Point Defects Research Articles

Enabling defect control or polyiodide formation regimes in halide perovskites

Defect engineering in oxide materials is typically achieved through manipulation of oxygen pressure and temperature, followed by quenching which freezes the concentration of point defects. Unlike oxides, halide perovskites equilibrate with gaseous atmosphere at room temperature. Information on defect engineering in halide perovskites that utilize the concentration of gaseous species is scarce and controversial. In this report we address this controversy by studying the interaction of MAPbI3 with molecular iodine over a wide range of partial pressures and reveal the two regimes of such interaction: defect control regime and polyiodide formation regime switching at ∼20 % of the saturated iodine pressure. In defect control regime the material undergoes reversible changes in semiconductor properties, while in polyiodide formation regime the material undergoes irreversible changes in crystallinity and microstructure. These findings emphasize the manifold role of molecular iodine for this class of materials and provides researchers with the experimental framework that can be utilized to tune stoichiometry and conductivity of halide perovskites to further enhance the performance and stability metrics of the corresponding devices.

Insight into insulation degradation mechanism of Al2O3 involved with positive and negative defects

Al2O3 with the desired electrical insulating properties and thermal shock resistivity has been extensively applied in the field of solid oxide fuel cells and oxygen sensors. However, degradation of the insulating Al2O3 layer is an intractable issue in practical applications. In this study, different point defect structures of Al2O3 were realized with the substitutional doping effect of ZrO2 and MgO. The MgO dopant provides positively charged oxygen vacancies, whereas the ZrO2 dopant tends to trigger negatively charged vacancy formation at Al3+ sites. The oxygen vacancy concentration of Al2O3 exhibits the following trend: MgO-doped Al2O3 > Al2O3 > ZrO2-doped Al2O3. Furthermore, the densification morphology, insulating properties, and oxygen vacancy migration of Al2O3 have been confirmed to be largely affected by the extrinsic factors. This study indicates that oxygen vacancy migration depends on the applied electric field at high temperatures. As the voltage and temperature increase, oxygen vacancy migration shows obvious electric-field-dependent characteristics, and its aggregation macroscopically shows hole defects. The defect position of Al2O3 is nonstoichiometric Al2O3-x with poor crystallinity. Therefore, it is believed that the oxygen vacancy migration triggered by the second phase directly determines the insulation performance and causes the degradation of Al2O3 materials.

Rapid Characterization of Point Defects in Solid-State Ion Conductors Using Raman Spectroscopy, Machine-Learning Force Fields, and Atomic Raman Tensors.

The successful design of solid-state photo- and electrochemical devices depends on the careful engineering of point defects in solid-state ion conductors. Characterization of point defects is critical to these efforts, but the best-developed techniques are difficult and time-consuming. Raman spectroscopy─with its exceptional speed, flexibility, and accessibility─is a promising alternative. Raman signatures arise from point defects due to local symmetry breaking and structural distortions. Unfortunately, the assignment of these signatures is often hampered by a shortage of reference compounds and corresponding reference spectra. This issue can be circumvented by calculation of defect-induced Raman signatures from first principles, but this is computationally demanding. Here, we introduce an efficient computational procedure for the prediction of point defect Raman signatures in solid-state ion conductors. Our method leverages machine-learning force fields and "atomic Raman tensors", i.e., polarizability fluctuations due to motions of individual atoms. We find that our procedure reduces computational cost by up to 80% compared to existing first-principles frozen-phonon approaches. These efficiency gains enable synergistic computational-experimental investigations, in our case allowing us to precisely interpret the Raman spectra of Sr(Ti0.94Ni0.06)O3-δ, a model oxygen ion conductor. By predicting Raman signatures of specific point defects, we determine the nature of dominant defects and unravel impacts of temperature and quenching on in situ and ex situ Raman spectra. Specifically, our findings reveal the temperature-dependent distribution and association behavior of oxygen vacancies and nickel substitutional defects. Overall, our approach enables rapid Raman-based characterization of point defects to support defect engineering in novel solid-state ion conductors.

Scalable crystal structure relaxation using an iteration-free deep generative model with uncertainty quantification

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and super large twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax’s reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science.

Study on growth kinetics of passivation film of Ti-6Al-3Nb-2Zr-1Mo alloy Based on point defect model

This study aims to explore the passivation behavior and growth mechanism of the Ti-6Al-3Nb-2Zr-1Mo alloy in an oxygen-free environment, taking into account various film-forming potentials and solution pH levels in the process. The point defect model is employed to study the growth mechanism of the passivation film. A film-forming potential is selected within the stable passivation region for polarization, followed by conventional electrochemical tests, Localized Electrochemical Impedance Spectroscopy, X-ray photoelectron spectroscopy characterization, and Glow Discharge Optical Emission Spectrometry. Experimental findings indicate that the passivation film on the Ti-6Al-3Nb-2Zr-1Mo alloy surface demonstrates characteristics of an n-type semiconductor. Increasing the film-forming potential leads to a decrease in the donor point defect density. Meanwhile, elevating the pH of the solution decreases the oxygen vacancy diffusion coefficient from 7.8 × 1019 to 4.3 × 1019, thus improving the corrosion resistance of the passivation film.

A combined transport-defect evolution model of microstructure damage in silicon carbide induced by precise irradiation of focused helium ion beams

In this paper, a combined transport-defect evolution multiscale model describing the generation and the evolution of microstructure damage in silicon carbide (SiC) induced by focused helium ion beams is developed. In the proposed model, the transport of helium ions and displaced atoms in the SiC substrate and the generation of point defects are described by the Boltzmann transport equations, while the subsequent defect evolution is characterized by a set of rate equations with the contributions of the modeling of the bubble coalescence as well as the substrate swelling. The validity and superiority of the transport equations are verified by comparing the simulation results with the data from experimental measurements and available simulation methods. The subsurface amorphous profile, onsurface swelling profile, and the spatial and size distribution of helium bubbles in a SiC substrate irradiated by focused helium ion beams are simulated using the proposed multiscale model. The damage morphology simulated by the proposed model is in good agreement with the transmission electron microscopy images at different beam energies and doses. This work provides an effective tool for full-stage modeling of complex evolutionary mechanisms of microstructure damage induced by precise and high-throughput helium irradiation.

Particle-Particle Random Phase Approximation for Predicting Correlated Excited States of Point Defects.

The particle-particle random phase approximation (ppRPA) within the hole-hole channel was recently proposed as an efficient tool for computing excitation energies of point defects in solids [J. Phys. Chem. Lett. 2024, 15, 2757-2764]. In this work, we investigate the application of ppRPA within the particle-particle channel for predicting correlated excited states of point defects, including the carbon-vacancy (VC) in diamond, the oxygen-vacancy (VO) in magnesium oxide (MgO), and the carbon dimer defect (CBCN) in two-dimensional hexagonal boron nitride (h-BN). Starting from a density functional theory calculation of the (N - 2)-electron ground state, vertical excitation energies of the N-electron system are obtained as the differences between the two-electron addition energies. We show that active-space ppRPA with the B3LYP functional yields accurate excitation energies, with errors mostly smaller than 0.1 eV for tested systems compared to available experimental values. We further develop a natural transition orbital scheme within ppRPA, which provides insights into the multireference character of defect states. This study, together with our previous work, establishes ppRPA as a low-cost and accurate method for investigating excited-state properties of point defect systems.

Dynamic Deformation in Nuclear Graphite and Underlying Mechanisms.

Time-dependent deformation in nuclear graphite is influenced by the creation and migration of radiation-induced defects in the reactor environment. This study investigates the role of pre-existing defects such as point defect clusters and Mrozowski cracks in nuclear graphite IG-110. Separate specimens were irradiated with a 2.8 MeV Au2+ beam with a fluence of 4.38 × 1014 cm-2 and an 8 MeV C2+ beam with a fluence of 1.24 × 1016 cm-2. Microscopic specimens were either mechanically loaded inside a transmission electron microscope (TEM) or subjected to ex situ indentation-based creep loading. In situ TEM tests showed significant plasticity in regions highly localized around the Mrozowski cracks, resembling slip or ripplocation bands. Slip bands were also seen near regions without pre-existing defects but at very high stresses. Ex situ self-ion irradiation embrittled the specimens and decreased the creep displacement and rate, while heavy ion irradiation resulted in the opposite behavior. We hypothesize that the large-sized gold ions (compared to the carbon atoms) induced interplanar swelling as well as cross-plane channels for increased defect mobility. These findings illustrate the role of pre-existing defects in the dynamic relaxation of stresses during irradiation and the need for more studies into the radiation environment's impact on the mechanical response of nuclear graphite.

A unified moment tensor potential for silicon, oxygen, and silica

Si and its oxides have been extensively explored in theoretical research due to their technological importance. Simultaneously describing interatomic interactions within both Si and SiO2 without the use of ab initio methods is considered challenging, given the charge transfers involved. Herein, this challenge is overcome by developing a unified machine learning interatomic potentials describing the Si/SiO2/O system, based on the moment tensor potential (MTP) framework. This MTP is trained using a comprehensive database generated using density functional theory simulations, encompassing diverse crystal structures, point defects, extended defects, and disordered structure. Extensive testing of the MTP is performed, indicating it can describe static and dynamic features of very diverse Si, O, and SiO2 atomic structures with a degree of fidelity approaching that of DFT.

Controlled Phonon Transport via Chemical Bond Stretching and Defect Engineering: The Case Study of Filled β-Mn-Type Phases.

Controlling the elastic properties of the material could become a powerful tool for tuning the thermal transport in solids. Nevertheless, the impact of the crystal structure, chemical bonding, and elastic properties on the lattice thermal conductivity remains to be elucidated. This is a pivotal issue for the advancement of thermoelectric (TE) materials. In this context, the influence of cation substitution in tetrahedral voids on the structural, thermal, and TE properties of α- and β-PbyGa6-xInxTe10─filled β-Mn-type phases─is reported here. The investigated materials show semiconducting behavior and a change from p- to n-type conductivity, depending on the chemical composition and temperature. Our findings indicate that the electronic transport in β-Mn-type phases is largely influenced by the substantial distortion of the Te framework, which causes the low weighted mobility and strong scattering of charge carriers. The presence of a significant anharmonicity of lattice vibrations results in the ultralow lattice thermal conductivity of PbyGa6-xInxTe10 materials. With increasing x, κL decreases from 0.59 to an extremely low value of 0.36 W m-1 K-1 at 298 K due to the decrease of bonding energy, intensification of anharmonic thermal vibrations of atoms, and formation of point defects. This work demonstrates the efficacy of utilizing the crystal structure and elastic properties to regulate phonon transport in functional materials.

Heterogeneity in Point Defect Distribution and Mobility in Solid Ion Conductors.

Alkali metal anodes paired with solid ion conductors offer promising avenues for enhancing battery energy density and safety. To facilitate rapid ion transport crucial for fast charging and discharging of batteries, it is essential to understand the behavior of point defects in these conductors. In this study, we investigate the heterogeneity of defect distribution in two prototypical solid ion conductors, Li3OCl and Li2PO2N (LiPON), by quantifying the defect formation energy (DFE) as a function of distance from the surface and interface through first-principles simulations. To simulate defects at the electrode-electrolyte interface, we perform calculations of Li+ vacancy in Li3OCl near its interface with lithium metal. Our results reveal a significant difference between the bulk and surface/interface DFE which could lead to defect aggregation/depletion near the surface/interface. Interestingly, while Li3OCl has a lower surface DFE than the bulk in most cases, LiPON follows the opposite trend with a higher surface DFE compared to the bulk. Due to this difference between bulk and surface DFE, the defect density can be up to 14 orders of magnitude higher at surfaces compared to the bulk. Further, we reveal that the DFE transition from surface/interface to bulk is precisely characterized by an exponentially decaying function. By incorporating this exponential trend, we develop a revised model for the average behavior of defects in solid ion conductors that offers a more accurate description of the influence of grain sizes. Surface effects dominate for grain sizes ≲1 μm, highlighting the importance of surface defect engineering and the DFE function for accurately capturing ion transport in devices. We further explore the kinetics of defect redistribution by calculating the migration barriers for defect movement between bulk and surfaces. We find a highly asymmetric energy landscape for the lithium vacancies, exhibiting lower migration barriers for movement toward the surface compared to the bulk, while interstitial defects exhibit comparable kinetics between surface and bulk regions. These insights highlight the importance of considering both thermodynamic and kinetic factors in designing solid ion conductors for improved ion transport at surfaces and interfaces.

Mobile intrinsic point defects for conductive neutral domain walls in LiNbO3.

Conductive ferroelectric domain walls (DWs) hold great promise for neuromorphic nanoelectronics as they can contribute to realize multi-level diodes and nanoscale memristors. Point defects accumulating at DWs will change the local electrical transport properties. Hence, local, inter-switchable n- and p-type conductivity at DWs can be achieved through point defect population control. Here, we study the impact of point defects on the electronic structure at neutral domain walls in LiNbO3 by density functional theory (DFT). Segregation of Li and O vacancies was found to be energetically favourable at neutral DWs, implying that charge-compensating electrons or holes can give rise to n- or p-type conductivity. Changes in the electronic band gap and defect transition levels are discussed with respect to local property engineering, opening the pathway for reversible tuning between n- and p-type conduction at neutral ferroelectric DWs. Specifically, the high Curie temperature of LiNbO3 and the significant calculated mobility of O and Li vacancies suggest that thermal annealing and applied electric fields can be used experimentally to control point defect populations, and thus enable rewritable pn-junctions.

First-principles study of Re in BCC-Mo: Diffusion behavior and interaction with point defects

Due to their some beneficial properties, molybdenum-based alloys, such as Mo-Re alloys, are recognized as potential structural materials for nuclear power reactors. Irradiation induced precipitation of rhenium (Re) atoms causes hardening and embrittlement of Mo-Re alloys, restricting their application. The interaction of rhenium (Re) atoms with point defects (PDs), as well as the diffusion behavior of Re atoms in BCC-Mo (Body Center Cubic-molybdenum), were investigated using first-principles methods. The results revealed that Re atoms exhibited high binding energies with both vacancy (Vac) and interstitial dumbbells. Furthermore, the binding energies increased with the number of Re atoms. The binding energies of Re with self-interstitial dumbbell (SIA, ie., Mo-Mo) and mixed interstitial dumbbell (Mo-Re) were quite close to. Due to the high exchange barrier between Vac and Re, the diffusion of rhenium through the vacancy-drag mechanism was difficult. Due to the low migration and rotation barrier of Mo-Re mixed interstitial dumbbell, the diffusion of Re atoms in Mo was dominated by the interstitial-mediated mechanism. From the perspective of diffusion dynamics, only interstitial dumbbells can promote the aggregation of Re atoms. By comparing the binding energy of interstitial dumbbell with interstitial dumbbell and interstitial dumbbell with Re atoms, pairs of Mo-Re interstitial dumbbell was suggested to be the nucleation sites to attract more interstitial dumbbells, thereby promoting the precipitation of Re clusters. It was because they had high binding energy and were difficult to decompose once combined.

Many-defect solutions in planar nematics: interactions, spiral textures and boundary conditions.

From incompressible flows to electrostatics, harmonic functions can provide solutions to many two-dimensional problems and, similarly, the director field of a planar nematic can be determined using complex analysis. We derive a closed-form solution for a quasi-steady state director field induced by an arbitrarily large set of point defects and circular inclusions with or without fixed rotational degrees of freedom, and compute the forces and torques acting on each defect or inclusion. We show that a complete solution must include two types of singularities, generating a defect winding number and its spiral texture, which have a direct effect on defect equilibrium textures and their dynamics. The solution accounts for discrete degeneracy of topologically distinct free energy minima which can be obtained by defect braiding. The derived formalism can be readily applied to equilibrium and slowly evolving nematic textures for active or passive fluids with multiple defects present within the orientational order.

Linear dependence of potential drop at the passive film/solution interface on film-formation potential and pH: Combining first-principles calculations with experiments

Potential drop at the oxide film/solution interface plays a critical part in numerous electrochemical processes, especially for the passivated metal-electrolyte system, affecting the passive film breakdown and the pitting initiation. There are still some controversies over the dependence of potential drop at the passive film/solution interface (φf/s) on potential and pH of electrolyte. Herein, we develop a model presenting the linear dependence of φf/s on both potential and pH, as represented by φf/s=φf/s(V=0,pH=0)0+αV+βpH. By analyzing the surface charge (i.e., point of zero charge, pHpzc) and performing first-principles calculations, we provide the insights into the effect of potential and pH on the φf/s, and into the linear relation between φf/s with pH beyond the Nernst relation that is attributed to the role of point defects in pHpzc of passive film on iron. In addition, two methods, e.g., a combination of Mott-Schottky measurement with first-principles, contact angle titration, are suggested to determine the values of α, β and φf/s(V=0,pH=0)0, respectively. The study of passivity of iron in borate buffer solutions validates our model.

Hydrogen interactions with intrinsic point defects and hydrogen diffusion in tungsten doped Al2O3

In light of the extensive use of tungsten (W) in fusion experimental devices and the importance of hydrogen isotopes permeation, based on the first principle approaches we study the effects of W doping on the formation energies of intrinsic point defects, hydrogen interactions with such defects, and hydrogen diffusion in bulk of α-Al2O3. Our investigation demonstrated that W doping enhances the formation of oxygen and aluminum vacancies (Vo and VAl) in α-Al2O3. In W doping α-Al2O3, hydrogen primarily exists in the form of Ho− (hydrogenation of the bulk VO3−) and Hi− (H interstitial) defects, while it hardly occupies VAl. Hydrogen is firmly trapped by Vo with a formation energy −3.35eV, and Hi− diffusion become extremely challenging because W doping significantly raises the Hi− diffusion barrier to 4.44 eV. Our findings indicate that W doping is beneficial for hydrogen permeation resistance in α-Al2O3.

Synergistic strategy via modulated energy filtering and hierarchical defects evolution for high performance GeTe thermoelectrics

GeTe thermoelectric materials are very promising for sustainable waste-heat harvesting, while optimizations have been focusing on lowering lattice thermal conductivity or decreasing carrier concentration. As a long-pursued strategy to improve electronic transport properties, the full realization of effective energy filtering has been hindered by the mismatch between the energy barriers introduced and the intrinsic Fermi level of the matrix material. In this work, a synergistic strategy combining modulated energy filtering effect and hierarchical defect evolution engineering leads to ultrahigh performance GeTe-based thermoelectric materials. Very effective energy filtering is achieved by incorporating carbon fibers, which increases the overall energy of charge carriers. This greatly enhances Seebeck coefficient to over 230 μVK-1 with minor reduction in electrical conductivity which simultaneously decreases electronic thermal conductivity. Furthermore, the inclusion of carbon fibers modulates the microstructure of GeTe and facilitates the evolution of point defects to higher dimensional defects for broadband phonon scattering, greatly suppressing the lattice thermal conductivity to 0.3 Wm-1K-1. This strategy yields a prominent thermoelectric figure of merit ZTmax ∼ 2.3 and an exceptional quality factor Bmax ∼ 2.24 for Ge0.97Bi0.07Te with 0.9 wt% carbon fibers. This study demonstrates a promising strategy to modulate the convoluted thermoelectric properties for ultrahigh performance thermoelectric materials.

Defect-Induced Sensitivity Improvement in HfNBr Monolayers for Ammonia Detection.

Two-dimensional materials, owing to their unique physical properties and high surface area, play a crucial role in intelligent sensing, particularly in the domain of atmospheric pollutant monitoring. In this work, we have extensively investigated the gas-sensing capabilities of the HfNBr monolayer for ammonia detection by introducing point defects, utilizing density functional theory and nonequilibrium Green's function calculations. Upon the introduction of point defects, the adsorption energy of HfNBr monolayers for ammonia significantly increased (from -0.162 to -1.257 eV), indicating a markedly strengthened affinity. To further elucidate the sensing mechanism, we conducted an in-depth investigation into the charge transfer dynamics, the density of states, and the charge density difference between the adsorbent and the adsorbate. Besides, we employed the NEGF method to evaluate the changes in the current-voltage characteristics of the HfNBr monolayer before and after adsorption, which revealed a remarkable change in the apparent resistance, thereby demonstrating excellent sensitivity. The exceptional performance of the HfNBr monolayer toward NH3 demonstrates its significant value in practical applications for ammonia detection.

Scandium-based point defect in AlN for quantum information processing

Scandium-based point defect in AlN for quantum information processing

Diffusion mechanisms for spinel ferrite NiFe2O4 by using kinetic activation-relaxation technique.

Mass transport in bulk spinel ferrites NiFe2O4 is studied computationally using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo algorithm. Diffusion mechanisms-difficult to observe with molecular dynamics-are described by k-ART. Point defects are assumed to be responsible for ionic diffusion; thus, both cation and anion defects are investigated. This work focuses on vacancies and interstitials by comparing their properties with two Buckingham potential parameterizations: one with nominal charges and the other with partial charges. Both potentials are corrected at short distances, thus allowing interstitial diffusion and avoiding the catastrophic infinite energies appearing with Buckingham at short distances. The energy landscape along different pathways is described in detail. Both potentials predict the same mechanisms but different migration energies. Mechanisms by which a normal spinel is transformed to an inverse spinel via cation diffusion are unveiled, and diffusion coefficients are predicted. We find that interstitial Ni diffusion involves the movement of two Ni ions and that O interstitials trigger a collective diffusion of O ions, while an O vacancy diffuses by an O ion moving to the center of a cuboctahedron.