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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods

We construct a family of embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods of order 2 ≤ p ≤ 4 to be used to obtain numerical solution of spatially discretized hyperbolic PDEs. In this construction, the goals include non-defective property, large stability region, and small error values as defined in Dekker and Verwer (1984) and Kennedy et al. (2000). The new family of embedded pairs offer the ability for strong stability preserving (SSP) methods to adapt by varying the step-size. Through several numerical experiments, we assess the overall effectiveness in terms of work versus precision while also taking into consideration accuracy and stability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Mitigating electrochemical degradation in CsPbBr{sub 3} gamma detectors by organic and inorganic encapsulation.

CsPbBr3 perovskite semiconductors have emerged as a leading candidate for nextgeneration radiation detectors because of their exceptional charge transport properties, defect tolerance, and record-breaking sensitivity and energy resolution. Their long-term stability, however, is hindered by electrode-driven electrochemical decomposition, which is accelerated by moisture- and oxygen-assisted ion migration during operation. Here, we investigated organic and inorganic encapsulation strategies as both environmental barriers and means to suppress interfacial degradation pathways. Atomic layer deposition (ALD) of Al2O3 provided a conformal passivation layer that blocked environmental ingress, suppressed ionic diffusion, reduced leakage current, enhanced energy resolution and expanded the operational electric-field window beyond 5 kV∙cm1 . By contrast, organic encapsulants such as paraffin wax and polystyrene slowed moisture diffusion but did not suppress interfacial reactions, with wax extending stability to over 90 days. These results show that ALD-Al2O3 suppresses dominant interfacial degradation pathways, enabling stable, high-field operation and advancing the practical deployment of CsPbBr3 γ-ray detectors.

Unal, Mustafa↗
DOE OSTI2025

Uncertainty quantification for misspecified machine learned interatomic potentials

The use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which has brought renewed interest in robust means to quantify uncertainties. In many practical settings where model complexity is constrained (e.g., due to performance considerations), misspecification — the inability of any one choice of model parameters to exactly match all training data — is a key contributor to errors that is often disregarded. Here, we employ a recent misspecification-aware regression technique to quantify parameter uncertainties, which is then propagated to a broad range of phase and defect properties in tungsten. The propagation is performed through both brute-force resampling and implicit Taylor expansion. The propagated misspecification uncertainties robustly quantify and bound errors on a broad range of material properties. We demonstrate application to recent foundational machine learning interatomic potentials, accurately predicting and bounding errors in MACE-MPA-0 energy predictions across the diverse materials project database.

36 MATERIALS SCIENCE↗
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 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

Optical Properties of Low‐Defect Large‐Area Hexagonal Boron Nitride for Quantum Applications

Intrinsic defects and their concentrations in hexagonal boron nitride (h-BN) play a key role in single-photon emission. In this study, the optical properties of large-area multilayer h-BN-on-sapphire grown by metal-organic chemical vapor deposition are explored. Based on the detailed spectroscopic characterization using both cathodoluminescence (CL) and photoluminescence (PL) measurements, the material is devoid of random single-point defects instead of a few clustered complex defects. The emission spectra of the measurements confirm a record-low-defect concentration of ≈10 4 cm −2 . Post-annealing, no significant changes are observed in the measured spectra and the defect concentrations remain unaltered. Through CL and PL spectroscopy, an optically active boron vacancy spin defect is identified and a novel complex defect combination arising from carbon impurities is revealed. This complex defect, previously unreported, signifies a unique aspect of the material. In these findings, the understanding of defect-induced optical properties in h-BN films is contributed, providing insights for potential applications in quantum information science.

42 ENGINEERING↗
DOE OSTI2026

Exciton-Defect Interaction and Optical Properties from a First-Principles T-Matrix Approach

Understanding exciton-defect interactions is critical for optimizing optoelectronic and quantum information applications in many materials. However, ab initio simulations of material properties with defects are often limited to high defect density. Here, we study effects of exciton-defect interactions on optical absorption and photoluminescence spectra in monolayer MoS 2 using a first-principles T-matrix approach. We demonstrate that exciton-defect bound states can be captured by the disorderaveraged Green’s function with the T-matrix approximation and further analyze their optical properties. Our approach yields photoluminescence spectra in good agreement with experiments and provides a new, computationally efficient framework for simulating optical properties of disordered 2D materials from firstprinciples.

T-matrix↗
DOE OSTI2023

Excited State Properties of Point Defects in Semiconductors and Insulators Investigated with Time-Dependent Density Functional Theory

Here, we present a formulation of spin-conserving and spin-flip hybrid time-dependent density functional theory (TDDFT), including the calculation of analytical forces, which allows for efficient calculations of excited state properties of solid-state systems with hundreds to thousands of atoms. We discuss an implementation on both GPU- and CPU-based architectures along with several acceleration techniques. We then apply our formulation to the study of several point defects in semiconductors and insulators, specifically the negatively charged nitrogen-vacancy and neutral silicon-vacancy centers in diamond, the neutral divacancy center in 4H silicon carbide, and the neutral oxygen-vacancy center in magnesium oxide. Our results highlight the importance of taking into account structural relaxations in excited states in order to interpret and predict optical absorption and emission mechanisms in spin defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effects of structural defects on optical properties of In x Ga 1-x N layers and quantum wells

This review concentrates on the microstructure of In x Ga 1-x N layers and quantum wells (QWs) in relation to their optical properties. The microstructure of In x Ga 1-x N, with a constant In(x) concentration, shifts with layer thickness. Only layers below 100 nm for x = 0.1 are nearly defect-free. A photoluminescence peak is observed at 405 nm, in line with ~10% In, suggesting band-edge luminescence. Layers with greater thickness and In content present a corrugated surface with numerous structural defects, including V-defects, causing redshifts and multi-peaks in photoluminescence up to 490 nm. These defects, resembling those in GaN, lead to a corrugated sample surface. Atomic force microscopy shows a 3.7-fold larger corrugation in samples with 20 QWs compared to those with 5 QWs measured on 2 × 2 μm 2 areas. Like in GaN, dual growth on different crystallographic planes results in varied QW thicknesses, influencing optical traits of devices made from In x Ga 1-x N layers. The purpose of this review and the chosen subject is to highlight the significant contribution of Wladek Walukiewicz and his group to the current research on the properties of In x Ga 1-x N, which are crucial alloys in the field of optoelectronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Impact of Arsenic- and Indium-Terminated InGaAs Stressors on Carrier Confinement, Strain, Defects, and Transport Properties of Tensile-Strained Ge

Device-quality tensile-strained Ge (ε-Ge) grown on a large bandgap semiconductor with superior electrical and optical carrier confinement is essential for group-IV-based optoelectronics. Properties of ε-Ge active layers synthesized on In 0.24 Ga 0.76 As buffers with two different surface terminations─arsenic-rich and indium-rich─were experimentally demonstrated, highlighting the factors not considered in theoretical calculations. High-resolution X-ray diffraction and Raman spectroscopy analyses of these ε-Ge/In 0.24 Ga 0.76 As heterostructures confirmed the fully strained (1.6%) and partially relaxed (0.82%) nature of the ε-Ge bonded with arsenic-terminated (Ge As-terminated ) and indium-terminated (Ge In-terminated ) In 0.24 Ga 0.76 As stressors, respectively. High-resolution cross-sectional transmission electron microscopy showed a coherent, sharp, and fully strained ε-Ge/In 0.24 Ga 0.76 As heterointerface in the Ge As-terminated heterostructure, whereas microtwin defects were present in the Ge In-terminated heterostructure. These heterostructures were further characterized by evaluating the minority carrier lifetimes, high for Ge As-terminated (525 ns) and low for Ge In-terminated (69 ns), using the photoconductive decay technique. Moreover, band alignment was constructed using X-ray photoelectron spectroscopy, where the Ge As-terminated heterostructure revealed that both holes and electrons were confined within the ε-Ge active layer as a type-I band alignment with ΔE V, As-terminated = 0.22 eV and ΔE C,As-terminated = 0.38 eV. On the other hand, the Ge In-terminated heterostructure exhibited a type-II band alignment with ΔE V,In-terminated = – 0.02 eV and ΔE C,In-terminated = 0.53 eV. Furthermore, the magnetotransport properties revealed high mobility (321 cm 2 /(V s)) with single-electron transport in Ge As-terminated heterostructure and low mobility (3.34 cm 2 /(V s)) with multihole transport in the Ge In-terminated heterostructure. Therefore, preferring the ε-Ge on the arsenic-rich surface of In 0.24 Ga 0.76 As stressor over the indium-rich surface during material synthesis offers device-quality materials with high carrier lifetime and superior carrier confinement, which can provide an opportunity to fabricate efficient group-IV-based optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach

Here, the relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe 35+ irradiation is systematically investigated, employing experimental characterizations combined with first-principle calculations. Based on the ion irradiation-induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A comprehensive first-principles study of the effects of the exchange-correlation functional and magnetism on defect and diffusion properties of the CoCrNi medium-entropy alloy

The present work is a novel, systematic study of the effect of density functional theory input parameters on the vacancy formation energy (VFE), migration barrier for diffusion, and electronic structure for each element in the CoCrNi medium-entropy alloy (MEA). In particular, the novelties include: (1) calculating the aforementioned properties of Co, Cr, or Ni, in the CoCrNi MEA using magnetic and non-magnetic states, and two versions of the generalized gradient approximation: Perdew, Burke, and Ernzerhof (PBE) and the PBE version for solids (PBEsol), and (2) a detailed comparison of 0 K activation energy to experimental creep activation energies. First-principles calculations at 0 K are performed using the Vienna ab-initio simulation package. Special quasirandom structures (SQS) and Widom-type substitution are employed. For each element, Co, Cr, or Ni, non-magnetic calculations result in a higher VFE and larger range of calculated values for the configurations studied. The averaged migration barrier is the highest for Co in the CoCrNi for three of four sets of calculation parameters in the configurations studied. Finally, the results indicate that the average 0 K activation energy for diffusion makes up 70–80% of the experimental creep activation energy, depending on the exchange-correlation functional employed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analyzing the effect of pressure on the properties of point defects in $\gamma\mathrm{U–Mo}$ through atomistic simulations

Uranium–molybdenum (U–Mo) alloys in monolithic fuel foil are the primary candidate for the conversion of high-performance research reactors in the USA. Monolithic fuel is utilized in a plate-type design with a zirconium diffusion barrier and aluminum cladding. These fuel types are unique in that they contain no plenum for the release of fission gases, which, in conjunction with the aluminum cladding, can lead to large stress states within the fuel. The nature of how fundamental processes of radiation damage, including the evolution of point defects, under such stresses occur is unknown. In this work, we present molecular dynamics simulations of the formation energy of point defects under applied stress. We report this work will allow for the implementation of stress-dependent microstructural evolution models of nuclear fuels, including those for both fission gas bubble growth and creep, which are critical to ensure the stable and predictable behavior of research reactor fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Tunable magneto-optical properties in MoS 2 via defect-induced exciton transitions

The presence of chalcogen vacancies in monolayer transition metal dichalcogenides (TMDs) leads to excitons with mixed localized-delocalized character and to reduced valley selectivity. Recent experimental advances in defect design in TMDs allow for a close examination of such mixed exciton states as a function of their degree of circular polarization under external magnetic fields, revealing strongly varying defect-induced magnetic properties. A theoretical understanding of these observations and their physical origins demands a predictive, structure-sensitive theory. In this work, we study the effect of chalcogen vacancies on the exciton magnetic properties in monolayer MoS 2 . Using many-body perturbation theory, we show how the complex excitonic picture associated with the presence of defects—with reduced valley and spin selectivity due to hybridized electron-hole transitions—leads to a structurally controllable exciton magnetic response. We find a variety of $\textit{g}$-factors with changing magnitudes and sign depending on the exciton energy and character. Further, our findings suggest a pathway to tune the nature of the excitons—and by that their magneto-optical properties—through defect architecture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2024

Defect Thermodynamics and Transport Properties of Perovskite and Fluorite Materials for Solid-Oxide and Proton Conducting Oxide Cells Evaluated Based on Density Functional Theory Modeling

Density functional theory based defect thermodynamic modeling was performed to determine the effect of humidity and H2/O2 gas pressure on various defect chemistry and transport properties of perovskite and fluorite oxides for solid-oxide and proton-conducting-oxide cell applications, with inclusion of the electronic-conducting oxides (as electrodes) and insulating oxides (as electrolytes). Automatic defect generation workflow and first-principles charged defect analysis were implemented on NETL Joule supercomputer for modeling defect equilibria and transport properties of insulating oxides as electrolytes in SOCs and proton-conducting ceramic cells. A GNU Octave defect model subroutines were developed to facilitate defect modeling of electronic conducting oxides in a wide range of operating conditions guided by modeling and experiments. The model includes the hydride defect formation reaction under reducing conditions and allows to incorporate nonstoichiometry effects on the defect thermodynamic parameters. The developed model serves as a platform to facilitate fundamental understanding of the defect thermodynamics in SOC oxide materials and can be used as a novel tool in computational materials screening for SOC and other energy applications.

Lee, Yueh-Lin↗