting hazardous ethanol gas. Pure and 3% Mn doped ZnO thin films were synthesized by a spray pyrolysis method. The study focused on investigating structural, morphological, chemical composition, optical and gas sensing properties of these films. By adding 3% Mn doping, the structural, morphological and optical properties of ZnO film notably changed. The 3% Mn-doped ZnO thin film exhibits a high response of 360 compared to undoped ZnO (154) towards 50 ppm of ethanol at room temperature. This may be due to the increased surface reactivity and defects sites. The response/recovery time of the Mn-doped ZnO to ethanol is found to be 18/40s. Gas sensing studies suggest that the 3% Mn-doped ZnO thin film has good reproducibility, stability and selectivity. The sensing mechanism of ethanol by Mn-doped ZnO thin films is studied and discussed. These findings suggest that Mn-doped ZnO thin films are promising candidates for low temperature ethanol sensing application. [ABSTRACT FROM AUTHOR]

[Display omitted] • Swelling-assisted pyrolysis was proposed for the recovery of glass fibers from WTBs. • Resin decomposition ratio reached 76.8 % at 350 °C in swelling-assisted pyrolysis. • The swelling treatment physically disrupted the cross-linked structure of the WTBs. • The oxidation duration was reduced owing to the less content of pyrolysis char. • Tensile strength of fibers from swollen-WTB was higher than that from original-WTB. The recycling of end-of-life wind turbine blades has become a global environmental challenge driven by the rapid growth of wind power. Pyrolysis is a promising method for recovering glass fibers from these discarded blades, but traditional pyrolysis is often operated at high temperatures, which degrades the mechanical properties of recovered fibers. To address this issue, a swelling-assisted pyrolysis method was proposed to recover high-quality glass fibers from end-of-life wind turbine blades at low temperatures. The results confirmed that the decomposition of the resin matrix within the blade was significantly promoted at low temperatures in the swelling-assisted pyrolysis process, achieving a resin decomposition ratio of 76.8 % at 350 °C. This improvement was attributed to enhanced heat transfer and co-pyrolysis with acetic acid. Swelling could physically disrupt the cross-linked structure of the blade, creating a more porous and layered structure, thereby enhancing heat transfer during the pyrolysis process. Simultaneously, the co-pyrolysis with acetic acid could generate hydrogen radicals, which promoted the cracking of macromolecular oligomers into lighter products or gaseous alkanes. Consequently, the formation of pyrolysis char within the solid pyrolysis product was reduced, shortening the oxidation duration to 30 min. In comparison to traditional pyrolysis, the swelling-assisted pyrolysis process effectively suppressed the diffusion of surface defects over the recovered fibers, leading to promising improvements in their flexibility, elasticity, and mechanical properties, with tensile strength notably increased by 27.5 %. These findings provided valuable insights into recovering high-quality glass fibers from end-of-life wind turbine blades. [ABSTRACT FROM AUTHOR]

The rail is an important component of track infrastructure, which withstands repeated wheel loading directly, and its condition is related to the safety of train operation. Thus, accurately identifying the size and location of surface defects in rails helps to optimize maintenance strategies, including adjusting regular monitoring and conducting timely repairs. This approach not only mitigates risks but also enhances work efficiency, which has real economic value and brings safety guarantees. This paper aims to build a data-driven model for rail surface defect identification using photos taken in real lines. Two modules, multidirection rectangular convolution (MRC) and cross-scale (CS) feature extraction, are proposed. The results indicate that the detection and classification of multiple rail surface defects can be automated simultaneously with greater accuracy. Among the defects, spalling sees the most significant boost, and its average detection precision increases from 44.1% to 67%. Moreover, the accuracy for detecting a bright contact band and corrugation exceeds 90%, with 0.995 and 0.915, respectively. Compared with the original You Only Look Once algorithm version 8, the mean of average precision (mAP) of the improved network increases from 85.3% to 88.1% when both models are trained for 300 epochs. Additionally, the precise location and size information of the rail surface defects are obtained through postprocessing, providing support for further intelligent track maintenance. [ABSTRACT FROM AUTHOR]

Steel surface defect detection is crucial in manufacturing, but achieving high accuracy and real-time performance with limited computing resources is challenging. To address this issue, this paper proposes DFFNet, a lightweight fusion network, for fast and accurate steel surface defect detection. Firstly, a lightweight backbone network called LDD is introduced, utilizing partial convolution to reduce computational complexity and extract spatial features efficiently. Then, PANet is enhanced using the Efficient Feature-Optimized Converged Network and a Feature Enhancement Aggregation Module (FEAM) to improve feature fusion. FEAM combines the Efficient Layer Aggregation Network and reparameterization techniques to extend the receptive field for defect perception, and reduce information loss for small defects. Finally, a WIOU loss function with a dynamic non-monotonic mechanism is designed to improve defect localization in complex scenes. Evaluation results on the NEU-DET dataset demonstrate that the proposed DFFNet achieves competitive accuracy with lower computational complexity, with a detection speed of 101 FPS, meeting real-time performance requirements in industrial settings. Furthermore, experimental results on the PASCAL VOC and MS COCO datasets demonstrate the strong generalization capability of DFFNet for object detection in diverse scenarios. [ABSTRACT FROM AUTHOR]

To address the challenge of detecting tiny flaws in tile defect detection, a lightweight algorithm for identifying minor defects in tile images has been developed, referred to as CTDD-YOLO. Firstly, CAACSPELAN is proposed as the core component of the backbone network for extracting features of tile defects; secondly, full-dimensional dynamic convolution ODConv is introduced at the end of the backbone network to enhance the model's ability to deal with tiny defects; next, a new neck network, CGRFPN, is proposed to improve the model's ability to represent multi-scale features and enhance the model's ability to recognize small targets in the context of large formats; finally, MPNWD is proposed to optimize the loss function to improve the model's detection accuracy further. Experiments on the Ali Tianchi tile defect detection dataset show that the CTDD-YOLO model not only has a lower number of parameters than the original YOLOv8n but also improves the mAP by 7.2 percentage points, i.e., the proposed model can more accurately recognize and deal with minor surface defects of tiles and can significantly improve the detection effect while maintaining the light weight. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Laser directed energy deposition (LDED), a class of additive manufacturing (AM) processes, has immense potential to be used for various engineering applications to build components with medium to high complexity. However, dimensional deviations from intended values and inadequate surface quality of the built parts limit its wide deployment. The present work reports the development of an adaptive tool path trajectory platform to correct the dimensional inaccuracies in-situ to build high-quality components using LDED. The study deploys a laser line scanner to scan the part after the deposition of the definite number of layers followed by the detection of concave, convex, and flat surfaces using deep learning. Further, a novel adaptive trajectory planning algorithm is deployed by using three different strategies to control material deposition on concave, convex, and flat surfaces. The material deposition is controlled by using adaptive scanning speed control (ASSC), and a combination of laser on–off and scanning speed control (ASSLC). Subsequently, the built geometries are subjected to geometric, microstructure, and mechanical characterizations. It is observed that the deviation of the part was reduced by 30%, and 27.5% using ASSC and ASSLC, respectively. The structures built using the three strategies show some micropores at isolated locations. The microstructure is mainly cellular under all conditions with a similar average microhardness of ~ 210 HV. The study provides an integrated and comprehensive approach for building high-quality large-scale components using LDED with minimal dimensional deviation from the original CAD model. [ABSTRACT FROM AUTHOR]

This article delves into optimizing and modeling the input parameters for the selective laser melting (SLM) process on Inconel 625. The primary aim is to investigate the microstructure within the interlayer regions post-process optimization. For this study, 100 layers with a thickness of 40 µm each were produced. Utilizing the design of experiments (DOE) methodology and employing the Response Surface Method (RSM), the SLM process was optimized. Input parameters such as laser power (LP) and hatch distance (HD) were considered, while changes in microhardness and roughness, Ra, were taken as the responses. Sample microstructure and surface alterations were assessed via scanning electron microscopy (SEM) analysis to ascertain how many defects and properties of Inconel 625 can be controlled using DOE. Porosity and lack of fusion, which were due to rapid post-powder melting solidification, prompted detailed analysis of the flaws both on the surfaces of and in terms of the internal aspects of the samples. An understanding of the formation of these imperfections can help refine the process for enhanced integrity and performance of Inconel 625 printed material. Even slight directional changes in the columnar dendrite structures are discernible within the layers. The microstructural characteristics observed in these samples are directly related to the parameters of the SLM process. In this study, the bulk samples achieved a microhardness of 452 HV, with the minimum surface roughness recorded at 9.9 µm. The objective of this research was to use the Response Surface Method (RSM) to optimize the parameters to result in the minimum surface roughness and maximum microhardness of the samples. [ABSTRACT FROM AUTHOR]

CsPbIBr2 has garnered significant interest due to its ideal bandgap and good stability. However, defects formed at the interface between the electron transport layer and the perovskite can lead to increased non‐radiative recombination, which negatively impacts both the power conversion efficiency (PCE) of perovskite solar cells and the long‐term stability of the cells. Herein, the TiO2/perovskite interface is modified by adding sodium silicate to passivate the defects on the interface. The introduction of Na+ partially reduces Ti4+ to Ti3+ in TiO2, thereby passivating trap states caused by oxygen vacancy defects and adjusting the energy level alignment between TiO2 and the perovskite film, enhancing the carrier transport efficiency. Additionally, SiO32− can form SiOPb (and Cs) bonds with the undercoordinated Pb2+ and Cs+ on the surface of the perovskite layer, effectively passivating surface defects of the perovskite film and thereby improving the efficiency of the devices. Ultimately, the carbon‐based all‐inorganic CsPbIBr2 perovskite solar cells treated with Na2SiO3 exhibit a significantly improved PCE of 10.85% compared to 8.62% of the control sample and achieve a high open‐circuit voltage of 1.31 V. With this modification, the devices also demonstrate reduced hysteresis effects and enhanced stability. [ABSTRACT FROM AUTHOR]

The nonradiative recombination arising from the interfaces of perovskite solar cells (PSCs) pose a hurdle, impacting both the efficiency and stability of devices. Functionalized organic molecules can passivate the perovskite surface to suppress the defects and can also fine‐tune the microstructure. This in turn promotes reliability and performance enhancement in solar cells. Using a design protocol, cyanoguanidine diiodide is synthesized and employed as a surface passivator for the fabrication of PSCs, and boosted performance from 20.44% to 23.04% is achieved. This improvement stems from an improved fill factor reaching up to 80.64%, together with the open‐circuit voltage (Voc) measuring 1119 mV. The steady‐state photoluminescence and microstructure of passivated perovskites display significant surface modification of the perovskite film which favorably impacts the charge carrier transfer at the interface of perovskite and Spiro‐OMeTAD. Our findings suggest that improved solar cell performance is due to the synergetic effect of amino and cyano functional groups along with the iodide reservoir in the organic passivator. [ABSTRACT FROM AUTHOR]

The detection of surface defects on wood-based panels plays a crucial role in product quality control. However, due to the complex background and low contrast of defects in wood-based panel images, features extracted by traditional deep learning methods based on spatial domain processing often contain noise and blurred boundaries, which severely affects detection performance. To address these issues, we have proposed a wood-based panel surface defect detection method based on frequency domain transformation and adaptive dynamic downsampling (FDADNet). Specifically, we designed a Multi-axis Frequency Domain Weighted Information Representation Module (MFDW), which effectively decoupled the indistinguishable low-contrast defects from the background in the transform domain. Gaussian filtering was then employed to eliminate noise and blur between the defects and the background. Additionally, to tackle the issue of scale differences in defects that led to difficulties in accurate capture, we designed an Adaptive Dynamic Convolution (ADConv) module for downsampling. This method flexibly compressed and enhanced features, effectively improving the differentiation of the features of objects of varying scales in the transform space, and ultimately achieved effective defect detection. To compensate for the lack of data, we constructed a dataset of wood-based panel surface defects, WBP-DET. The experimental results showed that the proposed FDADNet effectively improved the detection performance of wood-based panel surface defects in complex scenarios, achieving a solid balance between efficiency and accuracy. [ABSTRACT FROM AUTHOR]

Detecting track geometry and rail surface defects using on-board vehicle monitoring systems is a key issue for rail infrastructure managers to increase availability and reliability while reducing the costs associated with monitoring and maintenance. Rail corrugation is one of the most common rail surface defects which grows in almost all metro, conventional and high-speed lines. This paper focuses on the development of a methodology to detect rail corrugation using axle box acceleration measurements acquired on an in-service high-speed vehicle. The main purpose of the proposed methodology is to distinguish the effect of rail corrugation on the accelerations from the other excitations that can be observed in the same wavelength range. For this purpose, the accelerations are analysed by calculating the fast Fourier transform and the spectrogram. Based on the characteristics of each excitation, the effects of modes of vibration, resonances, bridges, switches, and wheel defects are identified. From the remaining effects, which have congruent characteristics, a hypothesis of rail corrugation is formulated. The hypothesis is consolidated with multibody dynamics simulations and by comparing the corrugation indicators provided by the railway infrastructure company. [ABSTRACT FROM AUTHOR]

Understanding the formation of a slag rim on the mold meniscus is crucial for controlling surface defects in the initial shell. However, there is a scarcity of quantitative studies on this matter. This study has developed a comprehensive three-dimensional (3D) numerical model for analyzing the meniscus multi-phase flow, heat transfer, and solidification, considering mold oscillation. The 3D morphology of the solidifying shell and the slag rim in the meniscus region were accurately reproduced. The solidification depth (DIS), solidification length (LIS) and oscillation mark depth (DOM) of the initial shell were used to quantify the morphological characteristics of the initial shell. The results confirmed that the formation position difference of the slag rim along the circumferential direction of the mold significantly affects the initial solidification and uniform growth of the shell. In the corner of the mold, the deeper overflow makes the oscillation mark extend 2.8 to 3.2 mm in the direction of casting. In addition, in order to quantitatively investigate the influence of the slag rim, a two-dimensional (2D) model is established with phenomena and parameters considered the same as those of the 3D model. According to the slag rim morphology obtained by the 3D model, in the 2D model, it is proposed to construct three slag rims with the same maximum thickness of 6 mm at 10, 20 and 35 mm above the meniscus (HRim). The simulation of initial shell morphology revealed that a lower formation position of the slag rim led to more severe overflow of molten steel from the meniscus, resulting in non-uniform continuous growth of the initial shell. This increases the likelihood of potential blockage in the liquid slag flow towards the slag channel between solidified shell and mold. [ABSTRACT FROM AUTHOR]

During the construction of cable joints, three common defects may occur on the XLPE surface: scratches, moisture exposure, and adhered contaminated particles. To evaluate the impact of these defects on joint performance, this paper establishes a sheet model of XLPE insulation in cable joints to analyze the changes in the electric field under different defects and explore the influence of different defects on the electric field and breakdown voltage. Results of the study reveal that the electric field at the scratch site on XLPE produces severe distortion, being 1.6 times that of non-scratch areas. When exposed to moisture, the more conductive impurities present in the adhered contaminated water on the XLPE surface, the higher the conductivity of the contaminated water, thereby increasing its conductive performance and the electric field strength, which is 1.22-1.4 times that of the non-moist interface. When particles adhere to the XLPE surface, severe distortion occurs at the particle-interface electric field, approximately 1.5 times that of the defect-free interface. Scratches have the most significant impact on the electric field of XLPE insulation. Experimental results also demonstrate that the breakdown voltage without defects is 129.6 kV, while the breakdown voltage with scratch defects is 59.1 kV, moisture defects is 69.7 kV, and particle contamination defects is 59.2 kV, with scratches having the most significant impact on the breakdown voltage of XLPE insulation. These findings provide important insights into the influence of different defects on the insulation performance of cable joints. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of carbon fiber reinforced polymers (CFRP) is crucial in industries, such as aerospace, automotive, and marine, due to their excellent strength-to-weight ratio and corrosion resistance. However, machining CFRP is challenging due to its abrasive nature, which can cause premature tool wear. Some of the commonly used processes for machining these materials are dry milling and abrasive water jet machining (AWJM), which offer the best alternatives from an environmental point of view. This article presents an analysis of the defects and surface quality obtained in CFRP after machining by AWJM and milling. For this purpose, combinations of relevant parameters have been chosen for each process: cutting speed and tool wear in milling and traverse feed rate and hydraulic pressure in AWJM. The results obtained have been evaluated from two points of view: macroscopically, through the evaluation of delamination, and microscopically, through the study of the roughness in terms of Ra. Furthermore, a discussion on functional, environmental, economic, and social terms has been made between both processes. In summary, each machining process generates a specific type of delamination: Type II in milling and Type I in AWJM. In addition, the best Ra results are obtained for pressures of 1200 bar in AWJM. [ABSTRACT FROM AUTHOR]

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

[Display omitted] Highly flexible hydrogels are widely used in fields such as agriculture, drug delivery, and tissue engineering. However, the simultaneous integration of excellent mechanical properties, swelling properties, and high electrical conductivity into a hydrogel is still a great challenge. This work introduces 1D tubular multi-walled carbon nanotubes (MWCNTs) and 2D layered graphene oxide (GO) into polyacrylamide/poly-acrylic acid (PAM/PAA) hydrogels. The high specific surface area and oxygen-containing groups of GO contribute to excellent mechanical properties and water absorption of the PAM/PAA hydrogels, but the conductivity is poorly affected due to the presence of defects on GO surface. However, MWCNTs with large aspect ratios benefit to form continuous conductive paths in PAM/PAA hydrogels which further improves conductivity of the hydrogels. MWCNTs are entangled with PAM/PAA molecular chains to form a dense three-dimensional (3D) network structure, and this special structure improves the water absorption of PAM/PAA hydrogels by 3.7 g g−1. What's more, the MWCNTs/PAM/PAA hydrogel not only provides excellent mechanical properties (compressive strength up to 2.7 MPa), but also has high conductivity (2.3 S m−1). In particular, a strain sensor based on MWCNTs/PAM/PAA hydrogel exhibits exceptional sensitivity (gauge factor = 3.9 at 230–300 % strain) with a rapid response (200 ms) over a wide strain range (50 ∼ 200 %) which enables the ability to precisely and reliably monitor human motion. Therefore, the work provides a new insight into the design of multifunctional hydrogels with application on anatomical water plugging, electronic skin, and biosensors. [ABSTRACT FROM AUTHOR]

[Display omitted] Chemical defects at the surface and grain boundaries of perovskite crystals cause deterioration of conversion efficiency and stability of perovskite solar cells (PSCs). In this study, a multifunctional additive, 5-fluoro-2-pyrimidine carbonitrile (FPDCN) molecule, is added into the perovskite precursor solution in order to passivate the uncoordinated Pb2+ by the cyanogen (–CN) group and pyrimidine N in FPDCN. Interestingly, fluorine (F) atoms interact with FA+ to form hydrogen bonds, which could regulate the perovskite crystallization process for the formation of high-quality perovskite crystals. Besides, the F atoms in FPDCN increase the water contact angle of perovskite films. As a result, the carrier extraction and transport in the perovskite film are significantly enhanced, and the non-radiative recombination is suppressed. The corresponding devices achieve a champion photovoltaic conversion efficiency (PCE) of 20.7 % and a fill factor (FF) of over 83 %. The device based on FPDCN shows long-term stability under a high-humidity atmospheric environment by maintaining 85 % of the initial efficiency after aging of 700 h in the glove box. This study provides a simple and convenient method to prepare stable and efficient PSCs by optimizing the perovskite precursor solution. [ABSTRACT FROM AUTHOR]

Through hydrothermal-induced interfacial reconstruction treatment, a multifaceted combination involving the spinel phase, oxygen vacancies, and reduced manganese is orchestrated to improve the anionic redox reversibility. The designed sample exhibits excellent rate capability and cycling stability, with ultra-low voltage decay of 0.91 mV cycle−1 after 150 cycles. [Display omitted] • Integrated introduction of spinel phase, oxygen vacancy, and reduced manganese in Li-rich layered oxides. • Enhanced initial couloumbic efficiency, superb rate capability, and advanced cycling stability with ultra-low voltage decay. • Chemical formulas unveil the underlying mechanism of surface defect engineering. • The modified sample has a 1.658% cell volume change, close to the "zero strain" of 1 %. • Density functional theory calculations provide comprehensive and in-depth insights. Cobalt (Co)-free lithium (Li)-rich layered oxides (LLOs) have emerged as promising cathode materials for the next generation of Li-ion batteries, attributed to their competitive market positioning and high energy density. Nevertheless, challenges arise from surface oxygen loss due to irreversible anionic redox reactions, leading to severe voltage and capacity decay that hinder the large-scale adoption of LLOs. Herein, we present an innovative, facile, and environmentally friendly hydrothermal approach to induce surface reconstruction of Li 1.2 Mn 0.6 Ni 0.2 O 2 material. A multifaceted combination involving the spinel phase, oxygen vacancies, and reduced manganese is orchestrated to alleviate the irreversible oxygen redox and impressively enhance Li-ion diffusion. The modified sample, owing to this surface transition, demonstrates low-strain and low-distortion properties along with a substantial improvement in structural stability, supported by both experimental validations and theoretical studies. As a result, the engineered sample exhibits exceptional capacity retention of 97.12% after 150 cycles at 1C, with an ultra-low voltage decay (0.91 mV cycle−1). Additionally, noteworthy enhancements in initial coulombic efficiency and rate performance are also observed. This straightforward surface defect engineering method offers a pathway to developing "low-strain" LLOs with superior electrochemical performance, thereby laying a solid foundation for future commercial applications. [ABSTRACT FROM AUTHOR]

Liquid-aluminum tends to adhere to some surfaces rather than others, and the underlying mechanism of the differences in adhesion of liquid-aluminum on different surfaces is still unclear. This manuscript takes liquid-aluminum/aluminum and liquid-aluminum/silicon interfaces as research objects, revealing that solid aluminum surface is aluminophilic but the solid silicon surface is aluminophobic, mainly due to differences in interfacial thermal conductance (ITC) between two interfaces. We also investigate effect of surface temperature on adhesion characteristics of liquid-aluminum on aluminum/silicon surfaces, and decode the reasons from lattice integrity and phonon spectra. It is shown that vibrational state with intact lattice excites fewer low frequency phonons with increasing surface temperature, resulting in a decrease in ITC and thus adhesion force. In diffusion state where lattice is fractured resulting from high temperature, interfacial adhesion is increased due to surface defects. [ABSTRACT FROM AUTHOR]

An in-depth understanding of the microstructure evolution of the thermotropic metamorphic layer is the basis for effectively suppressing surface and subsurface defects in electrical discharge machining (EDM) of Ti–6Al–4V. In this work, the thermo-hydraulic-metallographic coupling model with successive pulse was established for the first time, based on which the visual simulation of time-variant phase transformation in recast layer and heat-affected zone (HAZ) was achieved. Further, the microstructure distribution characteristics in the thermotropic metamorphic layer were investigated from the perspective of experimental observation. The results show that with the accumulation of successive pulse discharges, the temperature on the processed surface gradually increases while the overall temperature distribution tends to be relatively uniform. The microstructure of the EDMed surface is characterized by a layered distribution, in which the recast layer undergoes complete α ′-Ti (martensitic phase) transformation, and HAZ is composed of an upper layer with α ′-Ti and a lower layer with α + β + α ′ mixture. Meanwhile, it was revealed that the microstructure in the β grain of HAZ changed from a staggered distribution of the secondary α -Ti phase to a parallel distribution of the acicular α ′-Ti phase. A transition layer composed of cellular martensite was observed between the recast layer and HAZ, and the internal grain showed a change from parallel arrangement to staggered arrangement as the peak current increased to a relatively larger level. The martensite volume fraction and microhardness of the thermotropic metamorphic layer have also been verified to correlate to the peak current. The combined study of the thermo-hydraulic-metallographic coupling model and insights into microstructure characteristics were expected to provide theoretical references for predicting and controlling the surface integrity in EDM of Ti–6Al–4V. [ABSTRACT FROM AUTHOR]

Figure. Dual-element substitution induced integrated defect structure to suppress voltage decay and capacity fading of Li-rich Mn-based cathode. [Display omitted] • The integrated defects are constructed in Li-rich cathodes by Na 2 SnO 3 modification. • The modification improves the cycling stability and suppresses the voltage decay. • The mechanism of enhanced performance by Na 2 SnO 3 modification is revealed. Li-rich manganese-based oxide (LRMO) is considered one of the most promising cathode materials for next-generation lithium-ion batteries due to its high energy density. However, many issues need to be addressed before its large-scale commercialization, including significant voltage decay and capacity fading. Herein, a Sn4+/Na+ co-doping induced integrated defect structure (oxygen vacancies, stacking faults, and surface spinel phase) strategy is proposed to suppress the voltage decay and enhance the cycling performance of LRMO. The integrated surface defect structures have significantly favorable effects on the LRMO, where the oxygen vacancies remove surface labile oxygen and suppress surface oxygen release, the induced stacking faults alleviate the stress accumulation during cycling, the surface spinel phase promotes the Li+ diffusion and prevents the outward migration of cations, and the co-doped Sn4+/Na+ stabilize the layered structure. As a result, the modified sample Na 2 SnO 3 -1 % (NSO-1) achieves excellent cycling performance (capacity of 207 mAh/g and capacity retention of 96.71 % after 100 cycles at 0.5C) and a smaller voltage decay (less than 1.5 mV per cycle) compared with the unmodified LRMO. This work provides a new valuable strategy to suppress capacity fading and voltage decay of LRMO through dual-element substitution induced surface defect engineering. [ABSTRACT FROM AUTHOR]

Skin flaps are tissue transferred from a donor to a recipient site to fill covering defects in the surface of the body. During transfer, skin flaps are severely predisposed to ischemia not only due to ischemia but also to ischemia--reperfusion (I/R) injury, a paradoxical exacerbation of cellular death following blood flow restoration in tissues exposed to ischemic insults. This systematic review aimed to report the in vivo outcomes of the application of stem cell-derived conditioned medium (secretome) or its derivatives toward skin flap following I/R injury in experimental studies. This study was a systematic review with literature searched using Science Direct, PubMed, Directory of Open Access Journal, Cochrane Central, Clinicaltrials.gov, and Europe PMC on January 24, 2024, for studies reporting the effects of stem cell-derived conditioned medium (secretome) or its derivatives in the skin flap I/R injury in animal models. We obtained a total of 318 studies during the search, which were then screened. Ten studies were included in the review. Our study found that stem cell-conditioned medium increases overall flap survivability; promotes vascularization, perfusion, and angiogenesis; reduces inflammation, reduces apoptosis and oxidants; and increases collagen secretion and maturation. The effect was found to be even more profound when the stem cells were set to proliferate under hypoxic conditions. Secretome did not only exhibit prosurvival and proproliferation properties suitable for responding to ischemic insults but also anti-inflammatory and antiapoptotic properties suitable for responding to I/R injury. Furthermore, secretome also assisted native structure recovery. The results from the experimental studies found that secretome is a promising therapy to increase flap survivability when also promoting histology recovery. [ABSTRACT FROM AUTHOR]

[Display omitted] Photocatalysts are one of the effective methods to degrade antibiotic contamination, but the efficiency is low and the toxicity is not well recognized. Deep lattice doping to induce defect generation is an effective way to improve the performance of photocatalysts. Here, defect-rich bromine-doped BiOCl-XBr photocatalysts were constructed with the help of small molecules inserted into the interlayer. The photocatalytic degradation performance of BiOCl-XBr was significantly enhanced, and its degradation rate was up to about 12 times that of BiOCl monomer. The main reasons for the stronger photocatalytic performance of BiOCl-XBr include Br doping to enhance visible light absorption, surface defects, and Bi valence changes to improve charge transport. The degradation of tetracycline (TC) produced more toxic intermediates, and the biotoxicity experiments also confirmed that the toxicity showed a trend of increasing and then decreasing, indicating that the more toxic intermediates were also mineralized during the degradation process. However, the mortality and hatching rate of zebrafish in the exposed group after degradation recovered but changed their activity pattern under light and dark conditions. This further warns us to focus on the toxicity changes after antibiotic degradation. Finally, based on the free radical analysis, the mechanism of photocatalytic degradation and detoxification of TC by BiOCl-XBr was proposed. [ABSTRACT FROM AUTHOR]

[Display omitted] Solar-driven photo-thermal dry reforming of methane (DRM) is an environmentally friendly production route for high-value-added chemicals. However, the lack of thorough understanding of the mechanism for photo-thermal reaction has limited its further development. Here, we systematically investigated the mechanism of photo-thermal DRM reaction with the representative of Ru/CeO 2 catalyst. Through in situ DRIFTs and transient experiments, comprehensive investigation into the reaction steps and their reactive sites in the process of DRM reaction were conducted. Besides, the excitation and migration direction of photo-electron was determined by ISI-XPS experiments, and the change of surface defect structure induced by light was characterized by ISI-EPR experiments. Based on the above results, the photo-enhancement effect on each micro-reaction step was determined. This study provides a theoretical basis for the industrialization of photo-thermal DRM reaction and its development of catalysts. [ABSTRACT FROM AUTHOR]

The surfaces of ceramic products are replete with numerous defects, such as those that appear during the diamond grinding of sintered SiAlON ceramics. The defective surface layer is the reason for the low effectiveness of TiZrN coatings under abrasive and fretting wear. An obvious solution is the removal of an up to 4-µm-thick surface layer containing the defects. It was proposed in the present study to etch the layer with fast argon atoms. At the atom energy of 5 keV and a 0.5 mA/cm2 current density, the ions were converted into fast atoms and the sputtering rate for the SiAlON samples reached 20 μm/h. No defects were observed in the microstructures of coatings deposited after beam treatment for half an hour. The treatment reduced the volumetric abrasive wear by five times. The fretting wear was reduced by three to four times.

State‐of‐the‐art inverted perovskite solar cells (PSCs) have exhibited considerable promise for commercialization due to their prospective stability. However, the intricate crystallization of halide perovskite, especially for multi‐component perovskites, not only distorts the surface lattice from its ideal form but also introduces numerous unsaturated dangling bonds to form surface defects, which can easily lead to reduced stability and poor performance. Herein, a surface lattice engineering is developed by coupling surface unsaturated ions and regulating ion bonding lengths/angles to achieve efficient and stable inverted PSCs. The renovated surface lattice not only eliminates shallow/deep level defects on the surface of perovskite, but also enhances photo/thermal stability of the materials. Moreover, the surface lattice engineering contributes to uniform potential surface, and improves energy‐level alignment at the interfaces of the perovskite and C60 carrier transport layer, enhancing charge carrier extraction and transportation. Finally, the champion PSC delivers an impressive efficiency of 25.82% (certified 25.5%). Moreover, these PSCs exhibit excellent operational stability, retaining 94% initial efficiency after more than ≈1 000h maximum power point test. [ABSTRACT FROM AUTHOR]

The YOLOv8 model has high detection efficiency and classification accuracy in detecting commutator surface defects, aimed at the problem of low working efficiency of a commutator, caused by commutator surface defects. First, the theoretical framework of Region-based Convolutional Neural Networks (R-CNN), spatial pyramid pooling (SPP)-net, Fast R-CNN, and Faster R-CNN is introduced, and the detection principle and process are described in detail. Secondly, the principle of the YOLOv8 network structure, head structure, neck structure, and C2f module are explained, and the loss function is described. The average precision of the proposed algorithm for detecting cracks and small points is more than 98%, and the frames per second (FPS) is 27. The detection results are mapped to the original image, and the visualization of the commutator surface defect detection is obtained, which has a higher robustness, accuracy, and real-time performance than the R-CNN, SPP-net, Fast R-CNN, and Faster R-CNN algorithms. [ABSTRACT FROM AUTHOR]

Plasmonic nanoantennas have attracted much attention lately, among other reasons because of the directionality of light emitted by fluorophores coupled to their localized surface plasmon resonances. Plasmonic picocavities, i.e., cavities with mode volumes below 1 nm3, could act as enhanced antennas due to their extreme field confinement, but the directionality on their emission is difficult to control. In this work, we show that the plasmonic picocavity formed between the tip of a scanning tunneling microscope and a metal surface with a monoatomic step shows directional emission profiles and, thus, can be considered as a realization of a picoantenna. Electromagnetic calculations demonstrate that the observed directionality arises from the reshaping and tilting of the surface charges induced at the scanning tip due to the atomic step. Our results pave the way to exploiting picoantennas as an efficient way for the far-field probing and control of light-matter interactions below the nanoscale. [ABSTRACT FROM AUTHOR]

Process parameter optimization and selection play a crucial role in additive manufacturing, particularly in determining the quality and characteristics of the final product. Among these parameters, the infill pattern holds significant importance as it directly influences the structural integrity, production time, and material usage efficiency of the printed object. This research focuses on identifying the most suitable 3D printing infill pattern process parameters for thermoplastic polyurethane (TPU) material, specifically for applications in pipeline construction. The criteria considered for process parameter selection include printing time, ultimate tensile strength, ultimate flexural strength, and surface defect minimization. Various infill patterns, including hexagonal, line, solid, triangle (35°), triangle (55°), and line patterns, are evaluated as alternatives. Utilizing the multi‐criteria decision‐making technique known as analytical hierarchy process (AHP), a systematic approach is employed to determine the optimal printing pattern. The findings of this study reveal that the hexagonal infill pattern outperforms other selected patterns in terms of meeting the criteria set forth for pipeline construction using TPU material. This research contributes to enhancing the efficiency and quality of additive manufacturing processes in pipeline applications, emphasizing the importance of informed parameter selection for achieving desired performance outcomes. [ABSTRACT FROM AUTHOR]

Clear cell renal cell carcinoma (ccRCC), a prevalent malignant tumor, exhibits resistance to chemotherapy, necessitating advanced therapeutic approaches. Sonocatalytic therapy has emerged as a promising non‐invasive treatment for solid tumors due to its ability to penetrate deep tissue. Herein, the development of single atomic Au‐doped 2D TiO2 nanosheets are presented with oxygen vacancies (Au‐SA/Def‐TiO2, ASDT) for sonocatalytic treatment of ccRCC. Surface defects on TiO2 nanosheets effectively stabilize Au single atomic sites via the Ti‐Au‐Ti structure, enhancing catalytic properties and facilitating reactive oxygen species (ROS) generation by reducing energy barriers and improving electron (e−) and hole (h+) separation. Additionally, ASDT exhibits peroxidase‐like activities, further augmenting ROS production, leading to significant inhibition of tumor growth in subcutaneous and orthotopic ccRCC models under ultrasound irradiation. This study underscores the efficacy of defect engineering for stabilizing single atoms to boost ROS production and achieve effective tumor eradication by the enhanced sonocatalytic effect. [ABSTRACT FROM AUTHOR]

Triple‐cation mixed‐halide (TCMH), i.e., (FAPbI3)1‐x‐y(MAPbBr3)y(CsPbI3)x, perovskite single‐crystal thin‐films (SCTFs) have emerged as candidates for high‐performance photodetectors. However, high lattice strain, surface defects, and the non‐ideal yellow phase such as δ‐FAPbI3 and δ‐CsPbI3, are impeding the realization of high‐quality TCMH SCTFs. Therefore, the synthesis of pure‐phase, high‐quality TCMH SCTFs with low lattice strain and defect density is imperative for enhancing light absorption and carrier mobility, thereby optimizing photoresponsivity. Herein, an innovative approach is proposed for synthesize TCMH SCTFs using an optimized space‐limited anti‐solvent assisted crystallization technique which employs 2‐methoxyethanol as the solvent and diethyl ether as anti‐solvent, devoid of thermal enhancement. A novel reducing additive, formic acid, is incorporated to mitigate phase separation, and the composition ratio is meticulously adjusted to regulate lattice strain. The results show that a pure‐phased optimal composition ratio (FA0.82MA0.11Cs0.07) SCTF with a low surface defect density (2.29 × 109 cm−2), low lattice strain (0.81%) and high hole mobility (77.58 cm−2 V−1 s−1) is successfully prepared. Moreover, the non‐integrated planar FA0.82MA0.11Cs0.07 SCTF photodetector also achieved a record photo‐responsivity (229.5 A W−1), and external quantum efficiency (5.4 × 104%), indicating its great potential in light‐detecting. This research paves the way for the development of high‐performance photodetectors via adjusting lattice strain and mitigating surface defects in TCMH SCTFs. [ABSTRACT FROM AUTHOR]

The utilization of device for the space explorations, the active material of the device must show resilience toward cosmos radiation. In this work, the radiation hardness of ZnGa2O4‐based deep ultra‐violet (DUV) photodetectors (PDs) is examined using γ‐ray irradiation. Responsivity of the photodetector at zero bias is found to improve from 0.98 to 1.94 mA W−1, the dark current increased from 0.11 to 5.6 pA, while photo‐to‐dark current ratio (PDCR) increased the from 3.2 × 103 to 3.1 × 104 and the photocurrent decay time improved from 220 to 190 ms. The high‐resolution X‐ray photoelectron spectra (HR‐XPS) of O 1s core level peak is deconvoluted into two main peaks namely, O(I) and O(II), where the lattice oxygen of ZnGa2O4 is identified by the O(I) peak, while its surface oxygen defect is represented by O(II). A clear increment is observed in the percentage of oxygen defect peak, O(II), from 6.82 to 53.19% after 200 kGy. Also, the device remains undeteriorated after 200 kGy irradiation, indicating it to be a radiation‐hard device. These characteristics allow ZnGa2O4 DUV PDs to function effectively in cosmic radiation environments with the capability to operate on zero‐bias, regardless of the γ‐radiation. [ABSTRACT FROM AUTHOR]

The surface defect detection of magnetic blocks faces challenges such as low accuracy, high missed detection rates, and weak anti-interference capabilities. Additionally, existing models are often large in size and require significant computational resources. To address these issues, this article integrated the Yolov8 framework and designed the RCYOLO model to improve detection performance and resource utilization. Firstly, we used RevCol as the backbone, and explored its optimal number of sub-networks to reduce model parameters and complexity, as well as improve model robustness. Secondly, we removed some deep structures from Yolov8s to simplify the model, making it easier to deploy. Afterwards, we developed a more efficient feature extraction module, C2f_SA, and replaced all existing modules with it to compensate for accuracy loss caused by simplification and improve overall detection performance. Finally, we optimized reg_max to explore the best minimum value for detecting defects in magnetic blocks to reduce unnecessary computational burden. Experimental results show that compared to Yolov8s, although RCYOLO’s mAP0.5 was reduced by 0.2%, it significantly reduced the model parameters, FLOPs, and model size by 51.64%, 30.31%, and 50.22%, respectively, achieving a better balance between accuracy and resources. Moreover, RCYOLO demonstrated good detection performance compared to other improved models. [ABSTRACT FROM AUTHOR]

In the commercial development of perovskite solar cells, the main challenge lies in achieving efficient devices with high stability. Additive engineering in polycrystalline perovskites is considered as an effective approach to address this challenge by passivating surface defects and reducing carrier losses associated with these defects. In this work, the passivation effect of molecules with different side chain groups on perovskites and the role of binding energy in mitigating carrier loss are studied. The findings reveal that the thiophene group is particularly effective in passivating defects and enhancing hole transport. Consequently, devices treated with 2‐thienylmethylamine hydrochloride (TMAC) demonstrate a champion power conversion efficiency (PCE) of 24.63%. Furthermore, these TMAC‐treated devices exhibit remarkable stability, maintaining over 93.13% of their initial efficiencies after 1200 h of continuous illumination under maximum power point tracking (MPPT). This research presents a pathway to enhance the optoelectronic performance and stability of perovskite solar cells. [ABSTRACT FROM AUTHOR]

All‐inorganic cesium lead halide flexible perovskite solar cells (f‐PSCs) exhibit superior thermal stability compared to their organic‐inorganic hybrid counterparts. However, their flexibility and efficiency are still below‐par for practical viability. This study presents an approach involving the introduction of multifunctional molecule ammonium benzenesulfonate (ABS) to selectively etch 0D‐Cs4Pb(IBr)6 from the mixed‐dimensional perovskite film surface, to attain more contact area between the perovskite and hole transport layer for improved hole extraction and transport. It is found that the ABS molecules bind to the perovskite lattice surface via O atoms and NH4+, effectively passivating surface defects and enhancing phase stability. The hydrophobic nature of the benzene ring in ABS further contributes to operational stability, leading to high cell efficiency of 15.00%, accompanied by enhanced operational stability. Even after undergoing 60 000 flexing cycles at a curvature radius of 5 mm, the ABS‐treated f‐PSC still retains over 98.5% of its initial efficiency. This multifunctional strategy for modifying typical mixed‐dimensional perovskite compositions significantly enhances the photovoltaic performance and stability of flexible all‐inorganic f‐PSCs. [ABSTRACT FROM AUTHOR]

Curved ceramic materials possess corrosion-resistant, heat-resistant, and exceptional hardness, rendering them indispensable in many critical fields, including automotive, aerospace, biomedical, architectural, and artistic applications. The detection of defects in these materials is of paramount importance; but traditional inspection methods fall short due to their unique structural characteristics. Presently, the assessment of curved ceramics predominantly relies on manual inspection, which is fraught with subjective errors and inefficiencies. This paper provides a comprehensive overview of the advancements in machine vision technology as applied to defect detection across various types of curved ceramic materials, including industrial, daily-use, and artistic ceramics. The paper highlights the key factors influencing the development of surface defect detection technology in curved ceramics. It summarises the advantages and disadvantages of traditional machine vision and deep learning approaches for defect detection in curved ceramics and analyzes their respective application scopes. Concluding with an examination of the technical challenges inherent in defect detection, the paper also outlines a prospective trajectory for the advancement of inspection technology in curved ceramic materials. [ABSTRACT FROM AUTHOR]