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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interplay between Facets and Defects during the Dissociative and Molecular Adsorption of Water on Metal Oxide Surfaces

Both surface terminations and defects play a central role in determining how water interacts with metal oxides, thereby setting important properties of the interface that govern reactivity such as the type and distribution of hydroxyl groups. However, the interconnections between facets and defects remain poorly understood, limiting the usefulness of conventional notions such as that hydroxylation is controlled by metal cation exposure at the surface. Here, using hematite (α-Fe 2 O 3 ) as a model system, we show how oxygen vacancies overwhelm surface cation-dependent hydroxylation behavior. Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy was used to monitor the adsorption of molecular water and its dissociation to form hydroxyl groups in situ on (001), (012), or (104) facet-engineered hematite nanoparticles. Supported by density functional theory calculations of the respective surface energies and oxygen vacancy formation energies, the findings show how oxygen vacancies are more prone to form on higher energy facets and induce surface hydroxylation at extremely low relative humidity values of 5 x10 - 5 %. Further, when these vacancies are eliminated, the extent of surface hydroxylation across the facets is as expected from the areal density of exposed iron cations at the surface. These findings help answer fundamental questions about the nature of reducible metal oxide-water interfaces in natural and technological settings and lay the groundwork for rational design of improved oxide-based catalysts.

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

Sensing at the Nanoscale Using Nitrogen-Vacancy Centers in Diamond: A Model for a Quantum Pressure Sensor

The sensing of stress under harsh environmental conditions with high resolution has critical importance for a range of applications including earth’s subsurface scanning, geological CO2 storage monitoring, and mineral and resource recovery. Using a first-principles density functional theory (DFT) approach combined with the theoretical modelling of the low-energy Hamiltonian, here, we investigate a novel approach to detect unprecedented levels of pressure by taking advantage of the solid-state electronic spin of nitrogen-vacancy (NV) centers in diamond. We computationally explore the effect of strain on the defect band edges and band gaps by varying the lattice parameters of a diamond supercell hosting a single NV center. A low-energy Hamiltonian is developed that includes the effect of stress on the energy level of a ±1 spin manifold at the ground state. By quantifying the energy level shift and split, we predict pressure sensing of up to 0.3 MPa/Hz using the experimentally measured spin dephasing time. We show the superiority of the quantum sensing approach over traditional optical sensing techniques by discussing our results from DFT and theoretical modelling for the frequency shift per unit pressure. Importantly, we propose a quantum manometer that could be useful to measure earth’s subsurface vibrations as well as for pressure detection and monitoring in high-temperature superconductivity studies and in material sciences. Our results open avenues for the development of a sensing technology with high sensitivity and resolution under extreme pressure limits that potentially has a wider applicability than the existing pressure sensing technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
DOE OSTI2017

Damage evolution of ion irradiated defected-fluorite La 2 Zr 2 O 7 epitaxial thin films

Pyrochlore-structure oxides, A2B2O7, may exhibit remarkable radiation tolerance due to the ease with which they can accommodate disorder by transitioning to a defected fluorite structure. The mechanism of defect formation was explored by evaluating the radiation damage behavior of high quality epitaxial La2Zr2O7 thin films with the defected fluorite structure, irradiated with 1 MeV Zr+ at doses up to 10 displacements per atom (dpa). The level of film damage was evaluated as a function of dose by Rutherford backscattering spectrometry in the channeling geometry (RBS/c) and scanning transmission electron microscopy (STEM). At lower doses, the surface of the La2Zr2O7 film amorphized, and the amorphous fraction as a function of dose fit well to a stimulated amorphization model. As the dose increased, the surface amorphization slowed, and amorphization appeared at the interface. Even at a dose of 10 dpa, the core of the film remained crystalline, despite the prediction of amorphization from the model. To inform future ab initio simulations of La2Zr2O7, the bandgap of a thick La2Zr2O7 film was measured to be indirect at 4.96 eV, with a direct transition at 5.60 eV.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

Raman spectroscopy of thermally perturbed carbon fibers: Discriminating spectral responses of modulus classes and defect types

The mechanical strength properties of carbon fibers are generally thought to be correlated with the presence of underlying atomic-level defects. These defects serve to break the underlying translational symmetry of the graphitic or graphene subunits of the fiber construction, resulting in the emergence of new Raman-active spectral features. However, historical attempts to classify the precise origin of defect contributions to the Raman spectra have been challenging because of indistinct and overlapping features in the carbon fiber Raman spectra. Further, while substantial research exists on high-temperature exposure in inert atmospheres for carbon fiber composites, comparatively less addresses microscale behaviors and Raman spectral alterations to monofilament carbon fibers exposed to high-temperature atmospheric environments. Here, we report Raman spectral responses of nine commercially available high-performance, polyacrylonitrile-based carbon fibers exposed to various atmospheric heat treatments. In this work, we introduce a model-independent characterization method, the integrated absolute difference, to quantify the spectral responses to heat treatment of different fiber modulus classes. We combine this new method with a newly reported strategy to standardize spectral fitting for carbon fibers. With this approach, we show that atomic-scale defects in the underlying fiber microstructure manifest in measurably distinct manners and have distinct responses to thermal perturbation. These combined approaches may lay the foundation for disentangling contributions from specific defects in the Raman spectra of carbon fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Generalized symmetry in dynamical gravity

We explore generalized symmetry in the context of nonlinear dynamical gravity. Our basic strategy is to transcribe known results from Yang-Mills theory directly to gravity via the tetrad formalism, which recasts general relativity as a gauge theory of the local Lorentz group. By analogy, we deduce that gravity exhibits a one-form symmetry implemented by an operator U α labeled by a center element α of the Lorentz group and associated with a certain area measured in Planck units. The corresponding charged line operator W ρ is the holonomy in a spin representation ρ, which is the gravitational analog of a Wilson loop. The topological linking of U α and W ρ has an elegant physical interpretation from classical gravitation: the former materializes an exotic chiral cosmic string defect whose quantized conical deficit angle is measured by the latter. We verify this claim explicitly in an AdS-Schwarzschild black hole background. Notably, our conclusions imply that the standard model exhibits a new symmetry of nature at scales below the lightest neutrino mass. More generally, the absence of global symmetries in quantum gravity suggests that the gravitational one-form symmetry is either gauged or explicitly broken. The latter mandates the existence of fermions. Finally, we comment on generalizations to magnetic higher-form or higher-group gravitational symmetries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗
DOE OSTI2025

Surface Nanostructure Control and Thermodynamic Stability Analysis of Femtosecond Laser-Ablated CuCoMn 1.75 NiFe 0.25 Nanoparticles

Surface nanostructure control is the key to functionalizing nanomaterials. This paper presents a characterization with thermodynamic stability analysis of CuCoMn 1.75 NiFe 0.25 high-entropy alloy (HEA) nanoparticles synthesized by femtosecond laser ablation in ethanol and liquid nitrogen (LN2). Using multimodal electron microscopy and spectroscopy, we examine phase, particle size, defect structure, chemical distribution, and surface composition and relate them to HEA stability. Elemental distributions are uniform in both media, but LN2 produces smaller particles with a narrower size distribution and mainly single- or few-domain interiors, whereas ethanol yields larger particles built from 2–4 nm crystallites with domain aggregation. Edge defects appear in both but energy-dispersive X-ray spectroscopy (EDS) is broadly uniform with local fluctuations in ethanol. X-ray photoelectron spectroscopy (XPS), supported by an attenuation model, indicates an ∼1 nm oxide overlayer that suppresses Mn 2p intensity; correcting for it returns Mn toward the bulk value. UV–NIR and photoluminescent spectra independently support a thin oxide shell. Composition-based thermodynamic descriptors place LN2 closer to bulk mixing parameters, while ethanol raises ΔH_mix and lowers Ω. Cooling simulations are consistent (LN2 ∼ 0.1 μs quench, ethanol ∼1 μs). In conclusion, these results connect solvent-controlled kinetics and thermodynamics to crystalline state and surface chemistry, informing surface control of HEA nanoparticles.

Femtosecond Laser Ablation↗
DOE OSTI2018

Shedding light on black titania

The article by Selcuk, Zhou, and Selloni provides a model on the formation of black titania representing how a collective, long distance and long time scale phenomenon may be captured at the atomic level, and demonstrates the critical importance of defect interactions over great distances. Moreover, it illustrates the importance of studies on materials structure/property under synthesis conditions.

Glezakou, Vassiliki-Alexandra↗
DOE OSTI2021

Dynamic behavior of chemically tunable mechano-responsive hydrogels

Here, using theory and simulation, we model the mechanical behavior of gels that encompass loops and dangling chain ends. If the loops remain folded and dangling ends are chemically inert, then these topological features just serve as defects. If, however, the loops unfold to expose the hidden (“cryptic”) binding sites and the ends of the dangling chains are reactive, these moieties can form bonds that improve the gel's mechanical properties. For gels with a lower critical solubility temperature (LCST), we systematically switch on the possible unfolding and binding events. To quantify the resulting effects, we derive equations for the gel's equilibrium and dynamic elastic moduli. We also use a finite element approach to simulate the gel's response to deformation and validate the analytic calculations. Herein, we show that the equilibrium moduli are highly sensitive to the presence of unfolding and binding transitions. The dynamical moduli are sensitive not only to these structural changes, but also to the frequency of deformation. For example, when reactive ends bind to exposed cryptic sites at T = 29 °C and relatively high frequency, the storage shear modulus is 119% greater than the corresponding equilibrium value, while the storage Young's modulus is 109% greater than at equilibrium. These findings provide guidelines for tuning the chemical reactivity of loops and dangling ends and the frequency of deformation to tailor the mechano-responsive behavior of polymer networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Role of KASH domain lengths in the regulation of LINC complexes

The linker of the nucleoskeleton and cytoskeleton (LINC) complex is formed by the conserved interactions between Sad-1 and UNC-84 (SUN) and Klarsicht, ANC-1, SYNE homology (KASH) domain proteins, providing a physical coupling between the nucleoskeleton and cytoskeleton that mediates the transfer of physical forces across the nuclear envelope. The LINC complex can perform distinct cellular functions by pairing various KASH domain proteins with the same SUN domain protein. For example, in Caenorhabditis elegans, SUN protein UNC-84 binds to two KASH proteins UNC-83 and ANC-1 to mediate nuclear migration and anchorage, respectively. In addition to distinct cytoplasmic domains, the luminal KASH domain also varies among KASH domain proteins of distinct functions. Here, we combined in vivo C. elegans genetics and in silico molecular dynamics simulations to understand the relation between the length and amino acid composition of the luminal KASH domain, and the function of the SUN–KASH complex. We show that longer KASH domains can withstand and transfer higher forces and interact with the membrane through a conserved membrane proximal EEDY domain that is unique to longer KASH domains. In agreement with our models, our in vivo results show that swapping the KASH domains of ANC-1 and UNC-83, or shortening the KASH domain of ANC-1, both result in a nuclear anchorage defect in C. elegans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Electric field driven domain wall dynamics in BaTiO 3 nanoparticles

We report a detailed investigation into the response of single BaTiO 3 (BTO) nanocrystals under applied electric fields (E-field) using Bragg coherent diffraction imaging. Our study reveals pronounced domain wall migration and expansion of a sample measure under applied electric field. The changes are most prominent at the surface of the nanocrystal, where the lack of external strain allows greater domain wall mobility. The observed domain shifts are correlated to the strength and orientation of the applied E-field, following a side-by-side domain model from Suzana []. Notably, we identified a critical electric field strength of 3 MV/m, which leads to irreversible structural changes, suggesting plastic deformation. The findings highlight how surface effects and intrinsic defects contribute to the enhanced dielectric properties of BTO at the nanoscale, in contrast to bulk materials, where strain limits domain mobility. These findings deepen our understanding of nanoscale dielectric behavior and inform the design of advanced nanoelectronic devices. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Mechanism of the Generation of Donor–Acceptor Pairs in Heavily Doped n-ZrNiSn with the Ga Acceptor Impurity

The nature of the mechanism of the simultaneous generation of donor–acceptor pairs under heavy doping of n-ZrNiSn intermetallic semiconductor with the Ga acceptor impurity is established. Such spatial arrangement in the crystal lattice of ZrNiSn{sub 1–x}Ga{sub x} is found when the rate of movement of the Fermi level εF found from calculations of the density distribution of electron states coincides with that experimentally established from dependences lnρ(1/T). It is shown that when the Ga impurity atom (4s{sup 2}4p{sup 1}) occupies the 4b sites of Sn atoms (5s{sup 2}5p{sup 2}), structural defects of both acceptor nature and donor nature in the form of vacancies in the 4b site are simultaneously generated. The results are discussed in the scope of the Shklovskii–Efros model of a heavily doped and compensated semiconductor.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Peridynamic Theory as a New Paradigm for Multiscale Modeling of Sintering

Sintering is a component fabrication process in which powder is compacted by pressing or some other means and then held at elevated temperature for a period of hours. The powder grains bond with each other, leading to the formation of a solid component with much lower porosity, and therefore higher density and higher strength, than the original powder compact. In this project, we investigated a new way of computationally modeling sintering at the length scale of grains. The model uses a high-fidelity, three-dimensional representation with a few hundred nodes per grain. The numerical model solves the peridynamic equations, in which nonlocal forces allow representation of the attraction, adhesion, and mass diffusion between grains. The deformation of the grains is represented through a viscoelastic material model. The project successfully demonstrated the use of this method to reproduce experimentally observed features of material behavior in sintering, including densification, the evolution of microstructure, and the occurrence of random defects in the sintered solid.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron

Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development. Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data. We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Phase equilibrium of liquid water and hexagonal ice from enhanced sampling molecular dynamics simulations

We study the phase equilibrium between liquid water and ice Ih modeled by the TIP4P/Ice interatomic potential using enhanced sampling molecular dynamics simulations. Our approach is based on the calculation of ice Ih-liquid free energy differences from simulations that visit reversibly both phases. The reversible interconversion is achieved by introducing a static bias potential as a function of an order parameter. The order parameter was tailored to crystallize the hexagonal diamond structure of oxygen in ice Ih. Furthermore, we analyze the effect of the system size on the ice Ih-liquid free energy differences, and we obtain a melting temperature of 270 K in the thermodynamic limit. This result is in agreement with estimates from thermodynamic integration (272 K) and coexistence simulations (270 K). Since the order parameter does not include information about the coordinates of the protons, the spontaneously formed solid configurations contain proton disorder as expected for ice Ih.

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

Modeling ammonia-fueled co-flow dual-channel protonic-ceramic fuel cells

This paper reports the model development for a dual-channel protonic-ceramic fuel cell (PCFC) operating on ammonia fuel. The model considers the coupled interactions of several physical and chemical processes, including three-dimensional heat conduction within the bipolar plates and the membrane-electrode assembly (MEA), one-dimensional flow within the fuel and air channels, detailed heterogeneous catalytic reactions within the porous composite anode structure, Butler–Volmer representation of the charge-transfer chemistry, and Nernst–Planck transport of three charged defects (protons, oxygen vacancies, and small polarons) within the dense electrolyte membrane. The membrane-electrode assembly is composed of a Ni-BCZYYb (BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3-δ ) anode, a BCZYYb electrolyte membrane, and a BCFZY (BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ ) cathode. Chemical and physical parameters for the MEA model are established using previously published button-cell data. One aspect of the study is to investigate the partial ammonia decomposition upstream of the fuel cell. Such fuel cracking increases the H 2 content of the fuel entering the PCFC, which may have benefits. However, endothermic ammonia pyrolysis within the composite anode structure assists with thermal control of the cell. The dual-channel model can be considered as the unit cell of a full fuel-cell stack.

25 ENERGY STORAGE↗