Defect Population Research Articles

Defects Characterization of HgCdTe and CdZnTe Compounds by Positron Annihilation Spectroscopy

Infrared cooled photodetectors must operate at higher temperatures to reduce their size, weight and power consumption (SWaP context). Their stability and image quality are then challenged by extra electrical activity of crystal defects. Knowledge of defect populations is mandatory to improve the material quality of the epitaxial Hg1−xCdxTe (MCT) active layer and the Cd1−xZnxTe (CZT) substrate. Positron annihilation spectroscopy with a slow positron beam was used to study near-surface open-volume defects profiles. Low- and high-momentum fractions (\(S\),\( W\)) were used to characterize the Doppler broadening of the 511 keV electron-positron pair annihilation-line as a function of the positron implantation energy \(E\). The results show that three regions can be identified beneath the surface of the as-grown non-optimized MCT layer. The quasi-linear relationship between the annihilation characteristics in the regions suggests that the defect populations mainly correspond to the same open-volume defect in different concentrations. The probed defect is thought to be related to the mercury vacancy. This hypothesis is discussed in an original way with near-surface elemental profiles using scanning transmission electron spectroscopy combined to energy dispersive x-ray spectroscopy (STEM-EDX). Afterwards, this approach is extended to CZT substrates showing that surface and bulk properties of those fabricated by LYNRED tend to match those that are state-of-the-art. A common open-volume defect is probed, in concentration estimated by Hall effect around 1015 cm−3 and thought to be related to the cadmium vacancy.

Diffusion of oxygen in Mg-doped α−Al2O3 : The corundum conundrum explained

It has been a puzzle for over two decades that the enhancement of oxygen diffusion in $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$, with respect to the amount of Mg doping, is several orders of magnitude less than expected. The standard model, which envisages that transport is mediated by oxygen vacancies induced to compensate the charge of ${\mathrm{Mg}}^{2+}$ ions substituting ${\mathrm{Al}}^{3+}$ ions, has not been able to explain this anomaly. Here, we report a detailed study of populations of point defects and defect clusters in Mg-doped $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$. By taking into account calculated defect formation energies from the literature, the condition of charge neutrality, and the environmental parameters (chemical potentials) under which the anomalous trend in oxygen diffusivities were previously observed, we are able to arrive at an explanation. A nonlinear relationship between Mg concentration in the system and key native point defects, which serve as mediators of self-diffusion in $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$, is predicted: The concentrations of such defects increase much more slowly in the supersaturation regime than in the presaturation regime, matching the anomalous result previously observed in $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$. We identify the reason for this as buffering by positively charged Mg interstitials and Mg--oxygen vacancy clusters, which compensate the negative charges of Mg substitutional defects (${\mathrm{Mg}}_{\text{Al}}^{1\ensuremath{-}}$). This study answers part of the long-standing question about self-diffusion in alumina, referred to by Heuer and Lagerl\"of in 1999 as the corundum conundrum.

Ternary CuCrCeOx Solid Solution Enhances N2‐Selectivity in the NO Reduction with CO in the Presence of Water and Oxygen

AbstractCo‐doping of ceria with Cu and Cr forming a ternary CuCrCeOx solid solution enhances N2‐selectivity as well as NO and CO conversions compared to the corresponding singly doped ceria, CuCeOx and CrCeOx, and pristine ceria, in the absence as well as presence of water and oxygen. The comparative study of these solid‐solution catalysts indicates that the doping of ceria results in the coupling of different transition metal redox cycles, which has a strong effect on the surface population of oxygen vacancies. The temperature required to reach 95 % N2‐selectivity is shown to be nearly linearly correlated to the concentration of oxygen vacancy defects. The oxygen defect population is highest for the ternary CuCrCeOx solid solution, which exhibits the best catalytic performance, reaching 100 % N2‐selectivity at around 100 °C. Three redox cycles (CrVI/CrIII, CuII/CuI, and CeIV/CeIII) have been identified in this catalyst leading to a synergistic effect. The ternary CuCrCeOx catalyst exhibits good water tolerance and long‐term stability while the SO2 tolerance is limited due to selective blocking of the active surface oxygen defects forming SO32− species, resulting in catalyst deactivation.

Bismuth oxyhalide quantum dots modified sodium titanate necklaces with exceptional population of oxygen vacancies and photocatalytic activity

We here demonstrate the controlled synthesis of BiOBr quantum dots (QDs) decorated Na2Ti3O7 necklaces via a hydrothermal transformation of sodium titanate nanotubes. The BiOBr QDs are deposited on the surface of Na2Ti3O7 necklaces, forming a heterogeneous interface of BiOBr(200) and Na2Ti3O7(110), which promotes the separation efficiency of photogenerated charges, thus resulting in its superior catalytic performance in the photo-oxidation of benzyl alcohol. The BiOBr/Na2Ti3O7-1.0 exhibiting highest oxygen defect population gives best photocatalytic activity with a promising conversion rate of 3.32 mmolreacted BA gcatal.−1h−1, which is substantially higher than the corresponding reported photocatalysts. DFT results corroborate the superior performance of BiOBr/Na2Ti3O7 is mainly due to the formation of a built-in electric field and given efficiently the charge transfer between BiOBr(200) and Na2Ti3O7(110). In all, this study reports a simple in-situ hydrothermal growth protocol to efficiently construct BiOBr/Na2Ti3O7 heterojunction composites and offers guidelines for design of a new synthetic strategy to prepare efficient photocatalysts.

Damage tolerance in additively manufactured ceramic architected materials

Technical ceramics exhibit exceptional high-temperature properties, but unfortunately their extreme crack sensitivity and high melting point make it challenging to manufacture geometrically complex structures with sufficient strength and toughness. Emerging additive manufacturing technologies enable the fabrication of large-scale complex-shape artifacts with architected internal topology; when such topology can be arranged at the microscale, the defect population can be controlled, thus improving the strength of the material. Here, ceramic micro-architected materials are fabricated using direct ink writing (DIW) of an alumina nanoparticle-loaded ink, followed by sintering. After characterizing the rheology of the ink and extracting optimal processing parameters, the microstructure of the sintered structures is investigated to assess composition, density, grain size and defect population. Mechanical experiments reveal that woodpile architected materials with relative densities of 0.38–0.73 exhibit higher strength and damage tolerance than fully dense ceramics printed under identical conditions, an intriguing feature that can be attributed to topological toughening.

Compact Integration of Hydrogen–Resistant a–InGaZnO and Poly–Si Thin–Film Transistors

The low–temperature poly–Si oxide (LTPO) backplane is realized by monolithically integrating low–temperature poly–Si (LTPS) and amorphous oxide semiconductor (AOS) thin–film transistors (TFTs) in the same display backplane. The LTPO–enabled dynamic refreshing rate can significantly reduce the display’s power consumption. However, the essential hydrogenation of LTPS would seriously deteriorate AOS TFTs by increasing the population of channel defects and carriers. Hydrogen (H) diffusion barriers were comparatively investigated to reduce the H content in amorphous indium–gallium–zinc oxide (a–IGZO). Moreover, the intrinsic H–resistance of a–IGZO was impressively enhanced by plasma treatments, such as fluorine and nitrous oxide. Enabled by the suppressed H conflict, a novel AOS/LTPS integration structure was tested by directly stacking the H–resistant a–IGZO on poly–Si TFT, dubbed metal–oxide–on–Si (MOOS). The noticeably shrunken layout footprint could support much higher resolution and pixel density for next–generation displays, especially AR and VR displays. Compared to the conventional LTPO circuits, the more compact MOOS circuits exhibited similar characteristics.

Defect-induced distinct exciton-exciton interactions in WS2 monolayers

The optoelectronic properties of atomically thin transition metal dichalcogenides (TMDs) are largely influenced by defect populations (DPs). In this work, we fabricate WS2 monolayers with different DPs by varying the fabrication methods and further reveal their distinct exciton-exciton interactions. Steady-state photoluminescence (PL) experiments show that the monolayer with the lowest DP shows optimal PL intensity at low excitation power; however, it is overtaken and significantly surpassed by monolayers with higher DPs at high excitation powers. Excitation-power-dependent experiments demonstrate that these monolayers exhibit distinct PL saturation behaviors with the threshold power differing by four orders of magnitude. Combined with in situ PL imaging and time-resolved PL experiments, we attribute such PL evolution discrepancies to the different DPs within these monolayers, which largely influence the exciton diffusion behavior and subsequently bring about distinct nonradiative exciton-exciton annihilations (EEAs). Valley polarization experiments are further employed to re-examine the DPs of these monolayers. This work reveals the distinct PL behaviors and underlying exciton dynamics in TMD monolayers with different DPs, which can largely facilitate the engineering of relevant high-performance devices for practical applications.

Towards Quantitative Inference of Nanoscale Defects in Irradiated Metals and Alloys

Quantifying the population of nanoscale defects that are formed in metals and alloys exposed to extreme radiation environments remains a pressing challenge in materials science. These defects both fundamentally alter material properties and seed long-timescale performance degradation, which often limits the lifespan of engineering systems. Unlike ceramic and semiconducting materials, these defects in metals and alloys are not spectroscopically active, forcing characterization to rely on indirect measurements from which the distribution of nanoscale defects may be inferred. In this mini-review, different experimental methodologies which have been employed for defect inference are highlighted to capture the current state of the art. Future directions in this area are proposed, which, by combining data streams from multiple and complementary characterization methods in concert with multi-scale modeling and simulation, will enable the ultimate goal of quantifying the full spectrum of defects in irradiated metals and alloys.

One-step oxidative-adsorptive desulfurization of DBT on simulated solar light-driven nano photocatalyst of MoS2-C3N4-BiOBr @MCM-41

Using a catalyst-adsorbent for simultaneous oxidation and adsorption of sulphuric compounds in liquid fuels is an effective and economical way. Thus in this paper, the core–shell MoS2-C3N4-BiOBr@MCM-41 photocatalyst-adsorbents with different percentages of MoS2 (1, 3, and 5 wt%) were prepared and used in a one-step photo oxidative-adsorptive desulfurization under simulated solar light. Thesamples were characterized by XRD, FESEM, FTIR, EDX, BET-BJH, TEM, UV–Vis DRS, and PL analyses. Theresults indicated that the final C/C0decreased from 0.42 to 0.016 with increasing the MoS2percentage (98.4% conversion). Despite the lowest surface area (845 m2/g) and the broad bandgap energy (2.8 eV), the sample with 5 wt% of MoS2illustrated the most degree of desulfurization due to strong interaction between components, the highest coverage of MCM-41 with active phases, high population of structural defects, high capability of light absorption and low recombination rate of charge carriers. GC-MS analysis indicated no DBT, DBTO or DBTO2 in the treated fuel. However, the presence of DBTO2 on the surface of the photocatalyst was confirmed that reveals the successful one-step oxidative-adsorptive desulfurization on the MoS2-C3N4-BiOBr@MCM-41. The adsorption mechanism was consistent with the pseudo-second-order kinetics, indicating that the rate-limiting step was chemical adsorption. Moreover, selectivity evaluations showed that while MoS2-C3N4-BiOBr@MCM-41 photocatalyst had high activity in the desulfurization of DBT, its affinity for adsorption and photocatalytic oxidation of non-sulfur aromatic compounds such as benzene, xylene and toluene was very low.

X-ray imaging of defect population and the effect on high cycle fatigue life of laser additive manufactured Ti6Al4V alloys

Laser powder bed fusion (L-PBF) Ti6Al4V samples were made to estimate their high cycle fatigue performance. The annealed samples were measured in the HCF regime and crack initiation was identified using scanning electron microscope. Defect population was detected using X-ray micro computed tomography. Additionally, their formation and effects on the fatigue life were characterized and discussed. The results demonstrated that optimized L-PBF process remained instability and induced metallurgical defects with random distribution, particularly in the horizontal orientation. The scatter and anisotropy of fatigue life were dependent upon the characteristics of surface keyholes. The pore defect presented a slight effect on crack propagation, while the persistent slip band at the surface can evolve into a crack initiation when the defect size was less than 40 μm. The lack of fusion defect significantly reduced the tensile properties and was sufficient to act as fatigue crack initiation when it appeared. The defect population in reconstructed three-dimensional volume was available for estimating fatigue life, and provided an attenuated exponential relationship using an X-parameter fatigue life prediction model considering the size and shape of surface keyholes. The results provide an understanding of the technological significance of process control and stability, and the effect of defects on the fatigue life.

DefAP: A Python code for the analysis of point defects in crystalline solids

Inevitably, all crystalline materials will contain imperfections that have the ability to modify the properties of the host material. Key to the development of advanced materials is the ability to predict the concentrations of different defects in any given environmental conditions and how the change in the defect population alters the material’s properties. Modern first principles atomistic simulation techniques, such as density functional theory (DFT), are now widely employed for the simulation of point defects, however, to develop true insight into a material’s defect chemistry, it is essential to link the energies calculated to thermodynamic variables that fully describe its operating conditions. The Defect Analysis Package (DefAP), an open-source Python code, has been designed to fulfil this role. The primary function of the package is to predict the concentrations of defects in materials as a function of key thermodynamic variables, such as temperature and availability of different species, expressed through chemical potentials. Through simple thermodynamic equations, DefAP allows the rapid exploration of a material’s defect chemistry allowing direct comparison with experimental observations. Rapid exploration is supported through the use of autoplotting with carefully considered automatic data labelling and simplification options enabling production of publication quality plots. DefAP offers a wide range of options for the calculation of defect and carrier concentrations that can be customised by the user to suit the material studied and an extensive suite of options have been designed for the study of extrinsic defects (e.g. dopants or impurities). The capabilities of DefAP are demonstrated in this paper by studying intrinsic defects in YBa2Cu3O7, P doping in Si, Am accumulation in PuO2, and simultaneous build-up of T and He in Li2TiO3.

Entropy Stabilization Effects and Ion Migration in 3D "Hollow" Halide Perovskites.

A recently discovered new family of 3D halide perovskites with the general formula (A)1-x(en)x(Pb)1-0.7x(X)3-0.4x (A = MA, FA; X = Br, I; MA = methylammonium, FA = formamidinium, en = ethylenediammonium) is referred to as "hollow" perovskites owing to extensive Pb and X vacancies created on incorporation of en cations in the 3D network. The "hollow" motif allows fine tuning of optical, electronic, and transport properties and bestowing good environmental stability proportional to en loading. To shed light on the origin of the apparent stability of these materials, we performed detailed thermochemical studies, using room temperature solution calorimetry combined with density functional theory simulations on three different families of "hollow" perovskites namely en/FAPbI3, en/MAPbI3, and en/FAPbBr3. We found that the bromide perovskites are more energetically stable compared to iodide perovskites in the FA-based hollow compounds, as shown by the measured enthalpies of formation and the calculated formation energies. The least stable FAPbI3 gains stability on incorporation of the en cation, whereas FAPbBr3 becomes less stable with en loading. This behavior is attributed to the difference in the 3D cage size in the bromide and iodide perovskites. Configurational entropy, which arises from randomly distributed cation and anion vacancies, plays a significant role in stabilizing these "hollow" perovskite structures despite small differences in their formation enthalpies. With the increased vacancy defect population, we have also examined halide ion migration in the FA-based "hollow" perovskites and found that the migration energy barriers become smaller with the increasing en content.

Tensile and fracture behavior of silica fibers from the Venus flower basket (Euplectella aspergillum)

The extraordinary mechanical properties shown by many biological materials stem from their unique hierarchical structures. The spicules of the deep-sea glass sponge, Euplectella aspergillum, show layered architecture and are known to improve toughness in various loading conditions. In the present work, we conducted a systematic study on the tensile and fracture behavior of E. aspergillum’s spicules. Tensile tests were performed on three different gage lengths of spicules that compose anchoring structures of E. aspergillum. The cross-sectional area of each spicule was accurately measured using an x-ray microscope. The effect of gage length and varying cross-sectional area on the tensile behavior of spicules is discussed in detail. The interplay between two failure initiation sites, namely, weakest-link flaws and minimum cross-sectional area locations was observed. Weibull statistics were used to quantify the variability in the strengths of spicules as a function of their gage length. The Weibull modulus was observed to decrease with the increase in gage length. The possibility of a bimodal flaw population for a higher gage length of spicules due to the interplay between failure initiation sites is also discussed. The fractography study was utilized to understand the failure and toughening mechanisms of spicules in tensile loading. The fracture toughness of the central core was quantified from fracture surfaces using a linear elastic fracture mechanics model. The present study shows that the failure of spicules initiates in the outer layers and proceeds progressively to the center. The layers surrounding the central core of the spicule resist the crack propagation and increase its toughness.

Correlating in-situ sensor data to defect locations and part quality for additively manufactured parts using machine learning

In this work, process monitoring data, including layerwise imagery, multi-spectral emissions, and laser scan vector data, were collected during laser-based powder bed fusion additive manufacturing and correlated to fatigue performance. All parts were X-ray CT scanned post-build, and internal flaws were identified via an automated defect recognition software. Convolutional neural networks were trained to discriminate flaws from nominal build conditions using in situ data modalities only. Trained classifiers were then tested against a previously unseen data set collected from an independent build, and classification performance and metrics for information content provided by each individual modality were formally established. Correlations were drawn between the detected flaw populations and the corresponding fatigue properties, demonstrating that fatigue critical lack-of-fusion flaws can be detected via machine learning of in situ sensor data. The present results also show that, at least from a classification accuracy perspective, flaw detection via ML on process monitoring data is a viable path forward for real-time flaw detection and automated, interlayer repair strategies. However, strategies for extracting and analyzing sensor data in real-time without incurring excessive increases in build time must first be developed. These developments represent necessary components to draw direct correlations between in situ data modalities, internal part quality, and fatigue performance.

A parallel discrete dislocation dynamics/kinetic Monte Carlo method to study non-conservative plastic processes

Non-conservative processes play a fundamental role in plasticity and are behind important macroscopic phenomena such as creep, dynamic strain aging, loop raft formation, etc. In the most general case, vacancy-induced dislocation climb is the operating unit mechanism. While dislocation/vacancy interactions have been modeled in the literature using a variety of methods, the approaches developed rely on continuum descriptions of both the vacancy population and its fluxes. However, there are numerous situations in physics where point defect populations display heterogeneous concentrations and/or non-smooth kinetics. Here, a kinetic Monte Carlo (kMC) approach for modeling vacancy transport in response to arbitrary stress fields is used. Vacancies are treated as point particles and are coupled to the dislocation substructure representing a deformed material via an advection term defined by the local stress gradients. The stress fields and the dislocation substructure are evolved using a discrete dislocation dynamics (DDD) module. To extend the coupled model to the treatment of large systems, we have implemented it in the massively-parallel DDD code ParaDiS. To avoid numerical incompatibilities associated with merging deterministic (DDD) and stochastic (kMC) integration algorithms, we cast the entire elasto-plastic-diffusive problem within a single stochastic framework, taking advantage of a parallel kMC algorithm to evolve the system as a single event-driven process. The large-scale implementation enables the study of the evolution of a variety of dislocation-defect scenarios governed by non-conservative transport kinetics. After carrying out an exhaustive numerical and computational analysis of our parallel algorithm, we show results that emphasize situations where inhomogeneous vacancy dynamics are of relevance, and compare discrete kinetics to continuum solutions for several cases.

Role of intrinsic defects in cubic NaNbO3: A computational study based on hybrid density-functional theory

Antiferroelectric NaNbO3 is a candidate material for application in high-energy density dielectric capacitors. In this context, various doping strategies have been used for installing the desired narrow double P–E loop behavior in this lead-free material. However, controlled doping requires a detailed understanding of the type and population of intrinsic defects, which have not been studied so far. In this study, we, therefore, calculate formation energies, electronic transition levels, and doping behavior of intrinsic defects in cubic NaNbO3 by means of electronic structure calculations based on density functional theory using a hybrid exchange-correlation functional (HSE06) and finite-size correction. The results show that the dominant defects are Na and O vacancies, and that the material is an n-type semiconductor for almost all oxygen partial pressures. Additionally, we predict the presence of a defect complex (VNa– VO– VNa) consisting of two Na vacancies and one O vacancy in two possible structures, which is stable for n- or p-type doping conditions.

Peridynamic modeling of stochastic fractures in bolted glass plates

This paper presents a peridynamics-based computational approach for modeling fractures in bolted glass plates that features an explicit consideration of randomly distributed micro-flaws. The glass fabrication procedures are assumed to produce a stochastic distribution of a single population of Pareto-distributed surface flaws and mono-sized edge flaws. Numerical simulations are presented of the cracking that develops for varying geometrical configurations of the glass plates under in-plane loads, using a plane stress ordinary state-based peridynamics formulation. The fracture patterns and failure loads predicted by the models agree reasonably well with corresponding experimental observations. The results from a series of simulations suggest that the distribution of strength can be fitted by the Weibull distribution or normal distribution, but is strongly dependent on the assumed values of edge flaw density and flaw depth.

Hot Isostatic Pressing for Fatigue Critical Additively Manufactured Ti-6Al-4V.

The efficacy of hot isostatic pressing (HIP) for enhancing fatigue performance is investigated for additively manufactured (AM) Ti-6Al-4V. The limitations of HIP are probed by varying the initial material state via the selection of AM system, powder chemical composition, and process parameters. We demonstrate that the fatigue performance of HIP’d AM Ti-6Al-4V depends on the as-built quality of the material. Differences in common material attributes, such as pre-HIP defect populations or post-HIP microstructure morphology, are shown to be insufficient to explain the observed discrepancies in performance. This implies that additional microstructure attributes or localized deviations from the expected structure control the failure of this material. Finally, HIP parameters outside ASTM recommendations were explored, where a reduced temperature and high-pressure treatment yielded significantly improved fatigue performance.

Arresting Photodegradation in Semiconducting Single-Walled Carbon Nanotube Thin Films

Solid-state dispersions of isolated single-walled carbon nanotubes (SWCNTs) in polymer matrices or networks of electronically coupled SWCNTs are gaining interest for a broad variety of optoelectronic applications. However, little is known about either the stability or degradation mechanisms of these systems. We show dramatic sp2-to-sp3 defect transformations of the SWCNT sidewall when either the S11 or S22 exciton transitions are optically pumped in ambient conditions, leading to the rapid decay of absorption and emission properties in less than 24 h for conditions similar to exposure to solar illumination. Importantly, we demonstrate that either (i) encapsulation to block reactive O2 from SWCNT excited states or (ii) exciton quenching via donor-to-acceptor electron transfer is an effective route for “kinetic stabilization” against photodegradation, with <8% loss in absorbance after 1200 h of illumination. We find that SWCNT:polymer loading does not impact degradation. Our study suggests that the sp3 defects are associated with the formation of oxygenic groups on the SWCNT sidewall. While such defect populations can detrimentally evolve over time in films where SWCNTs are environmentally exposed in the presence of light, we offer multiple pathways to arrest this degradation and enable their robust application as advanced optical materials in optical and electronic devices.

Effects of Defect on Work Function and Energy Alignment of PbI2: Implications for Solar Cell Applications

Two-dimensional (2D) layered lead iodide (PbI2) is an important precursor and common residual species during the synthesis of lead-halide perovskites. There currently exist some debates and uncertainties about the effect of excess PbI2 on the efficiency and stability of the solar cell with respect to its energy alignment and energetics of defects. Herein, by applying the first-principles calculations, we investigate the energetics, changes of work function and the defective levels associated with the iodine vacancy (VI) and interstitial iodine (II) defects of monolayer PbI2 (ML-PbI2). We find that the PbI2 has a very low formation energy of VI of 0.77 and 0.19 eV for dilute and high concentration, respectively, reflecting coalescence tendency of isolated VI, much lower than that of vacancies in other 2D materials like phosphorene. Similar to VI, a low formation energy of II of 0.65 eV is found, implying a high population of such defects. Both defects generate in-gap defective levels which are mainly due to the unsaturated chemical bonds of p-orbitals of exposed Pb or inserted I. Such rich defective levels allow the VI and II as the reservoir or sinks of electron/hole carriers in PbI2. Our results suggest that the remnant PbI2 in perovskite MAPbI3 (or FAPbI3) would play dual opposite roles in affecting the efficiency of the perovskite: (1) Forming Schottky-type interface with MAPbI3 (or FAPbI3) in which the built-in potential would facilitate the electron-hole separation and prolong the carrier lifetime; (2) Acting as the recombination centers due to the deep defective levels. To promote the efficiency by the Schottky effect, our work reveals that the II defect is favored, and to reduce the recombination centers the VI defect should be suppressed. Our results shall be beneficial in improving strategies for the related optoelectronics applications.