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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Systematization of Password Manager Use Cases and Design Paradigms

Despite efforts to replace them, passwords remain the primary form of authentication on the web. Password managers seek to address many of the problems with passwords by helping users generate, store, and fill strong and unique passwords. Even though experts frequently recommend password managers, there is limited information regarding their usability. To aid in designing such usability studies, we systematize password manager use cases, identifying ten essential use cases, three recommended use cases, and four extended use cases. We also systematize the system designs employed to satisfy these use cases, designs that should be examined in usability studies to understand their relative strengths and weaknesses. Finally, we describe observations from 136 cognitive walkthroughs exploring the identified essential use cases in eight popular managers. Ultimately, we expect that this work will serve as the foundation for an explosion of new research into the usability of password managers.

Simmons, James↗
DOE OSTI2022

Composition‐Conditioning Agent for Doped Spiro‐OMeTAD to Realize Highly Efficient and Stable Perovskite Solar Cells

Abstract The doped Spiro‐OMeTAD hole transport layer (HTL) formed using the lithium bis(trifluoromethane) sulfonimide salt and 4‐tert‐butylpyridine with phenethylammonium iodide surface treatment on a perovskite film has continuously dominated the record power conversion efficiencies (PCEs) of perovskite solar cells (pero‐SCs). However, unstable HTL compositions and iodide salts can cause severe device degradation. In this study, an HTL composition‐conditioning agent (CCA), Spiro‐BD‐2OEG, is designed, which contains a Spiro‐OMeTAD‐like backbone, functional pyridine units, and oligo (ethylene glycol) chains. This finely designed CCA presents good miscibility with Spiro‐OMeTAD and its dopants and acts as a conditioning agent through weak bond interactions. As a result, the CCA‐regulated HTL shows a pinhole‐free and smooth morphology with enhanced Spiro‐OMeTAD ordering and improves dopant stability. In addition, the gradient‐distributed CCA in the HTL can narrow the energy level offset with the valence band of the perovskite. The resultant pero‐SCs exhibit an excellent PCE of 24.19% without any interface treatment and weak size dependence. A remarkable PCE of 22.63% is obtained even for a 1.004‐cm 2 device. Importantly, the strategy shows good universality and significantly promotes the long‐term stability of the pero‐SCs based on the classical doped Spiro‐OMeTAD.

Chemistry↗
DOE OSTI2021

2-Group global symmetries and anomalies in six-dimensional quantum field theories

We examine six-dimensional quantum field theories through the lens of higher-form global symmetries. Every Yang-Mills gauge theory in six dimensions, with field strength ƒ (2) , naturally gives rise to a continuous 1-form global symmetry associated with the 2-form instanton current J (2) ~ * Tr (ƒ (2) $\wedge$ ƒ (2) ). We show that suitable mixed anomalies involving the gauge field ƒ (2) and ordinary 0-form global symmetries, such as flavor or Poincaré symmetries, lead to continuous 2-group global symmetries, which allow two flavor currents or two stress tensors to fuse into the 2-form current J (2) . We discuss several features of 2-group symmetry in six dimensions, many of which parallel the four-dimensional case. The majority of six-dimensional supersymmetric conformal field theories (SCFTs) and little string theories have infrared phases with non-abelian gauge fields. We show that the mixed anomalies leading to 2-group symmetries can be present in little string theories, but that they are necessarily absent in SCFTs. This allows us to establish a previously conjectured algorithm for computing the ’t Hooft anomalies of most SCFTs from the spectrum of weakly-coupled massless particles on the tensor branch of these theories. We then apply this understanding to prove that the a -type Weyl anomaly of all SCFTs with a tensor branch must be positive, a > 0.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Ordering effects on deformation substructures and strain hardening behavior of a CrCoNi based medium entropy alloy

Here, a CrCoNi based medium entropy alloy with small additions of Ti, Al and Nb (denoted as (CrCoNi) 93 Al 4 Ti 2 Nb) in the as-quenched condition, exhibits tensile properties comparable to those of the equiatomic CrCoNi alloy at room temperature. Dark field transmission electron microscopy (TEM), atomic resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) together with atom probe tomography (APT) show that spatially-localized long range ordering (LRO) L1 2 domains exist in this alloy. The evolution of deformation substructure with plastic deformation in this alloy was characterized using electron backscatter diffraction (EBSD), electron channeling contrast imaging (ECCI) and STEM based techniques including the recently developed weak beam dark field STEM imaging. Plastic deformation occurs by the slip of a/2<110>dislocations, which are narrowly dissociated into Shockley partial dislocations on {111} slip planes. Their dissociation distances in the (CrCoNi) 93 Al 4 Ti 2 Nb alloy are much smaller than the widths of the corresponding partials in the equiatomic CrCoNi alloy due to one or more of the minor alloying elements (Al, Ti, Nb). Dislocation slip in this alloy has a pronounced planar character. The leading dislocations in slip bands glide as pairs due to the existence of LRO domains. Multipoles were formed through the slip of dislocations with opposite signs on adjacent {111} slip planes. Those multipoles serve as building blocks for the formation of subgrain structures consisting of fine slip bands. The distances between slip bands were continuously refined during plastic deformation and dynamic refinement of slip bands plays a crucial role in strain hardening. The effects of LRO domains on planar dislocation slip, the deactivation of deformation twinning and strain hardening of this alloy are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Empirical probability and machine learning analysis of m , n = 2, 1 tearing mode onset parameter dependence in DIII-D H-mode scenarios

m, n = 2, 1 tearing mode onset empirical probability and machine learning analyses of a multiscenario DIII-D database of over 14 000 H-mode discharges show that the normalized plasma beta, the rotation profile, and the magnetic equilibrium shape have the strongest impact on the 2,1 tearing mode stability, in qualitative agreement with neoclassical tearing modes (m and n are the poloidal and toroidal mode numbers, respectively). In addition, 2,1 tearing modes are most likely to destabilize when n > 1 tearing modes are already present in the core plasma. The covariance matrix of tearing sensitive plasma parameters takes a nearly block-diagonal form, with the blocks incorporating thermodynamic, current and safety factor profile, separatrix shape, and plasma flow parameters, respectively. This suggests a number of paths to improved stability at fixed pressure and edge safety factor primarily by preserving a minimum of 1 kHz differential rotation, increasing the minimum safety factor above unity, using upper single null magnetic configuration, and reducing the core impurity radiation. In addition, lower triangularity, lower elongation, and lower pedestal pressure may also help to improve stability. Furthermore, the electron and ion temperature, collisionality, resistivity, internal inductance, and the parallel current gradient appear to only weakly correlate with the 2,1 tearing mode onsets in this database.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Nanoscale Imaging of Magnetotransport around a Circular 𝑝−𝑛 Junction in Graphene

Magnetoresistance studies of 2D systems are often shaped by the motion of electrons that occupy spatially confined wave functions, such as topological edge modes and disorder-induced bound states. Directly probing how such states form and behave in situ , under applied currents, provides a clear way of connecting microscopic physics to the macroscopic transport response. Here, in this Letter, scanning tunneling potentiometry is used to probe the local, current-induced electrochemical potential of carriers in graphene near circular 𝑝−𝑛 junctions in an out-of-plane magnetic field ranging from 0 to 1.4 T. These measurements provide detailed information about the motion of carriers at the nanometer scale, revealing how it evolves with increasing field. The electrochemical potential displays distinct patterns, such as dipoles, spirals, and concentric disks in weak, moderate, and high fields, respectively. The size and orientation of these patterns can be used to understand how local carrier dynamics change in different transport regimes as well as to directly extract physical parameters such as the electron mean free path and cyclotron diameter.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electronic and magnetic properties of quasi-one-dimensional osmium halide OsCl 4

Using ab initio density functional theory, we study the electronic and magnetic properties of the van der Waals chain material OsCl 4 . In the nonmagnetic state, a strongly anisotropic band structure was observed, in agreement with its anticipated one-dimensional crystal geometry. Based on Wannier functions, we found that the four electrons of the 5d Os atom form a low-spin S = 1 state, with a large crystal field between the d xz/yz and d xy orbitals, corresponding to a strong Jahn–Teller distortion (Q 3 < 0). As a consequence, the magnetic properties are mainly contributed by the d xz/yz states. Furthermore, when a Mott gap develops after the introduction of the Hubbard U and Hund coupling J, we found that the staggered spin order is the most likely magnetic state, namely, spins arranged as (↑-↓-↑-↓) with π wavevector along the chain. In addition, the energy differences between various spin states are small, suggesting a weak magnetic exchange coupling along the chain. Overall, our results provide guidance to experimentalists and theorists working on quasi-one-dimensional osmium halides chain materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Symmetric carbon tetramers forming spin qubits in hexagonal boron nitride

Abstract Point defect quantum bits in semiconductors have the potential to revolutionize sensing at atomic scales. Currently, vacancy-related defects are at the forefront of high spatial resolution and low-dimensional sensing. On the other hand, it is expected that impurity-related defect structures may give rise to new features that could further advance quantum sensing in low dimensions. Here, we study the symmetric carbon tetramer clusters in hexagonal boron nitride and propose them as spin qubits for sensing. We utilize periodic-DFT and quantum chemistry approaches to reliably and accurately predict the electronic, optical, and spin properties of the studied defect. We show that the nitrogen-centered symmetric carbon tetramer gives rise to spin state-dependent optical signals with strain-sensitive intersystem crossing rates. Furthermore, the weak hyperfine coupling of the defect to their spin environments results in a reduced electron spin resonance linewidth that can enhance sensitivity.

Chemistry↗
DOE OSTI2022

Lewis acid–base pair doping of p-type organic semiconductors

Doping is required to increase the electrical conductivity of organic semiconductors for uses in electronic and energy conversion devices. The limited number of commonly used p-type dopants suggests that new dopants or doping mechanisms could improve the efficiency of doping and provide new means for processing doped polymers. Drawing on Lewis acid–base pair chemistry, we combined Lewis acid dopant B(C 6 F 5 ) 3 (BCF) with the weak Lewis base benzoyl peroxide (BPO). The detailed behavior of p-type doping of the model polymer poly(3-hexylthiophene) (P3HT) with this Lewis acid–base pair in solution was examined. Solution 19F-NMR spectra confirmed the formation of the expected counterion, as well as side products from reactions with solvent. BCF : BPO was also found to efficiently dope a range of semiconducting polymers with varying chemical structures demonstrating that the BCF : BPO combination has an effective electron affinity of at least 5.3 eV. In thin films of regioregular P3HT cast from the doped solutions, delocalized polarons formed due to the large counterions leading to a large polaron-counterion distance. At and above 0.2 eq. BCF : BPO doping, amorphous areas of the film became doped, disrupting the structural order of the films. Despite the change in structural order, thin films of regioregular P3HT doped with 0.2 eq. BCF : BPO had a conductivity of 25 S cm -1 . This study demonstrates the effectiveness of a two-component Lewis acid–base doping mechanism and suggests additional two-component Lewis acid–base chemistries should be explored.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Aluminosilicate colloidal gels: from the early age to the precipitation of zeolites

Aluminosilicate hydrogels are often considered to be precursors for the crystallisation of zeolites carried out under hydrothermal conditions. The preparation of mechanically homogeneous aluminosilicate gels enables the study of these materials through bulk rheology and observation of the aging dynamics until the precipitation of crystalline zeolites. The first part of this study deals with the establishment of ternary state diagrams, in order to identify the range of chemical formulations that enable preparation of single-phase homogeneous gels. Then, by studying the viscoelastic moduli during the gelation reaction, and by yielding the gel under large deformation, we propose an empirical law considering the partial order of reaction on each chemical element, to predict the gelation time according to the chemical formulation. The scaling behavior of the elastic properties of this colloidal gel shows a transition from a strong link behavior to a weak link regime. Long term aging results in the shrinkage of the gel, accompanied by syneresis of interstitial liquid at the surface. Zeolites precipitate through crystallisation by a particle attachment mechanism, when thermodynamic equilibrium is reached. The stoichiometry of the precipitated zeolites is not only consistent with the concentration of the remaining species in the supernatant but, surprisingly, it is also very close to the partial order of the reaction of the chemical elements involved in the determination of the critical gel point. This indicates a strong correlation between the morphology of the soft amorphous gel network that is formed at an early age and those of the final solid precipitated crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cosmic neutrino decoupling and its observable imprints: insights from entropic-dual transport

Abstract Very different processes characterize the decoupling of neutrinos to form the cosmic neutrino background (CνB) and the much later decoupling of photons from thermal equilibrium to form the cosmic microwave background (CMB). The CνB emerges from the fuzzy, energy-dependent neutrinosphere and encodes the physics operating in the early universe in the temperature rangeT∼ 10 MeV toT∼ 10 keV. This is the epoch where beyond Standard Model (BSM) physics, especially in the neutrino sector, may be influential in setting the light element abundances, the necessarily distorted fossil neutrino energy spectra, and other light particle energy density contributions. Here we use techniques honed in extensive CMB studies to analyze the CνB as calculated in detailed neutrino energy transport and nuclear reaction simulations of the protracted weak decoupling and primordial nucleosynthesis epochs. Our moment method, relative entropy, and differential visibility approach can leverage future high precision CMB and light element primordial abundance measurements to provide new insights into the CνB and any BSM physics it encodes. We demonstrate that the evolution of the energy spectrum of the CνB throughout the weak decoupling epoch is accurately captured in the Standard Model by only three parameters per species, a non-trivial conclusion given the deviation from thermal equilibrium and the impact of the decrease of electron-positron pairs. Furthermore, we can interpret each of the three parameters as physical characteristics of a non-equilibrium system. Though the treatment presented here makes some simplifying assumptions including ignoring neutrino flavor oscillations, the success of our compact description within the Standard Model motivates its use also in BSM scenarios. We further demonstrate how observations of primordial light element abundances can be used to place constraints on the CνB energy spectrum, deriving response functions that can be applied for general deviations from a thermal spectrum. Combined with the description of those deviations that we develop here, our methods provide a convenient and powerful framework to constrain the impact of BSM physics on the CνB.

Astronomy & Astrophysics↗
DOE OSTI2023

Entanglement entropy, single-particle occupation probabilities, and short-range correlations

For quantum many-body systems with short-range correlations (SRCs), the intimate relationship between their magnitude, the behavior of the single-particle occupation probabilities at momenta larger than the Fermi momentum, and the entanglement entropy is a new qualitative aspect not studied and exploited yet. A large body of recent condensed matter studies indicates that the time evolution of the entanglement entropy describes the nonequilibrium dynamics of isolated and strongly interacting many-body systems, in a manner similar to the Boltzmann entropy, which is strictly defined for dilute and weakly interacting many-body systems. Both theoretical and experimental studies in nuclei and cold atomic gases have shown that the fermion momentum distribution has a generic behavior n(k)=C/k 4 at momenta larger than the Fermi momentum, due to the presence of SRCs, with approximately 20% of the particles having momenta larger than the Fermi momentum. Further, the presence of the long momentum tails in the presence of SRCs changes the textbook relation between the single-particle kinetic energy and occupation probabilities, n mf ⁡(k) = 1/{1+ exp ⁡β[ϵ⁡(k)-μ]} for momenta very different form the Fermi momentum, particularly for dynamics processes. SRCs induced high-momentum tails of the single-particle occupation probabilities increase the entanglement entropy of fermionic systems, which in its turn affects the dynamics of many nuclear reactions, such as heavy-ion collisions and nuclear fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

MicroRNAs as diagnostic and prognostic biomarkers of age-related macular degeneration: advances and limitations

A main cause of vision loss in the elderly is age-related macular degeneration (AMD). Among the cellular, biochemical, and molecular changes linked to this disease, inflammation and angiogenesis appear as being crucial in AMD pathogenesis and progression. There are two forms of the disease: dry AMD, accounting for 80–90% of cases, and wet AMD. The disease usually begins as dry AMD associated with retinal pigment epithelium and photoreceptor degeneration, whereas wet AMD is associated with choroidal neovascularization resulting in severe vision impairment. The new vessels are largely malformed, leading to blood and fluid leakage within the disrupted tissue, which provokes inflammation and scar formation and results in retinal damage and detachment. MicroRNAs are dysregulated in AMD and may facilitate the early detection of the disease and monitoring disease progression. Two recent reviews of microRNAs in AMD had indicated weaknesses or limitations in four earlier investigations. Studies in the last three years have shown considerable progress in overcoming some of these concerns and identifying specific microRNAs as biomarkers for AMD. Further large-scale studies are warranted using appropriate statistical methods to take into account gender and age disparity in the study populations and confounding factors such as smoking status.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Pulse Radiolysis Investigation of Radicals Derived from Water-Soluble Cyanine Dyes: Implications for Super-resolution Microscopy

Light-induced blinking, an inherent feature of many forms of super-resolution microscopy, has been linked to transient reduction of the fluorescent cyanine dye used as an imaging agent. There is, however, only scant literature information related to one-electron reduced cyanine dyes, especially in an aqueous environment. Here, we examine a small series of cyanine dyes, possessing disparate π-conjugation lengths, under selective reducing or oxidizing conditions. The experiment allows recording of both differential absorption spectra and decay kinetics of the resultant one-electron reduced or oxidized transient species in water. Relative to the ground state, absorption transitions for the various radicals are weak and somewhat broadened but do allow correlation with the π-conjugation length. In all cases, absorption maxima lie to the blue of the main ground-state transition. Under anaerobic conditions, the transient species decay on the microsecond to millisecond time scale, with the mean lifetime depending on molecular structure, radiation dose, and dye concentration. The experimental absorption spectra recorded for the one-electron reduced radicals and the presumed dimer cation radical compare well to spectra obtained from time-dependent density functional theory calculations. Furthermore, the results allow conclusions to be drawn regarding the plausibility of the reduced species being responsible for light-induced blinking in direct stochastic optical reconstruction microscopy.

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

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetic properties of the double trillium lattice antiferromagnet KBaCr 2 ⁢(PO 4 ) 3

Trillium lattices formed by corner-shared triangular units are the platform for magnetic frustration in three dimensions. Herein, we report structural and magnetic properties of the Cr-based (S = 3/2) double trillium lattice material KBaCr 2 ⁢(PO 4 ) 3 studied by x-ray diffraction, dc and ac magnetization, heat capacity, thermal conductivity, and 31 P nuclear magnetic resonance (NMR) measurements complemented by density-functional band-structure calculations. Magnetization, heat capacity, and 31 P NMR measurements reveal the magnetic transition at T N⁢1 ≃ 12.5 K in zero field followed by another transition (T N⁢2 ) at low temperatures in weak applied fields. The 31 P spin-lattice relaxation rate in the ordered state follows the T 3 behavior indicative of the two-magnon Raman process. Finally, the spin lattice of KBaCr 2 ⁢(PO 4 ) 3 comprises two crystallographically nonequivalent ferromagnetic sublattices that are coupled antiferromagnetically, thus eliminating frustration in this trillium network and leading to weak ferromagnetism in the vicinity of T N⁢1 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗