Point Defects In Materials Research Articles

Point defects in Dirac semimetal BeN[formula omitted] monolayer and their interaction with gas molecules

Point defects in materials may occur during the fabrication process of monolayer materials, or these defects can be created via electron beam irradiation to the perfect crystals. Recently, a triclinic phase of beryllium tetranitride BeN4 was synthesized from elements at ∼85 GPa pressure and can become a monolayer under ambient conditions. In this study, we have introduced various point defects into the BeN4 monolayer such as Be or N mono vacancy (Bevac, Nvac), BeN divacancy (BeNvac), antisite defect of BeN atomic positions and Stone–Wales (SW) defect, and investigated electronic and magnetic changes in the material. It is found that with the Be vacancy, the Dirac cone of the BeN4 monolayer disappears and the Bevac monolayer shows semi-metallic properties with overlapping valence and conduction bands. N vacancy induces local magnetic moment (0.797 μB) to the structure, and the Nvac monolayer has a direct band gap value of 0.172 eV. While the BeN divacancy turns the structure to metal, the antisite-defected BeN4 monolayer turns into a non-magnetic semiconductor with a band gap value of 0.256 eV. Furthermore, we have introduced bare and defected BeN4 monolayers with CO, CO2, H2, H2O and O2 gas molecules and found that these molecules give rise to crucial effects on the electronic and magnetic properties of the materials. While the considered molecules are physisorbed on the bare BeN4 monolayer, the H2O molecule dissociated to OH and H on the Nvac structure, and O2 molecule strongly binds on Nvac and antisite BeN4 monolayers. Furthermore, we have reported that the antisite BeN4 monolayer may be a good candidate material for hydrogen storage devices with an adsorption energy of 0.355 eV of the H2 molecule. We believe that our theoretical findings will be beneficial for further experimental and theoretical studies on BeN4 structure.

Compound-tunable embedding potential method: analysis of pseudopotentials for Yb in YbF2, YbF3, YbCl2 and YbCl3 crystals.

The compound-tunable embedding potential (CTEP) method developed in [Lomachuk et al., Phys. Chem. Chem. Phys., 2020, 22, 17922; Maltsev et al., Phys. Rev. B, 2021, 103, 205105] to describe the electronic structure of fragments and point defects in materials is applied to crystals containing periodically arranged lanthanide atoms, which can have an open 4f-shell. We consider YbF2, YbF3, YbCl2, and YbCl3 crystals for the pilot CTEP studies such that 4f-electrons are not treated explicitly at the CTEP generation stages. Instead, the pseudopotentials with 60 and 59 electrons in the core for Yb(II) and Yb(III), correspondingly, are applied and the latter treats the "4f-hole-in-core". At the final stage, the two-component embedded cluster study of fragments of YbHaln crystals (Hal = F, Cl; n = 2, 3) is performed using the CTEP method and a relativistic pseudopotential with 28 electrons in the core for the central Yb atom. Remarkable agreement of the electronic densities within the YbHal2 fragments with those of the original periodic crystal calculation is demonstrated. The calculated interatomic distances between the central Yb and nearest halide atoms are in pretty good agreement with the experimental data, the deviations are within 0.015 Å for all the studied crystals. Thus, the overall accuracy for the crystal characteristics evaluated using CTEP in the combined periodic-structure and embedded cluster study is comparable with that of Yb-containing molecular calculations.

Exploring the Evolution Mechanism of Sulfur Vacancies by Investigating the Role of Vacancy Defects in the Interaction between H2S and the FeS(001) Surface.

Vacancy defects are inherent point defects in materials. In this study, we investigate the role of Fe vacancy (VFe) and S vacancy (VS) in the interaction (adsorption, dissociation, and diffusion) between H2S and the FeS(001) surface using the dispersion-corrected density functional theory (DFT-D2) method. VFe promotes the dissociation of H2S but slightly hinders the dissociation of HS. Compared with the perfect surface (2.08 and 1.15 eV), the dissociation energy barrier of H2S is reduced to 1.56 eV, and HS is increased to 1.25 eV. Meanwhile, S vacancy (VS) significantly facilitates the adsorption and dissociation of H2S, which not only reduces the dissociation energy barriers of H2S and HS to 0.07 and 0.11 eV, respectively, but also changes the dissociation process of H2S from an endothermic process to a spontaneous exothermic one. Furthermore, VFe can promote the hydrogen (H) diffusion process from the surface into the matrix and reduce the energy barrier of the rate-limiting step from 1.12 to 0.26 eV. But it is very hard for H atoms gathered around VS to diffuse into the matrix, especially the energy barrier of the rate-limiting step increases to 1.89 eV. Finally, we propose that VS on the FeS(001) surface is intensely difficult to form and exist in the actual environment through the calculation results.

Defect Detection in Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning

Point defects play a fundamental role in the discovery of new materials due to their strong influence on material properties and behavior. At present, imaging techniques based on transmission electron microscopy (TEM) are widely employed for characterizing point defects in materials. However, current methods for defect detection predominantly involve visual inspection of TEM images, which is laborious and poses difficulties in materials where defect related contrast is weak or ambiguous. Recent efforts to develop machine learning methods for the detection of point defects in TEM images have focused on supervised methods that require labeled training data that is generated via simulation. Motivated by a desire for machine learning methods that can be trained on experimental data, we propose two self-supervised machine learning algorithms that are trained solely on images that are defect-free. Our proposed methods use principal components analysis (PCA) and convolutional neural networks (CNN) to analyze a TEM image and predict the location of a defect. Using simulated TEM images, we show that PCA can be used to accurately locate point defects in the case where there is no imaging noise. In the case where there is imaging noise, we show that incorporating a CNN dramatically improves model performance. Our models rely on a novel approach that uses the residual between a TEM image and its PCA reconstruction.

Modeling Excited States of Point Defects in Materials from Many-Body Perturbation Theory

Modeling Excited States of Point Defects in Materials from Many-Body Perturbation Theory

Evolutionary computing and machine learning for discovering of low-energy defect configurations

Density functional theory (DFT) has become a standard tool for the study of point defects in materials. However, finding the most stable defective structures remains a very challenging task as it involves the solution of a multimodal optimization problem with a high-dimensional objective function. Hitherto, the approaches most commonly used to tackle this problem have been mostly empirical, heuristic, and/or based on domain knowledge. In this contribution, we describe an approach for exploring the potential energy surface (PES) based on the covariance matrix adaptation evolution strategy (CMA-ES) and supervised and unsupervised machine learning models. The resulting algorithm depends only on a limited set of physically interpretable hyperparameters and the approach offers a systematic way for finding low-energy configurations of isolated point defects in solids. We demonstrate its applicability on different systems and show its ability to find known low-energy structures and discover additional ones as well.

Modeling Corrosion with First-Principles Electrochemical Phase Diagrams

Understanding and predicting materials corrosion under electrochemical environments are of increasing importance to both established and developing industries and technologies, including construction, marine materials, geology, and biomedicine, as well as to energy generation, storage, and conversion. Owing to recent progress in the accuracy and capability of density functional theory (DFT) calculations to describe the thermodynamic stability of materials, this powerful computational tool can be used both to describe materials corrosion and to design materials with the desired corrosion resistance by using first-principles electrochemical phase diagrams. We review the progress in simulating electrochemical phase diagrams of bulk solids, surface systems, and point defects in materials using DFT methods as well as the application of these ab initio phase diagrams in realistic environments. We conclude by summarizing the remaining challenges in the thermodynamic modeling of materials corrosion and promising future research directions.

Stabilization and self-passivation of symmetrical grain boundaries by mirror symmetry breaking

While computational methods for the study of point defects in materials have received significant attention, methods for the investigation of grain boundaries require further development. In this study, we applied a genetic algorithm to find the atomic structure of grain boundaries in semiconductor materials with given Miller indices and investigated their electronic structure. Our study of the {\Sigma}3 (112) grain boundary in CdTe shows that the stability of grain boundaries can be greatly enhanced by breaking mirror symmetry, locally or globally. The resulting grain boundary can be electrically less harmful because the origin of the defect levels are removed from the middle of the band gap and the grain boundaries can serve as a channel for electron extraction.

CoFFEE: Corrections For Formation Energy and Eigenvalues for charged defect simulations

Charged point defects in materials are widely studied using Density Functional Theory (DFT) packages with periodic boundary conditions. The formation energy and defect level computed from these simulations need to be corrected to remove the contributions from the spurious long-range interaction between the defect and its periodic images. To this effect, the CoFFEE code implements the Freysoldt–Neugebauer–Van de Walle (FNV) correction scheme. The corrections can be applied to charged defects in a complete range of material shapes and size: bulk, slab (or two-dimensional), wires and nanoribbons. The code is written in Python and features MPI parallelization and optimizations using the Cython package for slow steps. Program summaryProgram title: CoFFEEProgram Files doi:http://dx.doi.org/10.17632/s2x4d542dc.1Licensing provisions: BSD 3-clauseProgramming language: PythonExternal routines/libraries: numpy, scipy, mpi4py, matplotlibNature of problem: Most electronic structure codes based on Density Functional Theory use periodic boundary conditions. This leads to spurious electrostatic interactions during simulation of charged defects, which affects the computed defect formation energy and the defect eigenvalue.Solution method: We implement the Freysoldt–Neugebauer–Van de Walle (FNV) correction scheme to correct the defect formation energy and eigenvalues. Our implementation can be applied to charged defects in 3D bulk materials as well as materials having 2D and 1D geometries.

Positron annihilation spectroscopy study of lattice defects in non-irradiated doped and un-doped fuels

Fission gas behavior within the fuel structure plays a major role for the safety of nuclear fuels during operation in the nuclear power plant. Fission gas distribution and retention is determined by both, micro- and lattice-structure of the fuel matrix. The ADOPT (Advanced Doped Pellet Technology) fuel, containing chromium and aluminum additives, shows larger grain sizes than standard (undoped) UO2 fuel, enhancing the fission gas retention properties of the matrix. However, the additions of such trivalent cations shall also induce defects in the lattice. In this study, we investigated the microstructure of such doped fuels as well as a reference standard UO2 by positron annihilation spectroscopy (PAS). Although this technique is particularly sensitive to lattice point defects in materials, a wider application in the UO2 research is still missing. The PAS-lifetime components were measured in the hotlab facility of PSI using a 22 Na source sandwiched between two 500-μ m-thin sample discs. The values of lifetime at the center and the rim of both samples, examined to check at the radial homogeneity of the pellets, are not significantly different. The mean lifetimes were found to be longer in the ADOPT material, 220 ps, than in standard UO2 , 190 ps, which indicates a larger presence of additional defects, presumably generated by the dopants. While two-component decomposition (bulk + one defect component) could be performed for the standard material, only one lifetime component was found in the doped material. The absence of the bulk component in the ADOPT sample refers to a saturated positron trapping (i.e., all positrons are trapped at defects). In order to associate a type of lattice defect to each PAS component, interpretation of the PAS experimental observations was conducted with respect to existing experimental and modeling studies. This work has shown the efficiency of PAS to detect lattice point defects in UO2 produced by Cr and Al oxides. These additives create lattice irregularities, which are acting as sinks for fission products on one hand and trapping positrons on the other hand. Fitting of the obtained experimental data with a suitable theoretical model can provide a valuable qualitative assessment of these defects. At this stage of the research, some of the existing models were used for this purpose.

Optimizing the primary knock-on atom for simulating particle radiation-induced structural damage in Zr-based metals

Molecular dynamics (MD) can simulate the production of radiation-induced point defects in materials. However, the initial conditions of one “hypothetical” primary knock-on atom (PKA) which starts the MD simulation usually are simplified. In the present work, we aim to obtain the optimized initial conditions of PKA by using the Geant4 software which can simulate the passage of particles through matter. We find that the spectra of kinetic energies of PKAs are similar with each other among pure Zr, Zr2Cu, and Zr2Ni. This indicates that adopting simplified structural models can approximate the atomic-level structural damage in some corresponding served nuclear materials, such as Zr-based and Fe-based alloys. In addition, it is revealed that the moving directions of PKAs strongly relate to the kinetic energies of neutrons, and the corresponding preferred scattering angles of PKAs could be estimated. These findings are helpful for optimizing the initial conditions of MD simulation, and extend our understanding on simulating structural damage in nuclear materials accordingly.

Signatures of distinct impurity configurations in atomic-resolution valence electron-energy-loss spectroscopy: Application to graphene

The detection and identification of impurities and other point defects in materials is a challenging task. Signatures for point defects are typically obtained using spectroscopies without spatial resolution. Here in this paper, we demonstrate the power of valence electron-energy-loss spectroscopy (VEELS) in an aberration-corrected scanning transmission-electron microscope (STEM) to provide energy-resolved and atomically resolved maps of electronic excitations of individual impurities which, combined with theoretical simulations, yield unique signatures of distinct bonding configurations of impurities. We report VEELS maps for isolated Si impurities in graphene, which are known to exist in two distinct configurations. We also report simulations of the maps, based on density functional theory and dynamical scattering theory, which agree with and provide direct interpretation of observed features. We show that theoretical VEELS maps exhibit distinct and unambiguous signatures for the threefold- and fourfold-coordinated configurations of Si impurities in different energy-loss windows, corresponding to impurity-induced bound states, resonances, and antiresonances. With the advent of new monochromators and detectors with high energy resolution and low signal-to-noise ratio, the present work ushers an atomically resolved STEM-based spectroscopy of individual impurities as an alternative to conventional spectroscopies for probing impurities and defects.

Iterated Boolean random varieties and application to fracture statistics models

Models of random sets and of point processes are introduced to simulate some specific clustering of points, namely on random lines in R2 and R3 and on random planes in R3. The corresponding point processes are special cases of Cox processes. The generating distribution function of the probability distribution of the number of points in a convex set K and the Choquet capacity T (K) are given. A possible application is to model point defects in materials with some degree of alignment. Theoretical results on the probability of fracture of convex specimens in the framework of the weakest link assumption are derived, and used to compare geometrical effects on the sensitivity of materials to fracture.

Positron annihilation lifetime spectroscopy source correction determination: A simulation study

Positron annihilation lifetime spectroscopy (PALS) can provide sensitive detection and identification of vacancy-related point defects in materials. These measurements are normally performed using a positron source supported, and enclosed by, a thin foil. Annihilation events from this source arrangement must be quantified and are normally subtracted from the spectrum before analysis of the material lifetime components proceeds. Here simulated PALS spectra reproducing source correction evaluation experiments have been systematically fitted and analysed using the packages PALSfit and MELT. Simulations were performed assuming a single lifetime material, and for a material with two lifetime components. Source correction terms representing a directly deposited source and various foil supported sources were added. It is shown that in principle these source terms can be extracted from suitably designed experiments, but that fitting a number of independent, nominally identical, spectra is recommended.

Computational prediction of lattice defects in multinary compound semiconductors as photovoltaic materials

In the past 60 years development of photovoltaic semiconductors, the number of component elements has increased steadily, i.e., from silicon in the 1950s, to GaAs and CdTe in the 1960s, to CuInSe2 in the 1970s, to Cu(In, Ga) Se2 in the 1980s, to Cu2ZnSnS4 in the 1990s, and to recent Cu2ZnSn(S, Se)4 and CH3NH3PbI3. Whereas the material properties become more flexible as a result of the increased number of elements, and multinary compound semiconductors feature a dramatic increase of possible point defects in the lattice, which can significantly influence the optical and electrical properties and ultimately the photovoltaic performance. It is challenging to characterize the various point defects and defect pairs experimentally. During the last 20 years, first-principles calculations based on density functional theory (DFT) have offered an alternative method of overcoming the difficulties in experimental study, and widely used in predicting the defect properties of semiconductors. Compared with the available experimental methods, the first-principles calculations are fast, direct and exact since all possible defects can be investigated one by one. This advantage is especially crucial in the study of multinary compound semiconductors which have a large number of possible defects. Through calculating the formation energies, concentration and transition (ionization) energy levels of various possible defects, we can study their influences on the device performance and then identify the dominant defects that are critical for the further optimization of the performance. In this paper, we introduce the first-principles calculation model and procedure for studying the point defects in materials. We focus on the hybrid scheme which combines the advantages of both special k-points and -point-only approaches. The shortcomings of the presentcalculation model are discussed, with the possible solutions proposed. And then, we review the recent progress in the study of the point defects in two types of multinary photovoltaic semiconductors, Cu2ZnSn(S,Se)4 and H3NH3PbI3. The result of the increased number of component elements involves various competing secondary phases, limiting the formation of single-phase multinary compound semiconductors. Unlike ternary CuInSe2, the dominant defect that determines the p-type conductivity in Cu2ZnSnS4 is Cu-on-Zn antisite (CuZn) defect rather than the copper vacancy (VCu). However, the ionization level of CuZn is deeper than that of VCu. The self-compensated defect pairs such as [2CuZn+SnZn] are easy to form in Cu2ZnSnS4, which causes band gap fluctuations and limits the Voc of Cu2ZnSnS4 cells. Additionally the formation energies of deep level defects, SnZn and VS, are not sufficiently high in Cu2ZnSnS4, leading to poor lifetime of minority carriers and hence low Voc. In order to enhance the formation of VCu and suppress the formation of CuZn as well as deep level defects, a Cu-poor/Zn-rich growth condition is required. Compared with Cu2ZnSnS4, the concentration of deep level defects is predicted to be low in Cu2ZnSnSe4, therefore, the devices fabricated based on the Se-rich Cu2ZnSn(S,Se)4 alloys exhibit better performances. Unlike Cu2ZnSnS4 cells, the CH3NH3PbI3 cells exhibit rather high Voc and long minority-carrier life time. The unusually benign defect physics of CH3NH3PbI3 is responsible for the remarkable performance of CH3NH3PbI3 cells. First, CH3NH3PbI3 shows that flexible conductivity is dependent on growth condition. This behavior is distinguished from common p-type photovoltaic semiconductor, in which the n-type doping is generally difficult. Second, in CH3NH3PbI3, defects with low formation energies create only shallow levels. Through controlling the carrier concentration (Fermi level) and growth condition, the formation of deep-level defect can be suppressed in CH3NH3PbI3. We conclude that the predicted results from the first-principles calculations are very useful for guiding the experimental study.

Doping and Defect Chemistry in LiCoO2 By First-Principles Calculation

Introduction In order to improve the performance of lithium-ion batteries, doping to electrode active materials is often carried out. The doped ions are extrinsic point defects in the active materials, and thus the doping exerts an influence on native point defects in the materials. Since the point defects are associated with many properties of the active materials, information on the doped ions as well as the native defects is of importance to control the materials. In this study, we made comprehensive first-principles calculations to estimate solubility of various species doped into LiCoO2and to discuss effects of the doping on the defect chemistry. Computation method As the doped species to LiCoO2, several metals such as Na, Mg, and Al, were selected. Both the Li and Co sites were considered as the substitution positions of the doped ions. Vacancies, interstitial cations and antisite cations were examined as the native defects. Defect formation energy was evaluated by first-principles calculations using a supercell consisting of 144 atoms with a single defect. The first-principles calculations were carried out using the plain-wave basis PAW method and the GGA+U exchange correlation functional. Equilibrium defect concentrations were estimated by the Boltzmann distribution under given chemical conditions and charge neutrality. Results and discussion Figure 1(a) illustrates equilibrium defect concentrations in Al-doped LiCoO2 as a function of temperature when LiCoO2 coexists with LiAlO2 and Li5AlO4 under an oxygen pressure of 0.2 atm. Al preferentially substitutes for Co (AlCo) as shown in the figure, and thus this condition can be considered as a nominal composition of Li(Al x Co1-x )O2 with a small amount of excess Li. At this chemical condition, one can expect high Al solubility of ~50% with low concentrations (<1%) of the native defects such as CoLi under usual synthetic conditions (800-900 °C in air). Since defect formation energy and equilibrium defect concentration depend on the chemical condition, more Li-rich and Al-rich conditions were also examined. Figure 1(b) illustrates equilibrium defect concentrations at the more Li-rich condition, where LiCoO2 coexists with Li2O and Li5AlO4. At this condition, the concentration of AlCo is less than 10%. This is because excess Li reacts with Al, resulting in suppression of the Al-doping to LiCoO2. On the other hand, when LiCoO2 coexists with LiAlO2 and CoAl2O4 as the Al-rich condition, the concentration of CoLi becomes ~6% at 1100 K as shown in Fig. 1(c). The Al-rich condition means Li-poor condition, and thus Li deficiency in LiCoO2 is increased. These calculations suggest that the chemical conditions are of great importance to achieve both the increase in the Al solubility and the suppression of the Li deficiency. The solubility and effects on the defect chemistry of other species are discussed at the meeting. Acknowledgement This work was supported by RISING project of NEDO.

Temperature dependence of the point defect properties of GaN thin films studied by terahertz time-domain spectroscopy

The dielectric functions of GaN for the temperature and frequency ranges of 10-300 K and 0.3-1 THz are obtained using terahertz time-domain spectroscopy. It is found that there are oscillations of the dielectric functions at various temperatures. Physically, the oscillation behavior is attributed to the resonance states of the point defects in the material. Furthermore, the dielectric functions are well fitted by the combination of the simple Drude model together with the classical damped oscillator model. According to the values of the fitting parameters, the concentration and electron lifetime of the point defects for various temperatures are determined, and the temperature dependences of them are in accordance with the previously reported result. Therefore, terahertz time-domain spectroscopy can be considered as a promising technique for investigating the relevant characteristics of the point defects in semiconductor materials.

Determination of effective charge states for point radiation defects in fusion ceramic materials

Point defects in fusion ceramic materials under irradiation can have an effective charge due to ionization and covalent chemical bonding. The kinetics of charged point defects in these materials is determined by their effective charge and this kinetics is completely different from non-charged point defects in metals. The experimental investigation of point defect charge states in ceramic materials is rather difficult. In this paper, a new method is proposed for the investigation of charge states of point defects in irradiated ceramic materials. This method is based on a new theoretical model and experimental observations of defect cluster formation near permanent sinks, such as grain boundaries. Previous experimental investigations show that a denuded zone is formed in irradiated ceramic materials near free surfaces and grain boundaries. The effect of an applied electric field on the formation of interstitial-type point defect clusters (dislocation loops) near grain boundaries in irradiated ceramic materials is investigated. For this purpose a new theoretical model is suggested, which takes into account the effect of an applied electric field on the denuded zone formation. It is shown that the denuded zone size depends on point defect charge and direction of applied electric field. The obtained theoretical results are compared with experimental data.