Defects In Materials Research Articles

Proton-exchange induced reactivity in layered oxides for lithium-ion batteries.

LiNixCoyMn1-x-yO2 (0 < x, y < 1, NCM) is the dominant positive material for the state-of-the-art lithium-ion batteries. However, the sensitivity of NCM materials to moisture makes their manufacturing, storage, transportation, electrode processing and recycling complicated. Although it is recognized that protons play a critical role in their structure stability and performance, proton exchange with Li+ in NCM materials has not been well understood. Here, we employ advanced characterizations and computational studies to elucidate how protons intercalate into the layered structure of NCM, leading to the leaching of Li+ and the formation of protonated NCM. It is found that protonation facilitates cation rearrangement and formation of impurity phases in NCM, significantly deteriorating structural stability. The adverse effects induced by protons become increasingly pronounced with a higher Ni content in NCM. Through a comprehensive investigation into the thermodynamics and kinetics of protonation, we discover that Li deficiencies in NCM materials can be resolved via solution process in the presence of Li+ ions and controlled proton concentration. The underlying mechanism of relithiation is further explored through materials characterizations and kinetics modeling. This work provides crucial insights into controlling structural and compositional defects of Li-ion battery positive material in complicated processing environment.

Impact of submicron Nb3Sn stoichiometric surface defects on high-field superconducting radiofrequency cavity performance

Nb3Sn film coatings have the potential to drastically improve the accelerating performance of Nb superconducting radiofrequency (SRF) cavities in next-generation linear particle accelerators. Unfortunately, persistent Nb3Sn stoichiometric material defects formed during fabrication limit the cryogenic operating temperature and accelerating gradient by nucleating magnetic vortices that lead to premature cavity quenching. The SRF community currently lacks a predictive model that can explain the impact of chemical and morphological properties of Nb3Sn defects on vortex nucleation and maximum accelerating gradients. Both experimental and theoretical studies of the material and superconducting properties of the first 100 nm of Nb3Sn surfaces are complicated by significant variations in the volume distribution and topography of stoichiometric defects. This work contains a coordinated experimental study with supporting simulations to identify how the observed chemical composition and morphology of certain Sn-rich and Sn-deficient surface defects can impact the SRF performance. Nb3Sn films were prepared with varying degrees of stoichiometric defects, and the film surface morphologies were characterized. Both Sn-rich and Sn-deficient regions were identified in these samples. For Sn-rich defects, we focus on elemental Sn islands that are partially embedded into the Nb3Sn film. Using finite element simulations of the time-dependent Ginzburg-Landau equations, we estimate vortex nucleation field thresholds at Sn islands of varying size, geometry, and embedment. We find that these islands can lead to significant SRF performance degradation that could not have been predicted from the ensemble stoichiometry alone. For Sn-deficient Nb3Sn surfaces, we experimentally identify a periodic nanoscale surface corrugation that likely forms because of extensive Sn loss from the surface. Simulation results show that the surface corrugations contribute to the already substantial drop in the vortex nucleation field of Sn-deficient Nb3Sn surfaces. This work provides a systematic approach for future studies to further detail the relationship between experimental Nb3Sn growth conditions, stoichiometric defects, geometry, and vortex nucleation. These findings have technical implications that will help guide improvements to Nb3Sn fabrication procedures. Our outlined experiment-informed theoretical methods can assist future studies in making additional key insights about Nb3Sn stoichiometric defects that will help build the next generation of SRF cavities and support related superconducting materials development efforts. Published by the American Physical Society 2024

A numerical investigation of the structural behavior of reinforced concrete beams fully or partially encased with UHPC layers in flexure

Weakness in the structural facilities appears due to design faults, poor construction, usage change, maintenance lack, material defects, and environmental conditions. Therefore, strengthening structures becomes necessary for deteriorated concrete and enhancing aging concrete elements to achieve satisfactory performance perfectly. This study numerically investigated the structural behavior of conventional concrete beams reinforced with Ultra-High Performance Concrete (UHPC) layers on different sides. The arrangement of UHPC layers, bonding method between traditional concrete and UHPC, layer thickness, and reinforcement ratio were examined using Abaqus software. The interface between the UHPC layer and conventional concrete sustains compressive, tensile, and shear stresses, which cause weak resistance to the stresses at the contact surfaces. Therefore, the simulation of contact face in Abaqus needs a proper numerical model relying on practical methods. However, using the bonding models available in Abaqus is crucial for reaching logical results comparable to the practical ones. The practical bonding approaches are highly consequential, such as roughening surfaces by sandblasting to attain a firm connection between the contact surfaces, which permits using a surface-based tie constraint for simulation. Further, epoxy resin conducts as a thin coating between contact surfaces, making it possible to simulate via a cohesive surface. The results proved that increasing the area encased by the UHPC layer improves load capacity further and reduces the deflection at the maximum load. Surrounding the beam on whole sides with a UHPC raises load capacity by 108 % and reduces deflection by 46 %. Adding a UHPC layer to the beam delays crack initiation and reduces their number and spacing. Increasing the UHPC layer thickness or reinforcement ratio enhances the load capacity of the beam at cracking and the ultimate state.

Zr-Doping Strategy of High-Quality Cu2O/β-Ga2O3 Heterojunction for Ultrahigh-Performance Solar-Blind Ultraviolet Photodetection.

β-Ga2O3, as an ultrawide band gap semiconductor, has emerged as the most promising candidate in solar-blind photodetectors. The practical application of β-Ga2O3, however, suffers from intrinsic defects and suboptimal crystal quality within the devices. In this work, high-quality β-Ga2O3 was successfully synthesized by employing the Zr-doping strategy, which has facilitated the development of ultrahigh-performance solar-blind photodetectors based on Cu2O/β-Ga2O3 heterostructures. Structural analyses indicate that the strong Zr-O covalent bond effectively stabilizes the material, thereby eliminating oxygen vacancy defects. The Cu2O/β-Ga2O3 heterostructure photodetector demonstrates an ultrahigh responsivity and detectivity coupled with an external quantum efficiency. Furthermore, the device exhibits a photocurrent-to-dark current ratio of 3 × 105, showcasing its superior capability in detecting low-intensity deep ultraviolet signals, markedly surpassing previous heterostructure ultraviolet photodetectors. These exceptional performances are attributed to the effective elimination of oxygen vacancy defects in β-Ga2O3 and the variation of band alignment at the interface, which facilitate rapid separation of photogenerated electron-hole pairs under reverse bias. This study not only provides an enhanced and easy route to mitigate oxygen vacancy defects in oxide materials but also propels further exploration into the next generation of flexible, high-performance, solar-blind ultraviolet photodetectors.

Functionalization Strategies of Iron Sulfides for High-Performance Supercapacitors

AbstractSupercapacitors have emerged as a promising class of energy storage technologies, renowned for their impressive specific capacities and reliable cycling performance. These attributes are increasingly significant amid the growing environmental challenges stemming from rapid global economic growth and increased fossil fuel consumption. The electrochemical performance of supercapacitors largely depends on the properties of the electrode materials used. Among these, iron-based sulfide (IBS) materials have attracted significant attention for use as anode materials owing to their high specific capacity, eco-friendliness, and cost-effectiveness. Despite these advantages, IBS electrode materials often face challenges such as poor electrical conductivity, compromised chemical stability, and large volume changes during charge–discharge cycles. This review article comprehensively examines recent research efforts aiming at improving the performance of IBS materials, focusing on three main approaches: nanostructure design (including 0D nanoparticles, 1D nanowires, 2D nanosheets, and 3D structures), composite development (including carbonaceous materials, metal compounds, and polymers), and material defect engineering (through doping and vacancy introduction). The article sheds light on novel concepts and methodologies designed to address the inherent limitations of IBS electrode materials in supercapacitors. These conceptual frameworks and strategic interventions are expected to be applied to other nanomaterials, driving advancements in electrochemical energy conversion.

Unveiling sulfur vacancy pairs as bright and stable color centers in monolayer WS2

Color centers, arising from zero-dimensional defects, exploit quantum confinement to access internal electron quantum degrees of freedom, holding potential for quantum technologies. Despite intensive research, the structural origin of many color centers remains elusive. In this study, we employ in-situ cathodoluminescence scanning transmission electron microscopy combined with integrated differential phase contrast imaging to examine how defect configuration in tungsten sulfide determines color-center emission. Using an 80-kV accelerated electron beam, defects were deliberately produced, visualized, excited in situ and characterized in real time in monolayer WS2 within hBN|WS2 | hBN heterostructures at 100 K. These color centers were simultaneously measured by cathodoluminescence microscopy and differentiated by machine learning. Supported by DFT calculations, our results identified a crucial sulfur vacancy configuration organized into featured vacancy pairs, generating stable and bright luminescence at 660 nm. These findings elucidate the atomic-level structure-exciton relationship of color centers, advancing our understanding and quantum applications of defects in 2D materials.

Achieving Over 10% Efficiency in Kesterite Solar Cells via Selenium-Free Annealing

The unsatisfactory crystalline quality of the absorber layer has seriously impeded the development of kesterite photovoltaic devices, including a small grain size, a typical multi-layer structure, and inherent defects and defect clusters. Herein, we simultaneously modify the nature of the absorber bulk and the heterojunction interface by sputtering quaternary alloy targets and subsequent selenium-free annealing to improve the photovoltaic performance of Cu2ZnSnSe4 (CZTSe) solar cells. By adjusting the sputtering power, the elemental content and distribution in the precursor film are effectively controlled, which helps to obtain a single-layer large grain CZTSe absorber layer with better homogenization and compactness. The harmful inherent defects are significantly suppressed by such a modification. Simultaneously, the widened depletion width and enhanced built-in electric field, as well as improved band alignment at the heterojunction, enhance carrier collection. As a consequence, the efficiency of CZTSe solar cells has improved greatly from 6.91% to 10.12%. The single-target preparation strategy without selenization provides a simple and novel perspective for simultaneously adjusting the morphology and defects of kesterite photovoltaic materials, paving the way for promoting innovative industrial applications.

Trace benzene capture by decoration of structural defects in metal-organic framework materials.

Capture of trace benzene is an important and challenging task. Metal-organic framework materials are promising sorbents for a variety of gases, but their limited capacity towards benzene at low concentration remains unresolved. Here we report the adsorption of trace benzene by decorating a structural defect in MIL-125-defect with single-atom metal centres to afford MIL-125-X (X = Mn, Fe, Co, Ni, Cu, Zn; MIL-125, Ti8O8(OH)4(BDC)6 where H2BDC is 1,4-benzenedicarboxylic acid). At 298 K, MIL-125-Zn exhibits a benzene uptake of 7.63 mmol g-1 at 1.2 mbar and 5.33 mmol g-1 at 0.12 mbar, and breakthrough experiments confirm the removal of trace benzene (from 5 to <0.5 ppm) from air (up to 111,000 min g-1 of metal-organic framework), even after exposure to moisture. The binding of benzene to the defect and open Zn(II) sites at low pressure has been visualized by diffraction, scattering and spectroscopy. This work highlights the importance of fine-tuning pore chemistry for designing adsorbents for the removal of air pollutants.

Detecting and evaluating surface defects in additive manufacturing composite materials via image processing technique

Purpose This study aims to offer an image-based robust edge detection system that can estimate, identify, locate and label surface flaws during manufacturing for real-time surface issue diagnostics. Of great concern, this methodology extrapolates surface defect information from scanning electron microscopy (SEM) images of composite fracture surfaces. This study predicts changes in topological intensity of composite fracture surfaces and display them as real-time surface intensity values for the first time. Design/methodology/approach This work, however, introduces a novel robust edge detection method – based image processing – as it is shown to be effective in locating defects, as measured by SEM images of composite fracture surfaces created using additive manufacturing (AM). SEM images, obtained in this study, are related to previous study considering the fracture surfaces of reinforced thermoset composites created via the AM method. These SEM images are of two types: fracture surface of AM of carbon fiber reinforced thermoset composites and fracture surface of AM of syntactic foam reinforced thermoset composites. Initially, MATLAB environment is used for analyzing the SEM images; the technique used, as well as the validity are explained more in the methodology section. Findings The robust surface defect inspection approach used herein is found to be capable of predicting, identifying, localizing and labeling surface defects during production, allowing for real-time surface issue diagnosis. Further, this work makes it possible to use image processing and analysis of these surfaces to anticipate fluctuations in the topological intensity of the fracture surfaces of composites and represent them as values of surface intensity in real time. Originality/value Rising worldwide company rivalry requires a fast, accurate component failure diagnostic method. To create an efficient feature set, a surface defect inspection system must identify product flaws in real time. Thus, this study proposed an image-based robust edge detection system – based on MATLAB environment – that is capable of estimating, identifying, locating and labeling surface faults during production. This paves the way for an extensive set of high-quality tools for dealing with a wide range of problems associated with digital image processing in composites. As a result, the ability to define methodologies and rapidly prototype prospective solutions typically minimizes the cost and time required to implement a successful system during the design phase of an image processing system.

Enabling quantitative analysis of in situ TEM experiments: A high-throughput, deep learning-based approach tailored to the dynamics of dislocations

In situ TEM is by far the most commonly used microscopy method for imaging dislocations, i.e., line-like defects in crystalline materials. However, quantitative image analysis so far was not possible, implying that also statistical analyses were strongly limited. In this work, we created a deep learning-based digital twin of an in situ TEM straining experiment, additionally allowing to perform matching simulations. As application we extract spatio-temporal information of moving dislocations from experiments carried out on a Cantor high entropy alloy and investigate the universality class of plastic strain avalanches. We can directly observe “stick–slip motion” of single dislocations and compute the corresponding avalanche statistics. The distributions turn out to be scale-free, and the exponent of the power law distribution exhibits independence on the driving stress. The introduced methodology is entirely generic and has the potential to turn meso-scale TEM microscopy into a truly quantitative and reproducible approach.

Analysis of quality control in clothing production using SQC (Statistical Quality Control) and 5W+1H methods

CV Tujuh Pusaka Tala is a start-up company engaged in the clothing and sports jersey convection industry, as well as marching band musical instruments known by the brands 7MJR Store for clothing and SevenMajor for marching band musical instruments. This study was conducted to analyze the quality control of clothing production at CV. Tujuh Pusaka Tala using the Statistical Quality Control (SQC) method and the 5W and 1H approach to minimize defective products. The SQC methods used include Checksheet, Control Map, Histogram, Pareto Diagram and Cause and Effect Diagram to identify and control variability in the production process. While the 5W and 1H approach is applied to understand the main causes of product defects and find the right solution. The results of the study showed that there were 4 types of defects in the production process at CV. Tujuh Pusaka Tala, namely printing defects, screen printing defects, stitching, and material defects. The main factors causing production defects include humans, materials, machines, methods, and the environment. It can be concluded that the quality control of clothing production at CV. Tujuh Pusaka Tala using the Statistical Quality Control (SQC) method and the 5W and 1H approach to minimize defective products has been implemented well so that it can minimize the existence of defective products.

The Impact of Biowaste Composition and Activated Carbon Structure on the Electrochemical Performance of Supercapacitors.

The increasing demand for sustainable and efficient energy storage materials has led to significant research into utilizing waste biomass for producing activated carbons. This study investigates the impact of the structural properties of activated carbons derived from various lignocellulosic biomasses-barley straw, wheat straw, and wheat bran-on the electrochemical performance of supercapacitors. The Fourier Transform Infrared (FTIR) spectroscopy analysis reveals the presence of key functional groups and their transformations during carbonization and activation processes. The Raman spectra provide detailed insights into the structural features and defects in the carbon materials. The electrochemical tests indicate that the activated carbon's specific capacitance and energy density are influenced by the biomass source. It is shown that the wheat-bran-based electrodes exhibit the highest performance. This research demonstrates the potential of waste-biomass-derived activated carbons as high-performance materials for energy storage applications, contributing to sustainable and efficient supercapacitor development.

Experimental investigations of chemo-mechanical magneto-rheological finishing of Al-6061 via composite magnetic abrasive

ABSTRACT To achieve flawless soft material surfaces, defects and irregularities must be eliminated. Traditional abrasive-mixing techniques frequently produce surface flaws as a result of abrasive embrittlement, resulting in poor surface-quality. As a result, ensuring an immaculate finish is critical for these surfaces. In contrast, the chemo-mechanical magneto-rheological finishing (CMMRF) process, which employs a composite magnetic abrasive (CMA)-based smart fluid, has proven to be extremely effective at producing nano-finished surfaces. This study used a central-composite-rotatable design (CCRD) based on response surface methodology (RSM) to analyze how CMAs variables, slurry-based parameters, and polishing time affect final surface roughness (R a ) and percentage change in roughness (%∆R a ) for Al-6061. The CMMRF process resulted in a superior Al-surface finish (R a ) of 29 nm and a %∆R a of 91.23%. Statistical models predicted R a and %∆R a values, which matched experimental results. Characterization tests on the final Al-surface revealed significant reduction in initial machining scratches and valleys, resulting in a superior mirror-polished surface via CMA-based polishing.

Effect of graphene on absorption spectrum of Si/SiO2 multilayer

In recent decades, photonic crystals have emerged as a key technology in several fields, including light management, photovoltaics, detection, and lasing. This success can be attributed to the ability to regulate electromagnetic waves, which can be achieved by, through a variety of techniques, disruption the periodicity of crystals. In this study, the introduction of graphene as a material defect in a one-dimensional photonic crystal consisting of six Si/SiO2 patterns is subjected to investigation. The calculations are performed using the transfer matrix method, with the experimental data serving as the input, following a protocol that involves exploring the variation of the absorption spectra as a function of the parameters of the material system and the incident electromagnetic wave. The findings illustrate that the absorption peak exhibits a pronounced dependency on the positioning of the material defect, the graphene layer thickness, and the incident angle. This paves the way for a more detailed inquiry into its potential utility in the domain of detection.

Narrowband Electroluminescence from Color Centers in Hexagonal Boron Nitride.

Defects in wide bandgap materials have emerged as promising candidates for solid-state quantum optical technologies. Electrical excitation of single emitters may lead to scalable on-chip devices and therefore is highly sought after. However, most wide bandgap materials are not amenable to efficient doping, posing challenges for electrical excitation and on-chip integration. Here, we demonstrate narrowband electroluminescence from visible and near-infrared color centers in hexagonal boron nitride (hBN). We harness van der Waals tunnel junctions of graphene-hBN-graphene. Charge carriers are electrically injected into hBN, exciting localized defects that emit nonclassical light, as characterized by the second order correlation measurement. Remarkably, the devices operate at room temperature and produce robust, narrowband emission spanning from visible to the near-infrared. Our work marks an important milestone in vdW materials and their promising attributes for integrated quantum technologies and on-chip photonic circuits.

Study on the mechanism of laser-induced breakdown and damage performance of internal defects in transparent materials through local optical field modulation

This paper establishes a photothermal damage model for bubble impurities affecting laser optical field modulation based on Mie scattering theory and incorporates the effects of optical field modulation. This model elucidates the evolution mechanism of synergistic damage in fused silica, with simulation results validated through experimental verification. A novel characterization of optical breakdown due to bubble impurities is proposed, occurring on a millisecond timescale through the dynamic evolution of combustion waves. The model delineates the influence of bubble size and spacing on optical field distribution, temperature, stress distribution, and their evolutionary behaviors. The modulation of the optical field due to double bubble impurities creates a localized “hot spot,” resulting in a differential transverse contraction stress at the edges of the bubble impurities, thereby reducing the damage threshold of fused silica. The spacing of 1.1 λ represents the enhancement node for optical field modulation by double bubble impurities. Furthermore, localized oscillations in the optical field arise when the spacing between the double bubbles exceeds 1.1 λ, attributed to changes in the refractive index at the bubble defects and resonance oscillations generated by optical field modulation. This study not only enhances our understanding of the optical field modulation processes occurring at 1064 nm in the presence of bubble defects but also establishes a theoretical foundation for detecting internal defects at this wavelength without inducing surface damage.

Positron annihilation spectroscopy guided by two-component density functional theory calculations distinguishes irradiation-induced vacancy type in 4H-SiC

Based on two-component density functional theory integrated with the projector augmented-wave basis and incorporating both calculated and experimental data from Positron Annihilation Spectroscopy (PAS), this study introduces a novel method for identifying and analyzing specific types of vacancies when multiple types of vacancies are coexisting. This method was then tested on 4H-SiC irradiated by 300 keV C4+ ion beams. By calculating charge density to analyze positron annihilation lifetime spectroscopy and calculating wave functions to analyze slow positron-beam Doppler broadening spectroscopy, for the first time, silicon monovacancies (VSi) and carbon monovacancies (VC) in irradiated 4H-SiC were quantitatively detected separately, allowing them to be distinguished with high accuracy. In addition, a decreasing trend in the relative percentage of VC with increasing irradiation dose, consistent with that expected when irradiating with carbon ions, was also observed, illustrating both the effectiveness and potential of this method for broader applications in material defect analysis. This study not only addresses the challenges of identifying multiple coexisting vacancy types using PAS but also extends the applicability and depth of PAS in fields such as nuclear energy, aerospace, and semiconductors.

Enhancing insulating properties of glass-fiber reinforced polymers using plasma fluorination-modified boron nitride nanosheets

The insulation failure of glass fiber-reinforced polymers (GFRP) limits their use in high-voltage insulation fields. In this study, boron nitride nanosheets (BNNS) were prepared using ball-milling and further fluorinated via dielectric barrier discharge (DBD) plasma treatment. The GFRP nanocomposites were fabricated using different filler types and doping concentrations. The test results indicated that fluorinated BNNS (F-BNNS) displays good dispersion and interfacial compatibility, enhances the interfacial bonding strength of the “fiber-matrix-filler” ternary system in GFRP, and reduces the internal defects of materials. In addition, the insulating properties of the composites were related to the filler concentration. Adding a trace amount of F-BNNSs increased the flashover and breakdown voltages of the GFRP by up to 28.77% and 21.62%, respectively. The results of molecular dynamics simulations and trap distribution calculations showed that plasma fluorination of BNNS increases the bandgap and deep trap energy level at the interface. The extremely strong charge-binding ability of the deep traps inhibits continuous charge injection and regulates carrier migration, which improves the insulating properties of the composites. The results of this study provide a novel, environmentally friendly, and efficient solution for improving the insulating properties of GFRP.

Determination of the geometric parameters of the defects based on the tomographically obtained data and their influence on the fatigue behavior of the S960 with laser cladded protective layers

This article deals with identifying defects of layered high strength steel materials with the help of tomography measurement. Test samples were made of S960 High Strength Steel to which layers of either aluminium bronze, hardchrome, cobalt alloy or stainless steel were applied by a laser cladding technology. The experimental campaign included a study of morphometric parameters of internal defects in and near the bi-material interface region using X-ray micro-tomography and their potential influence on the fatigue behavior during a three-point bending test.

Effects of triflute pin geometry on defect formation and material flow in FSW using CEL approach

Complicated tool pin designs in Friction Stir Welding (FSW) need to be considered in terms of material flow and defect formation. This study investigates the effects of the triflute tool's geometrical parameters on temperature, strain, void formation, and material mixing using a numerical method. The numerical model employs a coupled Eulerian-Lagrangian (CEL) formulation and successfully predicts void formation and material mixing during friction stir welding (FSW). Four tool pin designs are considered for material flow, including one cylindrical pin and three triflute pins with flute radii of 1 mm, 1.5 mm, and 2 mm. The findings indicate that the stir zone is divided into shoulder-driven and pin-driven zones, each exhibiting distinct material flow patterns. In the shoulder-driven zone, material flow toward the advancing side is dominant, while in the pin-driven zone, it flows toward the retreating side. Flutes on the FSW pin tool increase the sweeping rate, strain, and material movement in the stir zone. However, flutes with a larger radius sweep a greater amount of material and thus require more softened material to facilitate movement. Therefore, for defect-free joint formation, a higher rotational speed of the tool will be required, which may adversely affect tool lifespan and joint mechanical properties. The effectiveness of flutes with a smaller radius of 1 mm is significantly greater than that of those with a larger radius (1.5 or 2 mm) in enhancing material flow and achieving defect-free welding.