Molecular dynamics study of interactions between edge dislocation and irradiation-induced defects in Fe–10Ni–20Cr alloy

Irradiation-induced defects frequently impede the slip of dislocations, resulting in a sharp decline in the performance of nuclear reactor structural materials, particularly core structural materials. In the present work, molecular dynamics method is used to investigate the interactions between edge dislocations and three typical irradiation-induced defects(void,Frank loop, and stacking fault tetrahedron) with the sizes of 3 nm, 5 nm, and 7 nm at different temperatures in Fe–10Ni–20Cr alloy. The critical resolved shear stresses(CRSSs) are compared among different defect types after interacting with edge dislocations. The results show that the CRSS decreases with temperature increasing and defect size decreasing for each defect type during the interaction with edge dislocations, except for the case of 3-nm Frank loops at 900 K. According to a comparison, the CRSS in Frank loop is significantly higher than that of others of the same size, which is due to the occurrence of unfaulting and formation of superjog or stacking-fault complex during the interaction. The atomic evolution of irradiation-induced defects after interacting with dislocations can provide a novel insight into the design of new structural materials.

Photoluminescence Analysis of Injection-Enhanced Annealing of Electron Irradiation-Induced Defects in GaAs Middle Cells for Triple-Junction Solar Cells

Photolumineseenee measurements are carried out to investigate the injection-enhanced annealing behavior of electron radiation-induced defects in a GaAs middle cell for GaInP/GaAs/Ge triple-junction solar cells which are irradiated by 1.8 MeV with a fluence of i ~ 1015 cm-2. Minority-carrier injection under forward bias is observed to enhance the defect annealing in the GaAs middle cell, and the removal rate of the defect is determined with photoluminescenee radiative efficiency recovery. Furthermore, the injection-enhanced defect removal rates obey a simple Arrhenius law. Therefore, the annealing activation energy is acquired and is equal to 0.58eV. Finally, in comparison of the annealing activation energies, the E5 defect is identified as a primary non-radiative recombination center.

Influence of helium on the evolution of irradiation-induced defects in tungsten:An object kinetic Monte Carlo simulation

Understanding the evolution of irradiation-induced defects is of critical importance for the performance estimation of nuclear materials under irradiation.Hereby,we systematically investigate the influence of He on the evolution of Frenkel pairs and collision cascades in tungsten(W)via using the object kinetic Monte Carlo(OKMC)method.Our findings suggest that the presence of He has significant effect on the evolution of irradiation-induced defects.On the one hand,the presence of He can facilitate the recombination of vacancies and self-interstitial atoms(SIAs)in W.This can be attributed to the formation of immobile He-SIA complexes,which increases the annihilation probability of vacancies and SIAs.On the other hand,due to the high stability and low mobility of He-vacancy complexes,the growth of large vacancy clusters in W is kinetically suppressed by He addition.Specially,in comparison with the injection of collision cascades and He in sequential way at 1223 K,the average sizes of surviving vacancy clusters in W via simultaneous way are smaller,which is in good agreement with previous experimental observations.These results advocate that the impurity with low concentration has significant effect on the evolution of irradiation-induced defects in materials,and contributes to our understanding of W performance under irradiation.

Study on irradiation-induced defects in GaAs/AlGaAs core–shell nanowires via photoluminescence technique

To gain a physical insight into the radiation effect on nanowires（NWs）, the time resolved photoluminescence（TRPL）technique is used to investigate the carrier dynamic behaviors in GaAs/AlGaAs core–shell NWs before and after 1-MeV proton irradiation with fluences ranging from 1.0 × 10^（12） cm^（-2） to 3.0 × 10^（13） cm^（-2）. It is found that the degradations of spectral peak intensity and minority carrier lifetime show similar trends against irradiation fluence, which is closely related to the displacement defects induced by irradiation. We also find that the proton irradiation-induced defects behave as Shockley–Read–Hall（SRH） recombination center trapping free carriers. Finally, the defect concentration could be estimated through measuring the minority carrier lifetime.

Effects of grain boundaries on irradiation-induced defects in tungsten by molecular dynamics simulations

The effects of two different symmetric tilt grain boundaries （GBs）, ∑13[001]（230） GB and ∑17[001]（140） GB, on displacement cascade processes in tungsten were investigated using molecular dynamics simulations. By quantifying the number of interstitials and vacancies surviving after irradiation with the kinetic energy of primary knock-on atom energies of 1, 3 and 5 keV, respectively, in these simulations, it is found that the GBs have dual nature for radiation-induced defects： They absorb interstitials while leaving more vacancies to survive in the grains. The net effect is that the number of total surviving defects in the GB system is not always less than that in the single crystal. These defect behaviors are understood by quantitatively analyzing the recovery fraction of irradiation-induced defects, the time to reach steady state and the mobility of vacancies and interstitials. It is also found that the ∑17 GB is a more effective sink of radiation-induced point defects than the ∑13 GB. One of the main reasons is that the ∑17 GB has a higher GB energy.

Decade Milestone Advancement of Defect-Engineered g-C_(3)N_(4) for Solar Catalytic Applications

Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.

High quality repair of osteochondral defects in rats using the extracellular matrix of antler stem cells

BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.

Impact of Atrial Septal Defect Closure on Mortality in Older Patients

Background:Atrial septal defect(ASD)is a common form of adult congenital heart disease that can lead to long-term adverse outcomes if left untreated.Early closure of ASD has been associated with excellent outcomes and lower complication rates.However,there is limited evidence regarding the prognosis of ASD closure in older adults.This study aims to evaluate the mortality rates in older ASD patients with and without closure.Methods:A retrospective cohort study was conducted on patients aged 40 years or older with ASD between 2001 and 2017.Patients were followed up to assess all-cause mortality.Univariable and multivariable analyses were performed to identify the predictors of mortality.A p-value of<0.05 was considered statistically significant.Results:The cohort consisted of 450 patients(mean age 56.6±10.4 years,77.3%female),with 66%aged between 40 and 60 years,and 34%over 60 years.Within the cohort,299 underwent ASD closure(201 with transcatheter and 98 with surgical closure).During the median follow-up duration of 7.9 years,51 patients died.The unadjusted cumulative 10-year rate of mortality was 3%in patients with ASD closure,and 28%in patients without ASD closure(log-rank p<0.001).Multivariable analysis revealed that age(hazard ratio[HR]1.04,95%confidence interval[CI]1.006–1.06,p=0.01),NYHA class(HR 2.75,95%CI 1.63–4.62,p<0.001),blood urea nitrogen(BUN)(HR 1.07,95%CI 1.03–1.12,p<0.001),right ventricular systolic pressure(RVSP)(HR 1.07,95%CI 1.003–1.04,p=0.01),and lack of ASD closure(HR 15.12,95%CI 5.63–40.59,p<0.001)were independently associated with mortality.Conclusion:ASD closure demonstrated favorable outcomes in older patients.Age,NYHA class,BUN,RVSP,and lack of ASD closure were identified as independent factors linked to mortality in this population.

Impact Analysis of Microscopic Defect Types on the Macroscopic Crack Propagation in Sintered Silver Nanoparticles

Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,the three primary micro-defect types at potential stress concentrations in sintered AgNPs are identified,categorized,and quantified.Molecular dynamics(MD)simulations are employed to observe the failure evolution of different microscopic defects.The dominant mechanisms responsible for this evolution are dislocation nucleation and dislocation motion.At the same time,this paper clarifies the quantitative relationship between the tensile strain amount and the failure mechanism transitions of the three defect types by defining key strain points.The impact of defect types on the failure process is also discussed.Furthermore,traction-separation curves extracted from microscopic defect evolutions serve as a bridge to connect the macro-scale model.The validity of the crack propagation model is confirmed through tensile tests.Finally,we thoroughly analyze how micro-defect types influence macro-crack propagation and attempt to find supporting evidence from the MD model.Our findings provide a multi-perspective reference for the reliability analysis of sintered AgNPs.

Defect mediated losses and degradation of perovskite solar cells:Origin impacts and reliable characterization techniques

The rapid advancement of halide-based hybrid perovskite materials has garnered significant research attention,particularly in the domain of photovoltaic technology.Owing to their exceptional optoelec-tronic properties,they demonstrated power conversion efficiency(PcE)of over 25%in single junction solar cells.Despite the notable progress in PCE over the past decade,the inherent high defect density pre-senting in perovskite materials gives rise to several loss mechanisms and associated ion migration in per-ovskite solar cells(PsCs)during operational conditions.These factors collectively contribute to a significant stability challenge in PsCs,placing their longevity far behind for commercialization.While numerous reports have explored defects,ion migration,and their impacts on device performance,a com-prehensive correlation between the types of defects and the degradation kinetics of perovskite materials and PsCs has been lacking.In this context,this review aims to provide a comprehensive overview of the origins of defects and ion migration,emphasizing their correlation with the degradation kinetics of per-ovskite materials and PsCs,leveraging reliable characterization techniques.Furthermore,these charac-terization techniques are intended to comprehend loss mechanisms by different passivation approaches to enhance the durability and PCE of PSCs.

Built defects of homogeneous junction to enhance the lithium storage capacity of niobium pentoxide materials

Niobium pentoxide(Nb_(2)O_(5))is deemed one of the promising anode materials for lithium-ion batteries(LIBs)for its outstanding intrinsic fast Li-(de)intercalation kinetics.The specific capacity,however,is still limited,because the(de)intercalation of excessive Li-ions brings the undesired stress to damage Nb_(2)O_(5) crystals.To increase the capacity of Nb_(2)O_(5) and alleviate the lattice distortion caused by stress,numerous homogeneous H-and M-phases junction interfaces were proposed to produce coercive stress within theNb_(2)O_(5)crystals.Such interfaces bring about rich oxygen vacancies with structural shrinkage tendency,which pre-generate coercive stress to resist the expansion stress caused by excessive Li-ions intercalation.Therefore,the synthesized Nb_(2)O_(5) achieves the highest lithium storage capacity of 315 mA h g−1 to date,and exhibits high-rate performance(118 mA h g^(-1) at 20 C)as well as excellent cycling stability(138 mA h g^(-1) at 10 C after 600 cycles).

Effect of Vacancy Defects on the Properties of CoS_(2) and FeS_(2)

In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2) and FeS_(2),first-principles calculation method was used to investigate the alloys.The calculated results of materials without vacancy are consistent with those reported in the literatures,while the results of materials with vacancy defect were different from those of literatures due to the difference vacancy concentration.The Co vacancy defect hardly changes the half-metallic characteristic of CoS_(2).The Fe vacancy defect changes FeS_(2) from semiconductor to half-metal,and the bottom of the spin-down conduction band changes from the p orbital state of S to the d(t_(2g))orbital state of Fe,while the top of the valence band remains the d orbital d(eg)state of Fe.The half-metallic Co vacancy defects of CoS_(2) and Fe vacancy defects of FeS_(2) are expected to be used in spintronic devices.S vacancy defects make both CoS_(2) and FeS_(2) metallic.Both the Co and S vacancy defects lead to the decrease of the magnetic moment of CoS_(2),while both the Fe and S vacancy defects lead to the obvious magnetic property of FeS_(2).Vacancy defects enhance the absorption coefficient of infrared band and long band of visible light obviously,and produce obvious red shift phenomenon,which is expected to be used in photoelectric devices.

YOLO-DD:Improved YOLOv5 for Defect Detection

As computer technology continues to advance,factories have increasingly higher demands for detecting defects.However,detecting defects in a plant environment remains a challenging task due to the presence of complex backgrounds and defects of varying shapes and sizes.To address this issue,this paper proposes YOLO-DD,a defect detectionmodel based on YOLOv5 that is effective and robust.To improve the feature extraction process and better capture global information,the vanilla YOLOv5 is augmented with a new module called Relative-Distance-Aware Transformer(RDAT).Additionally,an Information Gap Filling Strategy(IGFS)is proposed to improve the fusion of features at different scales.The classic lightweight attention mechanism Squeeze-and-Excitation(SE)module is also incorporated into the neck section to enhance feature expression and improve the model’s performance.Experimental results on the NEU-DET dataset demonstrate that YOLO-DDachieves competitive results compared to state-of-the-art methods,with a 2.0% increase in accuracy compared to the original YOLOv5,achieving 82.41% accuracy and38.25FPS(framesper second).Themodel is also testedon a self-constructed fabric defect dataset,and the results show that YOLO-DD is more stable and has higher accuracy than the original YOLOv5,demonstrating its stability and generalization ability.The high efficiency of YOLO-DD enables it to meet the requirements of industrial high accuracy and real-time detection.

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

SAM Era:Can It Segment Any Industrial Surface Defects?

Segment Anything Model(SAM)is a cutting-edge model that has shown impressive performance in general object segmentation.The birth of the segment anything is a groundbreaking step towards creating a universal intelligent model.Due to its superior performance in general object segmentation,it quickly gained attention and interest.This makes SAM particularly attractive in industrial surface defect segmentation,especially for complex industrial scenes with limited training data.However,its segmentation ability for specific industrial scenes remains unknown.Therefore,in this work,we select three representative and complex industrial surface defect detection scenarios,namely strip steel surface defects,tile surface defects,and rail surface defects,to evaluate the segmentation performance of SAM.Our results show that although SAM has great potential in general object segmentation,it cannot achieve satisfactory performance in complex industrial scenes.Our test results are available at:https://github.com/VDT-2048/SAM-IS.

Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.

Surgical Repair of Ventricular Septal Defect in Neonates: Indications and Outcomes

Background:The optimal surgical timing and clinical outcomes of ventricular septal defect(VSD)closure in neo-nates remain unclear.We aimed to evaluate the clinical outcomes of VSD closure in neonates(age≤30 days).Methods:We retrospectively reviewed 50 consecutive neonates who underwent VSD closure for isolated VSDs between August 2003 and June 2021.Indications for the procedure included congestive heart failure/failure to thrive and pulmonary hypertension.Major adverse events(MAEs)were defined as the composite of all-cause mortality,reoperation,persistent atrioventricular block,and significant(≥grade 2)valvular dysfunction.Results:The median age and body weight at operation were 26.0 days(interquartile range[IQR],18.8–28.3)and 3.7 kg(IQR,3.3–4.2),respectively.The median follow-up duration was 110.4 months(IQR,56.8–165.0).Seven patients required preoperative respiratory support,andfive had significant(≥grade 2)preoperative valvular dysfunction.One early mortality occurred due to irreversible cardiogenic shock;no late mortality was observed.One reopera-tion was due to hemodynamically significant residual VSD at 103.8 months postoperatively.The overall survival,freedom from reoperation,and freedom from MAE at 15-years were 98.0%,96.3%,and 94.4%,respectively.Pre-operative mechanical ventilation was associated with a longer duration of postoperative mechanical ventilation(p<0.001)and a longer length of intensive care unit stay(p<0.001).Conclusions:VSD closure with favorable outcomes without morbidities is feasible even in neonates.However,neonates requiring preoperative respiratory support may require careful postoperative management considering the long-term postoperative risks.Overall,surgical VSD closure might be indicated earlier in neonates with respiratory compromise.

3D reconstruction and defect pattern recognition of bonding wire based on stereo vision

Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after packaging.Image-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding wire.Therefore,a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision,which can achieve non-destructive detection of bonding wire defects is proposed.The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires.Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface,a point cloud segmentation method based on spatial surface feature detection(SFD)was proposed.SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process.Furthermore,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires.The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires.The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires,and the average accuracy of defect recognition is 96.47%,which meets the production requirements of bonding wire defect detection.

Reliability of Echocardiographic Pulmonary Vascular Resistance to Screen for the New Definition of Precapillary Pulmonary Hypertension in Uncorrected Secundum Atrial Septal Defect

Background and Objective:The most feared complication of uncorrected secundum Atrial Septal Defect(ASD)is pulmonary arterial hypertension(PAH).Pulmonary vascular resistance(PVR)is crucial in detecting precapil-lary pulmonary hypertension(PH)to guide the need for PAH-specific therapy.There is a change in the cut-off value of PVR according to the recently updated PH guideline.How echocardiographic PVR(PVRecho)correlates to PVR by right heart catheterization(RHC)(PVRcath)according to the new guidelines has not been known.The aim of this study is to determine the reliability of PVRecho in detecting PAH in Uncorrected Ostium Secundum ASD based on the current updated guideline and to help screen the high PVR group.Methods:429 ostium secun-dum ASD in the COngenital HeARt Disease in Adult and Pulmonary Hypertension(COHARD-PH)registry was divided into three groups according to the PVR.PVRecho was calculated using Abbas’Formula and compared the its gold standard,the PVRcath.The correlation between the two methods was analyzed.The Bland-Altman plot was used to analyze the agreement between the two methods.Receiver operating characteristics(ROC)analysis was used to determine the PVRecho cut-off value for high PVR.Results:The majority of the population(63.5%)had high PVR.Female gender dominated the study population(84%).PVR_(echo) was significantly correlated with PVRcath(r=0.6225,p<0.0001).Bland-Altman plot among all groups and in subgroups analysis showed a wide range of agreement.PVRecho underestimated PVRcath 5.124 WU.In subgroup analysis,PVRecho overestimated PVRcath 0.35 WU in those with PVR<2 WU.In the second and third groups,PVR_(echo) underestimated PVRcath 0.52 and 10.77 WU,respectively.Conclusion:PVRecho is reliable in predicting high PVR in uncorrected secun-dum ASD.However,there is a wide range of agreement.PVR_(echo) cut-off value of>1.62 WU showed good dis-criminatory power in determining high PVR.

Intrinsic pentagon defect engineering in multiple spatial-scale carbon frameworks for efficient triiodide reduction

Intrinsic topological defect engineering has been proven as a promising strategy to elevate the electrocatalytic activity of carbon materials.However,the controllable construction of high-density and specific topological defects in carbon frameworks to reveal the relationship between reactivity and defect structure remains a challenging task.Herein,the intrinsic pentagon carbon sites that can favor electron overflow and enhance their binding affinity towards the intermediates of catalytic reaction are firstly presented by the work function and the p-band center calculations.To experimentally verify this,the cage-opening reaction of fullerene is proposed and utilized for synthesizing carbon quantum dots with specific pentagon configuration(CQDs-P),subsequently utilizing CQDs-P to modulate the micro-scale defect density of three-dimensional reduced graphene oxide(rGO)viaπ-πinteractions.The multiple spatial-scale rGO-conjugated CQDs-P structure simultaneously possesses abundant pentagon and edge defects as catalytic active sites and long-range-orderedπelectron delocalization system as conductive network.The defects-rich CQDs-P/rGO-4 all-carbon-based catalyst exhibits superb catalytic activity for triiodide reduction reaction with a high photoelectric conversion efficiency of 8.40%,superior to the Pt reference(7.97%).Theoretical calculations suggest that pentagon defects in the carbon frameworks can promote charge transfer and modulate the adsorption/dissociation behavior of the reaction intermediates,thus enhancing the electrocatalytic activity of the catalyst.This work confirms the role of intrinsic pentagon defects in catalytic reactions and provides a new insight into the synthesis of defects-rich carbon catalysts.