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Results for “Defect modelling”

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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Theory of photoemission from cathodes with disordered surfaces

Linear-accelerator-based applications like x-ray free electron lasers, ultrafast electron diffraction, electron beam cooling, and energy recovery linacs use photoemission-based cathodes in photoinjectors for electron sources. Most of these photocathodes are typically grown as polycrystalline materials with disordered surfaces. In order to understand the mechanism of photoemission from such cathodes and completely exploit their photoemissive properties, it is important to develop a photoemission formalism that properly describes the subtleties of these cathodes. Here, the Dowell–Schmerge (D–S) model often used to describe the properties of such cathodes gives the correct trends for photoemission properties like the quantum efficiency (QE) and the mean transverse energy (MTE) for metals; however, it is based on several unphysical assumptions. In the present work, we use Spicer’s three-step photoemission formalism to develop a photoemission model that results in the same trends for QE and MTE as the D–S model without the need for any unphysical assumptions and is applicable to defective thin-film semiconductor cathodes along with metal cathodes. As an example, we apply our model to Cs 3 Sb thin films and show that their near-threshold QE and MTE performance is largely explained by the exponentially decaying defect density of states near the valence band maximum.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Defect diffusion graph neural networks (d2gnn)

SAND2025-01004O Defect Diffusion Graph Neural Networks (d2gnn) is a software tool that assists in the discovery of new materials for high-temperature, clean-energy applications. It uses advanced graph neural networks to model the relationship between material structures and their defect properties. The application helps predict how materials will behave under different conditions and accelerates the development of innovative materials. 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.

Witman, Matthew [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2022

Low temperature CVD growth of WSe 2 enabled by moisture-assisted defects in the precursor powder

Two-dimensional transition metal dichalcogenides (TMDs) have been proposed for a wide variety of applications, such as neuromorphic computing, flexible field effect transistors, photonics, and solar cells, among others. However, for most of these applications to be feasible, it is necessary to integrate these materials with the current existing silicon technology. Although chemical vapor deposition is a promising method for the growth of high-quality and large-area TMD crystals, the high temperatures necessary for the growth make this technique incompatible with the processes used in the semiconductor industry. Herein, we demonstrate the possibility of low-temperature growth of TMDs, using tungsten selenide (WSe 2 ) as a model, by simply using moisture-assisted defective tungsten oxide (WO 3 ) precursor powders during the growth of these materials. Density functional theory calculations reveal the mechanism by which moisture promotes the defect formation on the precursor crystal structure and how it dictates the reduction of the temperature of the growth. The results were compared with the standard growth at high temperatures and with a precursor mixture with alkali salts to show the high quality of the WSe 2 grown at temperatures as low as 550 °C. To conclude, the work improves the understanding of nucleation and growth mechanisms of WSe 2 at low temperatures and provides a useful strategy for the growth of TMDs at temperatures required for the back-end-of-line compatibility with current silicon technology.

2D materials↗
DOE OSTI2025

Proton radiation effects in indium oxide using cascade molecular dynamics simulations

Metal oxide (MO) semiconductors, characterized by their wide band gaps and notable charge transport properties, are promising candidates for electronic applications in extreme environments, including near-Earth space. However, atomistic simulations of radiation–matter interactions in MOs remain challenging due to the limitations of existing interatomic potentials, which often fail to capture both the short-range repulsive forces essential for radiation damage modeling and the long-range electrostatic effects governing defect evolution. In this work, we develop a customized interatomic potential tailored for radiation damage simulations in indium oxide (In 2 O 3 ) as a model system, a representative MO material. Our potential integrates the Ziegler-Biersack-Littmark potential to accurately describe short-range interactions with Buckingham and Coulombic potentials to account for long-range forces. We perform molecular dynamics simulations of low-energy proton irradiation using this custom potential. We employ the primary knock-on atom (PKA) cascade method to study atomic displacements and primary defect formation. Simulations were conducted for 1 keV proton irradiation in four randomly chosen directions, and PKA-driven defect analyses at 5, 10, and 15 keV to examine the effects of direction and energy level on damage generation. Our results provide insight into the impact of irradiation direction and energy level on the cascade evolution and defect formation mechanisms.

Atomistic simulations↗
DOE OSTI2023

Drude weights in one-dimensional systems with a single defect

Ballistic transport of a quantum system can be characterized by Drude weight, which quantifies the response of the system to a uniform electric field in the infinitely long timescale. The Drude weight is often discussed in terms of the Kohn formula, which gives the Drude weight by the derivative of the energy eigenvalue of a finite-size system with the periodic boundary condition in terms of the Aharonov-Bohm flux. Recently, the Kohn formula is generalized to nonlinear responses. However, the nonlinear Drude weight determined by the Kohn formula often diverges in the thermodynamic limit. In order to elucidate the issue, in this work we examine a simple example of a one-dimensional tight-binding model in the presence of a single defect at zero temperature. We find that its linear and nonlinear Drude weights given by the Kohn formula (i) depend on the Aharonov-Bohm flux and (ii) diverge proportionally to a power of the system size. Here, we argue that the problem can be attributed to different order of limits. The Drude weight according to the Kohn formula (“Kohn-Drude weight”) indicates the response of a finite-size system to an adiabatic insertion of the Aharonov-Bohm flux. While it is a well-defined physical quantity for a finite-size system, its thermodynamic limit does not always describe the ballistic transport of the bulk. The latter should be rather characterized by a “bulk Drude weight” defined by taking the thermodynamic limit first before the zero-frequency limit. While the potential issue of the order of limits has been sometimes discussed within the linear response, the discrepancy between the two limits is amplified in nonlinear Drude weights. We demonstrate the importance of the low-energy excitations of O(1/L), which are excluded from the Kohn-Drude weight, in regularizing the bulk Drude weight.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Thermodynamics of Bimetallic Joints between Titanium and Tantalum Produced by Laser Powder Bed Fusion

Laser powder bed fusion (LBPF) is currently the most mature metal additive manufacturing (AM) technology. While it does not have the same flexibility as directed energy deposition techniques to produce compositional gradients, LPBF can still be used to generate bimetallic parts by depositing one metal on a build plate made of another. Here, in this study, we print combinations of Ti-6Al-4V with Ta and characterize defects that occur at the interface. We use thermodynamic modeling to explain the formation of keyhole porosity and solidification cracks when Ta is built on a Ti baseplate, and the lack of defects when the materials are reversed. By understanding the mechanisms that lead to defect formation, the methodology demonstrated here can be applied to other material systems to efficiently design bimetallic LPBF processes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Temperature-based reactive flow model for TATB plastic bonded explosives

A new reactive flow model is presented for TATB-based plastic bonded explosives, applicable to shock initiation and detonation problems of differing initial temperature. Temperature disequilibrium is assumed between unreacted explosive, material in the vicinity of compressed defects (called hot spots), and detonation products. The model incorporates temperature-dependent decomposition reaction rates. Arrhenius model parameters were derived from subscale quantum-based molecular dynamics simulations of shock-induced TATB decomposition. Further, a model of detonation carbon aggregation is incorporated, describing the late-time slow release of energy inherent to detonation in TATB-based materials. The predictive ability of the model in the shock initiation regime is tested against recent thin pulse experiments on PBX 9502. Here, the model is found to perform equally well in predicting the size effect curve of ambient, cold, and hot PBX 9502 rate sticks.

Chemistry - Chemical explosives↗
DOE OSTI2025

Temperature-based reactive flow model for triaminotrinitrobenzene (TATB) plastic bonded explosives

A new reactive flow model is presented for triaminotrinitrobenzene (TATB)-based plastic bonded explosives, applicable to shock initiation and steady detonation problems of differing initial temperature. Temperature disequilibrium is assumed between unreacted explosive, material in the vicinity of compressed defects (called hot spots), and reaction products. The model incorporates temperature-dependent decomposition reaction rates. Particularly, Arrhenius model parameters were derived from quantum-based molecular dynamics simulations of TATB decomposition. Further, a model of detonation carbon aggregation is incorporated, describing the slow release of energy inherent to detonation in TATB-based materials. Model parameters were calibrated against gas gun shock initiation experiments and steady detonation rate stick tests. The predictive ability of the model in the shock initiation regime is tested against recent thin pulse experiments. The model is found to perform equally well in predicting the size-effect curve of ambient, cold, and hot rate sticks. The present work demonstrates the viability of incorporating results from subscale simulations into a continuum-scale reactive flow model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Quantification of Ebola virus replication kinetics in vitro

Mathematical modelling has successfully been used to provide quantitative descriptions of many viral infections, but for the Ebola virus, which requires biosafety level 4 facilities for experimentation, modelling can play a crucial role. Ebola virus modelling efforts have primarily focused on in vivo virus kinetics, e.g., in animal models, to aid the development of antivirals and vaccines. But, thus far, these studies have not yielded a detailed specification of the infection cycle, which could provide a foundational description of the virus kinetics and thus a deeper understanding of their clinical manifestation. Here, we obtain a diverse experimental data set of the Ebola virus infection in vitro, and then make use of Bayesian inference methods to fully identify parameters in a mathematical model of the infection. Our results provide insights into the distribution of time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity. We suggest how these results can be used in future models to describe co-infection with defective interfering particles, which are an emerging alternative therapeutic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantum Simulations of Fermionic Hamiltonians with Efficient Encoding and Ansatz Schemes

Here, we propose a computational protocol for quantum simulations of fermionic Hamiltonians on a quantum computer, enabling calculations on spin defect systems which were previously not feasible using conventional encodings and a unitary coupled-cluster ansatz of variational quantum eigensolvers. We combine a qubit-efficient encoding scheme mapping Slater determinants onto qubits with a modified qubitcoupled cluster ansatz and noise-mitigation techniques. Our strategy leads to a substantial improvement in the scaling of circuit gate counts and in the number of required qubits, and to a decrease in the number of required variational parameters, thus increasing the resilience to noise. We present results for spin defects of interest for quantum technologies, going beyond minimum models for the negatively charged nitrogen vacancy center in diamonds and the double vacancy in 4H silicon carbide (4H-SiC) and tackling a defect as complex as negatively charged silicon vacancy in 4H-SiC for the first time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning

Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom neighborhood during atomic motion and providing statistical information of possible defect configurations. The combination of a Gaussian mixture model and principal component analysis applied to the deep learning-processed experimental data allowed disentangling of the atomic distortions for two different graphene sublattices. This approach demonstrates the potential of e-beam manipulation to create defect libraries of multiple realizations of the same defect and explore the potential of symmetry breaking physics. The rapid image analytics enabled via a deep learning network further empowers instrumentation for e-beam controlled atom-by-atom fabrication. Here, the analysis described in the paper can be reproduced via an interactive Jupyter notebook at https://git.io/JJ3Bx.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Correlating the three-dimensional atomic defects and electronic properties of two-dimensional transition metal dichalcogenides

The electronic, optical and chemical properties of two-dimensional transition metal dichalcogenides strongly depend on their three-dimensional atomic structure and crystal defects. Using Re-doped MoS 2 as a model system, here we present scanning atomic electron tomography as a method to determine three-dimensional atomic positions as well as positions of crystal defects such as dopants, vacancies and ripples with a precision down to 4 pm. We further measure the three-dimensional bond distortion and local strain tensor induced by single dopants. By directly offering these experimental three-dimensional atomic coordinates to density functional theory, we obtain more accurate electronic band structures than derived from conventional density functional theory calculations that relies on relaxed three-dimensional atomic coordinates. We anticipate that scanning atomic electron tomography not only will be generally applicable to determine the three-dimensional atomic coordinates of two-dimensional materials, but also will enable ab initio calculations to better predict the physical, chemical and electronic properties of these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extreme variation in fatigue: Fatigue life prediction and dependence on build volume location in laser powder bed fusion of 17-4 stainless steel

Laser powder bed fusion (LPBF), a metal additive manufacturing technology, is well-suited for design optimization but fatigue life is limited by manufacturing defects. In this work, 17-4 stainless steel components were manufactured in densely populated build volumes, simulating at-scale LPBF production. Tests revealed extreme variability in fatigue life data, analyzed via rigorous statistical tools. The El-Haddad model, modified for finite-life, enabled defect-based life prediction. Specimen location within the build volume correlated to life, which was heteroscedastic. Investigating defect concentration over the build volume explained typical life and scatter. Finally, these findings argue for qualification approaches which acknowledge high material lot variability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mapping TpPa-1 covalent organic framework (COF) molecular interactions in mixed solvents via atomistic modeling and experimental study

Complex solvent environments continue to limit the widespread adoption of organic solvent nanofiltration (OSN) in many chemical industry applications. In this paper we employ a commercially available covalent organic framework (COF), TpPa-1, and force field models to molecularly map separation performance of TpPa-1 membrane in mixed solvents. To minimize time and length scale mismatch between atomistic modeling and experiments, solvent permeance was normalized with water in modeling and experimental results to enable direct comparison. Model outputs, such as organic solvent permeance and solute rejection rate, matched well with filtration results. Since the atomistic models assume that all mass transfer is via through-pore transport, the discrepancies between modeling and experimental results provide insights on the effect of linear polymer defects, adsorption and interstitial mass transfer on polycrystalline COF membrane performance. In sum, force field models can serve as digital twins of COF membranes to simulate separation processes while capturing the effects of COF structure, chemistry, and crystallinity on membrane performance in complex organic solvent environments. Finally, this approach will provide insight into future COF design and synthesis for persisting separation challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Non-symmetric pinning of topological defects in living liquid crystals

Topological defects, such as vortices and disclinations, play a crucial role in spatiotemporal organization of equilibrium and non-equilibrium systems. The defect immobilization or pinning is a formidable challenge in the context of the out-of-equilibrium system, like a living liquid crystal, a suspension of swimming bacteria in lyotropic liquid crystal. Here we control the emerged topological defects in a living liquid crystal by arrays of 3D-printed microscopic obstacles (pillars). Our studies show that while –1/2 defects may be easily immobilized by the pillars, +1/2 defects remain motile. Due to attraction between oppositely charged defects, positive defects remain in the vicinity of pinned negative defects, and the diffusivity of positive defects is significantly reduced. Experimental findings are rationalized by computational modeling of living liquid crystals. Our results provide insight into the engineering of active systems via targeted immobilization of topological defects.

42 ENGINEERING↗
DOE OSTI2025

Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites

To push upper boundaries of thermal conductivity in polymer composites, understanding of thermal transport mechanisms is crucial. Despite extensive simulations, systematic experimental investigation on thermal transport in polymer composites is limited. To better understand thermal transport processes, we design polymer composites with perfect fillers (graphite) and defective fillers (graphite oxide), using polyvinyl alcohol (PVA) as a matrix model. Measured thermal conductivities of ~1.38 ± 0.22 W m -1 K -1 in PVA/defective filler composites is higher than those of ~0.86 ± 0.21 W m -1 K -1 in PVA/perfect filler composites, while measured thermal conductivities in defective fillers are lower than those of perfect fillers. We identify how thermal transport occurs across heterogeneous interfaces. Thermal transport measurements, neutron scattering, quantum mechanical modeling, and molecular dynamics simulations reveal that vibrational coupling between PVA and defective fillers at PVA/filler interfaces enhances thermal conductivity, suggesting that defects in polymer composites improve thermal transport by promoting this vibrational coupling.

42 ENGINEERING↗