Enhancing the Performance of Perovskite Light-Emitting Diodes via Synergistic Effect of Defect Passivation and Dielectric Screening

Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the presence of defects within these perovskites has a substantial influence on the emission efficiency and durability of the devices.In this study,we revealed a synergistic passivation mechanism on perovskite films by using a dual-functional compound of potassium bromide.The dual functional potassium bromide on the one hand can passivate the defects of halide vacancies with bromine anions and,on the other hand,can screen the charged defects at the grain boundaries with potassium cations.This approach effectively reduces the probability of carriers quenching resulting from charged defects capture and consequently enhances the radiative recombination efficiency of perovskite thin films,leading to a significant enhancement of photoluminescence quantum yield to near-unity values(95%).Meanwhile,the potassium bromide treatment promoted the growth of homogeneous and smooth film,facilitating the charge carrier injection in the devices.Consequently,the perovskite light-emitting diodes based on this strategy achieve a maximum external quantum efficiency of~21%and maximum luminance of~60,000 cd m^(-2).This work provides a deeper insight into the passivation mechanism of ionic compound additives in perovskite with the solution method.

Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information

Probabilistic back-analysis is an important means to infer the statistics of uncertain soil parameters,making the slope reliability assessment closer to the engineering reality.However,multi-source information(including test data,monitored data,field observation and slope survival records)is rarely used in current probabilistic back-analysis.Conducting the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction under rainfalls by integrating multi-source information is a challenging task since thousands of random variables and high-dimensional likelihood function are usually involved.In this paper,a framework by integrating a modified Bayesian Updating with Subset simulation(mBUS)method with adaptive Conditional Sampling(aCS)algorithm is established for the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction.Within this framework,the high-dimensional probabilistic back-analysis problem can be easily tackled,and the multi-source information(e.g.monitored pressure heads and slope survival records)can be fully used in the back-analysis.A real Taoyuan landslide case in Taiwan,China is investigated to illustrate the effectiveness and performance of the established framework.The findings show that the posterior knowledge of soil parameters obtained from the established framework is in good agreement with the field observations.Furthermore,the updated knowledge of soil parameters can be utilized to reliably predict the occurrence probability of a landslide caused by the heavy rainfall event on September 12,2004 or forecast the potential landslides under future rainfalls in the Fuhsing District of Taoyuan City,Taiwan,China.

In-situ interfacial passivation and self-adaptability synergistically stabilizing all-solid-state lithium metal batteries

The function of solid electrolytes and the composition of solid electrolyte interphase(SEI)are highly significant for inhibiting the growth of Li dendrites.Herein,we report an in-situ interfacial passivation combined with self-adaptability strategy to reinforce Li_(0.33)La_(0.557)TiO_(3)(LLTO)-based solid-state batteries.Specifically,a functional SEI enriched with LiF/Li_(3)PO_(4) is formed by in-situ electrochemical conversion,which is greatly beneficial to improving interface compatibility and enhancing ion transport.While the polarized dielectric BaTiO_(3)-polyamic acid(BTO-PAA,BP)film greatly improves the Li-ion transport kinetics and homogenizes the Li deposition.As expected,the resulting electrolyte offers considerable ionic conductivity at room temperature(4.3 x 10~(-4)S cm^(-1))and appreciable electrochemical decomposition voltage(5.23 V)after electrochemical passivation.For Li-LiFePO_(4) batteries,it shows a high specific capacity of 153 mA h g^(-1)at 0.2C after 100 cycles and a long-term durability of 115 mA h g^(-1)at 1.0 C after 800 cycles.Additionally,a stable Li plating/stripping can be achieved for more than 900 h at 0.5 mA cm^(-2).The stabilization mechanisms are elucidated by ex-situ XRD,ex-situ XPS,and ex-situ FTIR techniques,and the corresponding results reveal that the interfacial passivation combined with polarization effect is an effective strategy for improving the electrochemical performance.The present study provides a deeper insight into the dynamic adjustment of electrode-electrolyte interfacial for solid-state lithium batteries.

System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

Belief reliability:a scientific exploration of reliability engineering

This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.

Interrater Reliability Estimation via Maximum Likelihood for Gwet’s Chance Agreement Model

Interrater reliability (IRR) statistics, like Cohen’s kappa, measure agreement between raters beyond what is expected by chance when classifying items into categories. While Cohen’s kappa has been widely used, it has several limitations, prompting development of Gwet’s agreement statistic, an alternative “kappa”statistic which models chance agreement via an “occasional guessing” model. However, we show that Gwet’s formula for estimating the proportion of agreement due to chance is itself biased for intermediate levels of agreement, despite overcoming limitations of Cohen’s kappa at high and low agreement levels. We derive a maximum likelihood estimator for the occasional guessing model that yields an unbiased estimator of the IRR, which we call the maximum likelihood kappa (κML). The key result is that the chance agreement probability under the occasional guessing model is simply equal to the observed rate of disagreement between raters. The κMLstatistic provides a theoretically principled approach to quantifying IRR that addresses limitations of previous κcoefficients. Given the widespread use of IRR measures, having an unbiased estimator is important for reliable inference across domains where rater judgments are analyzed.

Bifunctional passivation by lewis-base molecules for efficient printable mesoscopic perovskite solar cells

Printable mesoscopic perovskite solar cells(PM-PSCs)possess notable merits in terms of cost-effectiveness,easy manufacturing,and large scale applications.Nevertheless,the absence of a hole transport layer contributes to the exacerbation of carrier recombination,and the defects between the perovskite and electron transport layer(ETL)interfaces significantly decrease the efficiency of the devices.In this study,a bifunctional surface passivation approach is proposed by applying a thioacetamide(TAA)surfactant on the mesoporous TiO_(2)interface.The results demonstrate that TAA molecules could interact with TiO_(2),thereby diminishing the oxygen vacancy defects.Additionally,the amino group and sulfur atoms in TAA molecules act as Lewis base to effectively passivate the uncoordinated Pb^(2+)in perovskite and improve the morphology of perovskite,and decrease the trap-state density of perovskite.The TAA passivation mechanism improves the alignment of energy levels between TiO_(2)and perovskite,facilitating electron transport and reducing carrier recombination.Consequently,the TAA-passivated device achieved a champion power conversion efficiency(PCE)of 17.86%with a high fill factor(FF)of 79.16%and an open-circuit voltage(V_(OC))of 0.971 V.This investigation presents a feasible strategy for interfacial passivation of the ETL to further improve the efficiency of PM-PSCs.

Constructing Al@C-Sn pellet anode without passivation layer for lithium-ion battery

Al is considered as a promising lithium-ion battery(LIBs)anode materials owing to its high theoretical capacity and appropri-ate lithation/de-lithation potential.Unfortunately,its inevitable volume expansion causes the electrode structure instability,leading to poor cyclic stability.What’s worse,the natural Al2O3 layer on commercial Al pellets is always existed as a robust insulating barrier for elec-trons,which brings the voltage dip and results in low reversible capacity.Herein,this work synthesized core-shell Al@C-Sn pellets for LIBs by a plus-minus strategy.In this proposal,the natural Al2O3 passivation layer is eliminated when annealing the pre-introduced SnCl2,meanwhile,polydopamine-derived carbon is introduced as dual functional shell to liberate the fresh Al core from re-oxidization and alle-viate the volume swellings.Benefiting from the addition of C-Sn shell and the elimination of the Al2O3 passivation layer,the as-prepared Al@C-Sn pellet electrode exhibits little voltage dip and delivers a reversible capacity of 1018.7 mAh·g^(-1) at 0.1 A·g^(-1) and 295.0 mAh·g^(-1) at 2.0 A·g^(-1)(after 1000 cycles),respectively.Moreover,its diffusion-controlled capacity is muchly improved compared to those of its counterparts,confirming the well-designed nanostructure contributes to the rapid Li-ion diffusion and further enhances the lithium storage activity.

Hybrid response surface method for system reliability analysis of pilereinforced slopes

To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile-slope system based on 3D numerical modeling is very challenging because it is computationally expensive and the performance function of the pile failure mode is only defined in the safe domain of soil stability.In this paper,an efficient hybrid response surface method is suggested to study the system reliability of pile-reinforced slopes,where the support vector machine and the Kriging model are used to approximate performance functions of soil failure and pile failure,respectively.The versatility of the suggested method is illustrated in detail with an example.For the example examined in this paper,it is found that the pile failure can significantly contribute to system failure,and the reinforcement ratio can effectively reduce the probability of pile failure.There exists a critical reinforcement ratio beyond which the system failure probability is not sensitive to the reinforcement ratio.The pile spacing affects both the probabilities of soil failure and pile failure of the pile-reinforced slope.There exists an optimal location and an optimal length for the stabilizing piles.

A non-probabilistic reliability topology optimization method based on aggregation function and matrix multiplication considering buckling response constraints

A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Synergistic defect passivation and strain compensation toward efficient and stable perovskite solar cells

Rational interface engineering is essential for minimizing interfacial nonradiative recombination losses and enhancing device performance.Herein,we report the use of bidentate diphenoxybenzene(DPOB)isomers as surface modifiers for perovskite films.The DPOB molecules,which contain two oxygen(O)atoms,chemically bond with undercoordinated Pb^(2+) on the surface of perovskite films,resulting in compression of the perovskite lattice.This chemical interaction,along with physical regulations,leads to the formation of high-quality perovskite films with compressive strain and fewer defects.This compressive strain-induced band bending promotes hole extraction and transport,while inhibiting charge recombination at the interfaces.Furthermore,the addition of DPOB will reduce the zero-dimensional(OD) Cs_4PbBr_6 phase and produce the two-dimensional(2D) CsPb_(2)Br_5 phase,which is also conducive to the improvement of device performance.Ultimately,the resulting perovskite films,which are strain-released and defect-passivated,exhibit exceptional device efficiency,reaching 10.87% for carbon-based CsPbBr_(3) device,14.86% for carbon-based CsPbI_(2)Br device,22,02% for FA_(0.97)Cs_(0.03)PbI_(3) device,respectively.Moreover,the unencapsulated CsPbBr_(3) PSC exhibits excellent stability under persistent exposure to humidity(80%) and heat(80℃) for over 50 days.

Zn Dissolution-Passivation Behavior with ZnO Formation via In Situ Characterizations

In this study,ZnO formation during the dissolution-passivation process of Zn anodes is observed via in situ Raman and optical characterization.The Zn passivation during galvanostatic anodization merely follows the dissolution-precipitation model,whereas that of potentiodynamic polarization exhibits different behaviors in different potential ranges.Initially,the Zn electrode is gradually covered by a ZnO precipitation film and then undergoes solid-state oxidation at~255 mV.The starting point of solid-state oxidation is well indicated by the abrupt current drop and yellow coloration of the electrode surface.During the pseudo passivation,an intense current oscillation is observed.Further,blink-like color changes between yellow and dark blue are revealed for the first time,implying that the oscillation is caused by the dynamic adsorption and desorption of OH groups.The as-formed ZnOs then experience a dissolution-reformation evolution,during which the crystallinity of the primary ZnO film is improved but the solid-state-formed ZnO layer becomes rich in oxygen vacancies.Eventually,oxide densification is realized,contributing to the Zn passivation.This study provides new insights into the Zn dissolution-passivation behavior,which is critical for the future optimization of Zn batteries.

Role of self-assembled molecules’anchoring groups for surface defect passivation and dipole modulation in inverted perovskite solar cells

Inverted perovskite solar cells have gained prominence in industrial advancement due to their easy fabrication,low hysteresis effects,and high stability.Despite these advantages,their efficiency is currently limited by excessive defects and poor carrier transport at the perovskite-electrode interface,particularly at the buried interface between the perovskite and transparent conductive oxide(TCO).Recent efforts in the perovskite community have focused on designing novel self-assembled molecules(SAMs)to improve the quality of the buried interface.However,a notable gap remains in understanding the regulation of atomic-scale interfacial properties of SAMs between the perovskite and TCO interfaces.This understanding is crucial,particularly in terms of identifying chemically active anchoring groups.In this study,we used the star SAM([2-(9H-carbazol-9-yl)ethyl]phosphonic acid)as the base structure to investigate the defect passivation effects of eight common anchoring groups at the perovskite-TCO interface.Our findings indicate that the phosphonic and boric acid groups exhibit notable advantages.These groups fulfill three key criteria:they provide the greatest potential for defect passivation,exhibit stable adsorption with defects,and exert significant regulatory effects on interface dipoles.Ionized anchoring groups exhibit enhanced passivation capabilities for defect energy levels due to their superior Lewis base properties,which effectively neutralize local charges near defects.Among various defect types,iodine vacancies are the easiest to passivate,whereas iodine-substituted lead defects are the most challenging to passivate.Our study provides comprehensive theoretical insights and inspiration for the design of anchoring groups in SAMs,contributing to the ongoing development of more efficient inverted perovskite solar cells.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

Improved efficiency and stability of inverse perovskite solar cells via passivation cleaning

Amidst the global energy and environmental crisis,the quest for efficient solar energy utilization intensifies.Perovskite solar cells,with efficiencies over 26%and cost-effective production,are at the forefront of research.Yet,their stability remains a barrier to industrial application.This study introduces innovative strategies to enhance the stability of inverted perovskite solar cells.By bulk and surface passivation,defect density is reduced,followed by a"passivation cleaning"using Apacl amino acid salt and isopropyl alcohol to refine film surface quality.Employing X-ray diffraction(XRD),scanning electron microscope(SEM),and atomic force microscopy(AFM),we confirmed that this process effectively neutralizes surface defects and curbs non-radiative recombination,achieving 22.6%efficiency for perovskite solar cells with the composition Cs_(0.15)FA_(0.85)PbI_(3).Crucially,the stability of treated cells in long-term tests has been markedly enhanced,laying groundwork for industrial viability.

Software Reliability Prediction Using Ensemble Learning on Selected Features in Imbalanced and Balanced Datasets: A Review

Redundancy,correlation,feature irrelevance,and missing samples are just a few problems that make it difficult to analyze software defect data.Additionally,it might be challenging to maintain an even distribution of data relating to both defective and non-defective software.The latter software class’s data are predominately present in the dataset in the majority of experimental situations.The objective of this review study is to demonstrate the effectiveness of combining ensemble learning and feature selection in improving the performance of defect classification.Besides the successful feature selection approach,a novel variant of the ensemble learning technique is analyzed to address the challenges of feature redundancy and data imbalance,providing robustness in the classification process.To overcome these problems and lessen their impact on the fault classification performance,authors carefully integrate effective feature selection with ensemble learning models.Forward selection demonstrates that a significant area under the receiver operating curve(ROC)can be attributed to only a small subset of features.The Greedy forward selection(GFS)technique outperformed Pearson’s correlation method when evaluating feature selection techniques on the datasets.Ensemble learners,such as random forests(RF)and the proposed average probability ensemble(APE),demonstrate greater resistance to the impact of weak features when compared to weighted support vector machines(W-SVMs)and extreme learning machines(ELM).Furthermore,in the case of the NASA and Java datasets,the enhanced average probability ensemble model,which incorporates the Greedy forward selection technique with the average probability ensemble model,achieved remarkably high accuracy for the area under the ROC.It approached a value of 1.0,indicating exceptional performance.This review emphasizes the importance of meticulously selecting attributes in a software dataset to accurately classify damaged components.In addition,the suggested ensemble learning model successfully addressed the aforementioned problems with software data and produced outstanding classification performance.

Doping PCBM with fullerene phosphinate derivatives enhances the interface energy alignment and synergistic passivation capability

Phenyl-C_(61)-butyric acid methyl ester(PCBM) serves as a common electron transport layer(ETL) in inverted p-i-n structure perovskite solar cells(IPSCs),yet energy barriers and insufficient passivation at the PCBM-perovskite interface hinder device effectiveness and durability.In this study,we present a series of novel Fullerene Phenylacid Ester Derivatives(FPEDs:FPP,FTPP,FDPP) incorporated into PCBM.Our investigations illustrate that FPEDs effectively act to passivate the perovskite surface by forming robust interactions with uncoordinated Pb^(2+) ions via the phosphine oxide groups present in their molecular structures,thereby enhancing the stability of the devices.Moreover,these additives elevate the energy level of the lowest unoccupied molecular orbital(LUMO) of ETL,diminish the electron injection barrier,and enhance the efficiency of interlayer electron transport.Incorporating FPEDs enhances ETL coverage on the perovskite layer,reducing leakage current significantly.Notably,Devices with PCBM/FTPP achieved a peak PCE of 23.62% and showed superior stability,maintaining 96,8% of the initial PCE after 500 h,while control devices retained merely 80.7% over the same period.

Interobserver and intraobserver reliability of skull base angles measured on magnetic resonance images

BACKGROUND Determination of platybasia and basilar kyphosis are significant parts of routine cranial magnetic resonance(MR)interpretations.These situations may explain a patient’s symptoms or may be associated with other anomalies.AIM To indicate the interobserver and intraobserver reliability of the skull base angles(SBA)(Koenigsberg standard)and modified SBA(mSBA)measurement techniques.METHODS In total,391 patients who had undergone cranial MR imaging were re-assessed regarding the SBA measurements.The SBA and mSBA techniques were used on MR images.Two reviewers independently measured the same angles twice within a 15-day interval,using different monitors.Intraclass correlation coefficient(ICC)was calculated to reveal the intraobserver and interobserver agreements.RESULTS There was an excellent agreement between reviewers regarding both angle measurements(ICC was 0.998 for SBA and mSBA).Excellent agreement levels were also observed for intraobserver measurements.ICC was 0.998 for SBA and 0.999 for mSBA for reviewer 1.ICC was 0.997 for SBA and 0.999 for mSBA according to the measurement results of reviewer 2.Higher SBA and mSBA values were observed for females compared to males.There was no correlation between SBA and age for SBA.However,a negative and low-level correlation was observed between mSBA values and age for both reviewers.CONCLUSION SBA and mSBA measurements indicated excellent agreement regarding interobserver and intraobserver differences.The study results showed that SBA angles were reliable measurement techniques to be used on MR images.