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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) v.0

SAND2024-08598O The Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) characterizes nitrogen-vacancy centers in diamond and other defects. It does this by using a radio frequency system-on-a-chip (RFSoC) field programmable gate array (FPGA). QICKDAWG synthesizes microwave pulses from the RFSoC to change the spin state of the defects. The software also allows for laser control using the RFSoC, which optically pumps defects. Ultimately, QICKDAWG supports the implementation of RFSoC FPGAs in defect characterization. This replaces the slow, expensive, traditional hardware, thus lowering the cost and time for defect characterization. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2022

Irradiation-Induced Defect Evolution in Nuclear Graphite

Graphite has historically been used as a moderator material in nuclear reactor designs dating back to the first man-made nuclear reactor to achieve criticality (Chicago Pile 1) in 1942. Additionally, graphite is a candidate material for use in the future envisioned next-generation nuclear reactors (Gen IV); specifically, the molten-salt-cooled (MSR) and very-high-temperature reactor (VHTR) concepts. Gen IV reactor concepts will introduce material challenges as temperature regimes and reactor lifetimes are anticipated to far exceed those of earlier reactors. Irradiation-induced defect evolution is a fundamental response in nuclear graphite subjected to irradiation. These defects directly influence the many property changes of nuclear graphite subjected to displacing radiation; however, a comprehensive explanation for irradiation-induced dimensional change remains elusive. The objectives of this project were focused on the characterization of irradiation-induced defect evolution in nuclear graphite via transmission electron microscopy (TEM). With the use of novel TEM specimen preparation techniques, high-temperature electron-irradiation and characterization of high-temperature neutron-irradiated nuclear graphite, novel fullerene-like defects are shown to be a dominant defect type, especially at higher temperatures. These results contradict the historical models of defect evolution and provide valuable insight into the macroscopically observed property changes in irradiated nuclear graphite.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Report on PTT Imaging of Defects in AM Metallic Materials-Part 2

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An Analytical Tool to Evaluate Defect Thermodynamics of (La,Ba)Fe1-xMxO3-δ Perovskites for Solid-Oxide Cell Applications

A modeling tool of the defect thermodynamics of (La,Ba)Fe1-xMxO3-δ perovskites which includes energetic information about oxygen vacancy formation, hydration, hydride formation, and charge disproportionation reactions has been developed1. This tool incorporates defect energies and entropies expressed as sixth order polynomial functions to allow refinements of the defect reaction equilibrium constants in the thermodynamic analysis. Calculation of (La,Ba)Fe1-xMxO3-δ Brouwer diagrams as a function of pO2/pH2O and pH2/H2O in a range of temperatures of interest is facilitated by this modeling tool. The results obtained can provide direct guidance how the electronic and ionic defect concentrations of the triple conducting perovskite materials can be used to optimize performance of solid oxide cells for energy applications. The impact of magnetic and electronic structures of the perovskites on the defect reaction energies and entropies as obtained from density function theory modeling and the role played by hydride defect species will also be discussed.

Lee, Yueh-Lin↗
DOE OSTI2022

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.

Hirst, Charles A.↗
DOE OSTI2025

Intrinsic Defect-Induced Local Semiconducting-to-Metallic Regions Within Monolayer 1T-TiS2 Displayed by First-Principles Calculations and Scanning Tunneling Microscopy

Using density functional theory (DFT) and scanning tunneling microscopy (STM), the intrinsic point defects, formation energy, and electronic structure of 1T-TiS2 were investigated. Defect systems include single-atom vacancies, interstitial and adatom additions, and direct atomic substitution. Using a collective approach for analyzing realistic systems for point defect investigation, we provide a more straightforward comparison to the experimental measurements, reproducing more realistic environmental conditions related to thin film growth. STM images are compared to computationally simulated electron density images to identify specific geometries that result from favorable point defects. DFT suggests that titanium interstitials are the most energetically favorable intrinsic defect, and sulfur vacancies are more likely to form than titanium vacancies within this realistic analysis, which is in agreement with STM data. A pristine, stoichiometric monolayer system is calculated to have a direct band gap of 0.422 eV, which varies based on local point defects. Local semiconducting-to-metallic electronic transitions are predicted to occur based on the presence of Ti interstitials.

Keeney, P. J.↗
DOE OSTI2023

Defect Characterization of Monocrystalline Silicon Solar Cells with Polysilicon Passivated Contact Using Electrically-Detected Magnetic Resonance (EDMR) Spectroscopy

As the c-Si based solar cell efficiencies are approaching over 26%, it is becoming critical to characterize the low concentrations of the defects – as low as 10^10-10^11 cm-3 (for e.g., iron contamination in high-lifetime Ga-doped wafers3 and n-type wafers), and further reduce them. Also, atomistic level understanding of the mechanisms of the low concentration process-induced-defects and reliability limiting defects (such as light and elevated temperature induced degradation, surface passivation degradation) is needed to design the mitigation strategies. The conventional characterization techniques are limited due to their detection limitations. Some of the techniques based on lifetime spectroscopies can still be used for low concentration characterization however, they are based on estimations and theoretical models and hence, indirect and cannot fully reveal information about the microscopic mechanism of the defects. Thus, we present the application of an ultrasensitive magnetic resonance-based technique for the direct spectroscopic detection of the defects in Si PV - electrically detected magnetic resonance (EDMR). In this work, we aim to focus on establishing a process flow for fabrication of minicells with (miniature replica of the larger-area cells) and setting up the routine for EDMR measurements on them with the EDMR instrumentation capability at NREL. For the EDMR measurements, sample size is limited by the dimensions of sample holder tube (width less than 3.2 mm, active area - 20 mm). Thus, we have designed c-Si based minicells with polysilicon (poly-Si) passivated contacts same as the larger-area cells that we fabricate in our group at NREL. We also modified our minicell process flow for fabricating the textured minicells for preserving the texture during processing and taking care of the laser-ablation edge damage which can significantly affect the performance of such small devices. We have achieved comparable performance on these newly fabricated minicells as that of our 4 cm2 devices with same structure (comparable VOC, JSC, FF). We also conducted EDMR measurements on the minicells and observed a distinct EDMR signal at g-value ~2.005 at temperatures 30K and above, as shown in Fig. 2. We associate this signal to the presence of silicon dangling bonds based on the g-value. We also observed an EDMR signal at g-value ~1.998 at temperature ~5K. The origin of this signal is still being investigated. Thus, we show the proof of concept of minicells and EDMR measurements with which we now aim to study some of the unknown defects in silicon solar cell devices.

EDMR↗
DOE OSTI2023

Dynamic Motions of Topological Defects in Nematic Liquid Crystals under Spatial Confinement

Abstract Topological defects (TDs) have become a sensational topic due to their significant influence on the unusual optical and physiochemical characteristics of the material. To facilitate their application across a wide range of disciplines it is desirable to analyze and gain fundamental understanding of TDs in both equilibrium and nonequilibrium systems. Liquid crystals (LCs) are considered an ideal system for study given the direct visualization of TDs and a straightforward analyzation process. In addition to the equilibrium morphology of LC TDs, it is also of great interest to track and control the formation and annihilation of defects during thermodynamic processes. However, controlling the dynamic behavior of formed defects remains a challenge. Here, nematic LCs confined in a cell exhibiting surfaces with periodic anchoring conditions containing surface topography are relied on. The effects of patterned surface characteristics such as width, periodicity, and degree of curvature on defects dynamic motion, stabilization, and annihilation are explored. The computational experiments recapitulate the TDs transition path and provide free energy‐based predictions of critical distances for defect annihilation. Taken together, this simple approach offers a promising opportunity to control the dynamics of TDs in LCs through chemical patterned surfaces with topography.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Be₂C as a neutron moderator for molten salt reactors: A first-principles study of structural, electronic, and defect properties

Beryllium carbide (Be 2 C), valued for its high neutron moderation efficiency and low absorption cross section, is a promising high-temperature neutron moderator for molten salt reactors. Its practical adoption, however, demands significant technological maturation, requiring comprehensive theoretical and experimental studies of its response to different conditions, including high temperature and irradiation. Here, we report initial results on the fundamental properties and radiation-induced defects of Be 2 C, focusing on antisites, vacancies, interstitial atoms, and Frenkel pairs in the Be and C sublattices. Using density functional theory (DFT) and ab initio molecular dynamics (AIMD), we calculate the defects formation and binding energies, evaluating their dependence on the supercell size, charge states, and chemical environment. In general, carbon defects exhibit higher formation energies, greater sensitivity to cell size, and stronger impacts on the density of states compared to beryllium defects, with charged state the effects being more pronounced. Static DFT reveals multiple metastable interstitial configurations, while AIMD identifies ground states as C-C <100> dumbbells and octahedral Be interstitials. In conclusion, the diversity of metastable configurations and defect states complicates the diffusion mechanisms, requiring further molecular dynamics analysis to elucidate the mechanisms and rates of radiation-induced atomic transport, as well as the structural stability of Be2C.

Ab initio modeling↗
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2021

Defect Chemistry and Hydrogen Transport in La/Sr-Based Oxyhydrides

Oxyhydrides in the series La 2 – y Sr y LiH 1 + y O 3 – y are attractive materials for solid-state hydride electrolytes. However, their chemical stability is poor, and thus far only La 2 LiHO 3 (y = 0) has been demonstrated in a working fuel cell. Using a first-principles approach to study defect chemistry and stability, we find that La 2 LiHO 3 can be stabilized over a range of H-rich, O-poor chemical conditions, while Sr 2 LiH 3 O has low stability. Here, defects are critical for ionic transport and for stability, particularly in Sr 2 LiH 3 O, in which anion antisites and H vacancies readily form. In fact, we show that the ground-state structure of Sr 2 LiH 3 O is inherently disordered. La 2 LiHO 3 has low conductivity, which we connect to the high formation energy of defects such as VO and OH that are necessary for hydride conduction. When Sr 2 LiH 3 O is grown under carefully selected conditions, V H + defects can be made prevalent; these defects give rise to much higher ionic conductivity than can be obtained in La 2 LiHO 3 . In general, we show that the choice of synthesis conditions is vital when seeking to optimize the stability and ionic conductivity of these oxyhydrides, thereby tailoring them for use in solid-state hydrogen fuel cells.

08 HYDROGEN↗
DOE OSTI2022

Metal Halide Perovskites Demonstrate Radiation Hardness and Defect Healing in Vacuum

Herein, we subject formamidinium lead iodide films to oxygen-containing gases (flowing O 2 or free diffusion of lab atmosphere), inert gases (flowing He, Ar, or N 2 ), and vacuum. Our films are irradiated by Cu Ka X-rays and held at 75 °C while X-ray diffraction is recorded. Under all gas conditions, we observe a reproducible 1.1 ± 0.5 A 3 perovskite lattice contraction from an initial unit cell volume of 256.5 ± 0.8 A 3 concurrent with continuous perovskite loss and lead iodide growth. Oxygen-containing gases increase the reaction rates without materially altering perovskite structural changes. Under the same temperature and irradiation conditions in vacuo, a self-healing reaction is observed, exhibited by a reproducible (0.9 ± 0.3 A 3 ) lattice expansion and stabilization of the perovskite. Furthermore, interactions between the perovskite, defects, and minority phases are simulated by generalized gradient approximation Perdew-Burke-Ernzerhof (GGA-PBE) density functional theory. Lattice contraction indicates an increase in the concentration of Schottky defects-pairs of formamidinium and iodine vacancies. Under irradiation in every atmospheric condition, a solid solution of Schottky defects with a concentration of several percent diffuses and precipitates forming lead iodide and consuming the defects. In the presence of ionized gases, this framework is modified to include the continual loss of formamidinium and iodine ions from the perovskite forming Schottky defects.

14 SOLAR ENERGY↗
DOE OSTI2023

Proton radiation effects on electronic defect states in MOCVD-grown (010) β -Ga 2 O 3

The impact of 1.8 MeV proton irradiation on metalorganic chemical vapor deposition grown (010) β-Ga 2 O 3 Schottky diodes is presented. It is found that after a 10.8 × 10 13 cm –2 proton fluence the Schottky barrier height of (1.40 ± 0.05 eV) and the ideality factor of (1.05 ± 0.05 ) are unaffected. Capacitance–voltage extracted net ionized doping curves indicate a carrier removal rate of 268 ± 10 cm –1 . The defect states responsible for the observed carrier removal are studied through a combination of deep level transient and optical spectroscopies (DLTS/DLOS) as well as lighted capacitance–voltage (LCV) measurements. The dominating effect on the defect spectrum is due to the E c -2.0 eV defect state observed in DLOS and LCV. This state accounts for ~75 % of the total trap introduction rate and is the primary source of carrier removal from proton irradiation. Of the DLTS detected states, the E c -0.72 eV state dominated but had a comparably smaller contribution to the trap introduction. These two traps have previously been correlated with acceptor-like gallium vacancy-related defects. Several other trap states at E C -0.36, E C -0.63, and E C -1.09 eV were newly detected after proton irradiation, and two pre-existing states at E C -1.2 and E C -4.4 eV showed a slight increase in concentration after irradiation, together accounting for the remainder of trap introduction. However, a pre-existing trap at E c -0.40 eV was found to be insensitive to proton irradiation and, therefore, is likely of extrinsic origin. Furthermore, the comprehensive defect characterization of 1.8 MeV proton irradiation damage can aid the modeling and design for a range of radiation tolerant devices.

42 ENGINEERING↗
DOE OSTI2020

Tuning Fermi Levels in Intrinsic Antiferromagnetic Topological Insulators MnBi 2 Te 4 and MnBi 4 Te 7 by Defect Engineering and Chemical Doping

MnBi 2 Te 4 and MnBi 4 Te 7 are intrinsic antiferromagnetic topological insulators, offering a promising materials platform for realizing exotic topological quantum states. However, high densities of intrinsic defects in these materials not only cause bulk metallic conductivity, preventing the measurement of quantum transport in surface states, but may also affect magnetism and topological properties. In this paper, systematic density functional theory calculations reveal specific material chemistry and growth conditions that determine the defect formation and dopant incorporation in MnBi 2 Te 4 and MnBi 4 Te 7 . The large strain induced by the internal heterostructure promotes the formation of large-size-mismatched antisite defects and substitutional dopants. The results here show that the abundance of antisite defects is responsible for the observed n-type metallic conductivity. Additionally, a Te-rich growth condition is predicted to reduce the bulk free electron density, which is confirmed by experimental synthesis and transport measurements in MnBi 2 Te 4 . Furthermore, Na doping is proposed to be an effective acceptor dopant to pin the Fermi level within the bulk band gap to enable the observation of surface quantum transport. The defect engineering and doping strategies proposed here should stimulate further studies for improving synthesis and for manipulating magnetic and topological properties in MnBi 2 Te 4 , MnBi 4 Te 7 , and related magnetic topological insulators.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quenching-Induced Defects Liberate the Latent Reversible Capacity of Lithium Titanate Anode

Interest in defect engineering for lithium-ion battery (LIB) materials is sparked by its ability to tailor electrical conductivity and introduce extra active sites for electrochemical reactions. However, harvesting excessive intrinsic defects in the bulk of the electrodes rather than near their surface remains a long-standing challenge. Here, a versatile strategy of quenching is demonstrated, which is exercised in lithium titanate (Li 4 Ti 5 O 12 , LTO), a renowned anode for LIBs, to achieve off-stoichiometry in the interior region. In situ synchrotron analysis and atomic-resolution microscopy reveal the enriched oxygen vacancies and cation redistribution after ice-water quenching, which can facilitate the native unextractable Li ions to participate in reversible cycling. Further, the fabricated LTO anode delivers a sustained capacity of 202 mAh g -1 in the 1.0–2.5 V range with excellent rate capability and overcomes the poor cycling stability seen in conventional defective electrodes. The feasibility of tuning the degree of structural defectiveness via quenching agents is also proven, which can open up an intriguing avenue of research to harness the intrinsic defects for improving the energy density of rechargeable batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Intermittent Defect Fluctuations in Oxide Heterostructures

Abstract The heterogeneous nature, local presence, and dynamic evolution of defects typically govern the ionic and electronic properties of a wide variety of functional materials. While the last 50 years have seen considerable efforts into development of new methods to identify the nature of defects in complex materials, such as the perovskite oxides, very little is known about defect dynamics and their influence on the functionality of a material. Here, the discovery of the intermittent behavior of point defects (oxygen vacancies) in oxide heterostructures employing X‐ray photon correlation spectroscopy is reported. Local fluctuations between two ordered phases in strained SrCoO x with different degrees of stability of the oxygen vacancies are observed. Ab‐initio‐informed phase‐field modeling reveals that fluctuations between the competing ordered phases are modulated by the oxygen ion/vacancy interaction energy and epitaxial strain. The results demonstrate how defect dynamics, evidenced by measurement and modeling of their temporal fluctuations, give rise to stochastic properties that now can be fully characterized using coherent X‐rays, coupled for the first time to multiscale modeling in functional complex oxide heterostructures. The study and its findings open new avenues for engineering the dynamical response of functional materials used in neuromorphic and electrochemical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Revealing the Defect‐Driven Ferroelectric Mechanisms of Aluminum Nitride

Wurtzite III-nitride compounds are CMOS-compatible with widespread industrial interest to exercise ferroelectricity, despite their polar structure being highly resistant to polarization reversal. Here, we induce and tune ferroelectric properties in w-AlN via direct-write ion-beam processing, using nanoscale patterned defect engineering as a post-growth alternative to conventional cation substitution. Nanometric piezoresponse spectroscopy of the focused He + beam patterned defect concentrations in ferroelectric Al 0.92 B 0.08 N measures a localized 10x enhancement in effective piezoresponse and 40% reduction in switching barrier. The irradiation-induced point defects convert piezoelectric AlN into a ferroelectric system with site-saturated nucleation and raise the dielectric susceptibility, switched polarization, and effective piezoelectric coefficient. Enhanced defect-lattice interactions in AlN increase carrier conduction and phonon scattering loss but preserve long-range crystallinity. Here, based on atomistic analysis of nudged elastic band density functional theory calculations and reactive force field simulations, both nitrogen vacancies and defect complexes disrupt bond ordering, facilitating a line-by-line low-barrier switching of pristine AlN.

36 MATERIALS SCIENCE↗