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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Technical Note: Robust measurement of the slice-sensitivity profile in breast tomosynthesis

Purpose: The purpose of this work is to improve the repeatability of the measurement of the slice-sensitivity profile (SSP) in reconstructed breast tomosynthesis volumes. Methods: A grid of aluminum ball-bearings (BBs) within a PMMA phantom was imaged on breast tomosynthesis systems from three different manufacturers. The full-width half-maximum (FWHM) values were measured for the SSPs of the BBs in the reconstructed volumes. The effect of transforming the volumes from a Cartesian coordinate system (CCS) to a cone-beam coordinate system (CBCS) on the variability in the FWHM values was assessed. Results: Transforming the volumes from a CCS to a CBCS before measuring the SSPs reduced the coefficient of variation (COV) in the measurements of FWHM in repeated measurements by 56% and reduced the dependence of the FWHM values on the location of the BBs within the reconstructed volume by 76%. Conclusions: Measuring the SSP in the volumes in a CBCS improves the robustness of the measurement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Molecular ligand modulation of palladium nanocatalysts for highly efficient and robust heterogeneous oxidation of cyclohexenone to phenol

Metallic nanoparticles are emerging as an exciting class of heterogeneous catalysts with the potential advantages of exceptional activity, stability, recyclability, and easier separation than homogeneous catalysts. The traditional colloid nanoparticle syntheses usually involve strong surface binding ligands that could passivate the surface active sites and result in poor catalytic activity. The subsequent removal of surface ligands could reactivate the surface but often leads to metal ion leaching and/or severe Ostwald ripening with diminished catalytic activity or poor stability. Molecular ligand engineering represents a powerful strategy for the design of homogeneous molecular catalysts but is insufficiently explored for nanoparticle catalysts to date. We report a systematic investigation on molecular ligand modulation of palladium (Pd) nanoparticle catalysts. Our studies show that β-functional groups of butyric acid ligand on Pd nanoparticles can significantly modulate the catalytic reaction process to modify the catalytic activity and stability for important aerobic reactions. With a β-hydroxybutyric acid ligand, the Pd nanoparticle catalysts exhibit exceptional catalytic activity and stability with an unsaturated turnover number (TON) >3000 for dehydrogenative oxidation of cyclohexenone to phenol, greatly exceeding that of homogeneous Pd(II) catalysts (TON, ~30). This study presents a systematic investigation of molecular ligand modulation of nanoparticle catalysts and could open up a new pathway toward the design and construction of highly efficient and robust heterogeneous catalysts through molecular ligand engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Above 400-K robust perpendicular ferromagnetic phase in a topological insulator

Here, the quantum anomalous Hall effect (QAHE) that emerges under broken time-reversal symmetry in topological insulators (TIs) exhibits many fascinating physical properties for potential applications in nanoelectronics and spintronics. However, in transition metal–doped TIs, the only experimentally demonstrated QAHE system to date, the QAHE is lost at practically relevant temperatures. This constraint is imposed by the relatively low Curie temperature ( T c ) and inherent spin disorder associated with the random magnetic dopants. We demonstrate drastically enhanced T c by exchange coupling TIs to Tm 3 Fe 5 O 12 , a high- T c magnetic insulator with perpendicular magnetic anisotropy. Signatures showing that the TI surface states acquire robust ferromagnetism are revealed by distinct squared anomalous Hall hysteresis loops at 400 K. Point-contact Andreev reflection spectroscopy confirms that the TI surface is spin-polarized. The greatly enhanced T c , absence of spin disorder, and perpendicular anisotropy are all essential to the occurrence of the QAHE at high temperatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A sensitive and robust thin-film x-ray detector using 2D layered perovskite diodes

Solid-state radiation detectors, using crystalline semiconductors to convert radiation photons to electrical charges, outperform other technologies with high detectivity and sensitivity. Here, we demonstrate a thin-film x-ray detector comprised with highly crystalline two-dimensional Ruddlesden-Popper phase layered perovskites fabricated in a fully depleted p-i-n architecture. It shows high diode resistivity of 10 12 ohm·cm in reverse-bias regime leading to a high x-ray detecting sensitivity up to 0.276 C Gy air –1 cm –3 . Such high signal is collected by the built-in potential underpinning operation of primary photocurrent device with robust operation. The detectors generate substantial x-ray photon–induced open-circuit voltages that offer an alternative detecting mechanism. Furthermore, our findings suggest a new generation of x-ray detectors based on low-cost layered perovskite thin films for future x-ray imaging technologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Atomically engineered cobaltite layers for robust ferromagnetism

Emergent phenomena at heterointerfaces are directly associated with the bonding geometry of adjacent layers. Effective control of accessible parameters, such as the bond length and bonding angles, offers an elegant method to tailor competing energies of the electronic and magnetic ground states. In this study, we construct unit-thick syntactic layers of cobaltites within a strongly tilted octahedral matrix via atomically precise synthesis. The octahedral tilt patterns of adjacent layers propagate into cobaltites, leading to a continuation of octahedral tilting while maintaining substantial misfit tensile strain. These effects induce severe rumpling within an atomic plane of neighboring layers, further triggering the electronic reconstruction between the splitting orbitals. First-principles calculations reveal that the cobalt ions transit to a higher spin state level upon octahedral tilting, resulting in robust ferromagnetism in ultrathin cobaltites. This work demonstrates a design methodology for fine-tuning the lattice and spin degrees of freedom in correlated quantum heterostructures by exploiting epitaxial geometric engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Perovskite grain wrapping by converting interfaces and grain boundaries into robust and water-insoluble low-dimensional perovskites

Stabilizing perovskite solar cells requires consideration of all defective sites in the devices. Substantial efforts have been devoted to interfaces, while stabilization of grain boundaries received less attention. Here, we report on a molecule tributyl(methyl)phosphonium iodide (TPI), which can convert perovskite into a wide bandgap one-dimensional (1D) perovskite that is mechanically robust and water insoluble. Mixing TPI with perovskite precursor results in a wrapping of perovskite grains with both grain surfaces and grain boundaries converted into several nanometer-thick 1D perovskites during the grain formation process as observed by direct mapping. The grain wrapping passivates the grain boundaries, enhances their resistance to moisture, and reduces the iodine released during light soaking. The perovskite films with wrapped grains are more stable under heat and light. The best device with wrapped grains maintained 92.2% of its highest efficiency after light soaking under 1-sun illumination for 1900 hours at 55°C open-circuit condition.

14 SOLAR ENERGY↗
DOE OSTI2016

Discovery of robust in-plane ferroelectricity in atomic-thick SnTe

Stable ferroelectricity with high transition temperature in nanostructures is needed for miniaturizing ferroelectric devices. Here, we report the discovery of the stable in-plane spontaneous polarization in atomic-thick tin telluride (SnTe), down to a 1–unit cell (UC) limit. The ferroelectric transition temperature T c of 1-UC SnTe film is greatly enhanced from the bulk value of 98 kelvin and reaches as high as 270 kelvin. Moreover, 2- to 4-UC SnTe films show robust ferroelectricity at room temperature. The interplay between semiconducting properties and ferroelectricity in this two-dimensional material may enable a wide range of applications in nonvolatile high-density memories, nanosensors, and electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spontaneous formation of robust two-dimensional perovskite phases

The two-dimensional on three-dimensional (2D/3D) perovskite bilayer heterostructure can improve the stability and performance of perovskite solar cells. We show that the 2D/3D perovskite stack in a device evolves dynamically during its end-of-life decomposition. Initially phase-pure 2D interlayers can evolve differently, resulting in different device stabilities. We show that a robust 2D interlayer can be formed using mixed solvents to regulate its crystallinity and phase purity. The resulting 2D/3D devices achieved 25.9% efficiency and had good durability, retaining 91% of their initial performance after 1074 hours at 85°C using maximum power point tracking.

14 SOLAR ENERGY↗
DOE OSTI2015

Archaeal Inorganic Pyrophosphatase Displays Robust Activity under High-Salt Conditions and in Organic Solvents

Soluble inorganic pyrophosphatases (PPAs) that hydrolyze inorganic pyrophosphate (PP i ) to orthophosphate (P i ) are commonly used to accelerate and detect biosynthetic reactions that generate PP i as a by-product. Current PPAs are inactivated by high salt concentrations and organic solvents, which limits the extent of their use. Here we report a class A type PPA of the haloarchaeon Haloferax volcanii (HvPPA) that is thermostable and displays robust PP i -hydrolyzing activity under conditions of 25% (vol/vol) organic solvent and salt concentrations from 25 mM to 3 M. HvPPA was purified to homogeneity as a homohexamer by a rapid two-step method and was found to display non-Michaelis-Menten kinetics with a V max of 465 U · mg –1 for PP i hydrolysis (optimal at 42°C and pH 8.5) and Hill coefficients that indicated cooperative binding to PP i and Mg 2+ . Similarly to other class A type PPAs, HvPPA was inhibited by sodium fluoride; however, hierarchical clustering and three-dimensional (3D) homology modeling revealed HvPPA to be distinct in structure from characterized PPAs. In particular, HvPPA was highly negative in surface charge, which explained its extreme resistance to organic solvents. To demonstrate that HvPPA could drive thermodynamically unfavorable reactions to completion under conditions of reduced water activity, a novel coupled assay was developed; HvPPA hydrolyzed the PP i by-product generated in 2 M NaCl by UbaA (a “salt-loving” noncanonical E1 enzyme that adenylates ubiquitin-like proteins in the presence of ATP). Altogether, we demonstrate HvPPA to be useful for hydrolyzing PP i under conditions of reduced water activity that are a hurdle to current PPA-based technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

NS3 from Hepatitis C Virus Strain JFH-1 Is an Unusually Robust Helicase That Is Primed To Bind and Unwind Viral RNA

Hepatitis C viruses (HCV) encode a helicase enzyme that is essential for viral replication and assembly (nonstructural protein 3 [NS3]). This helicase has become the focus of extensive basic research on the general helicase mechanism, and it is also of interest as a novel drug target. Despite the importance of this protein, mechanistic work on NS3 has been conducted almost exclusively on variants from HCV genotype 1. Our understanding of NS3 from the highly active HCV strains that are used to study HCV genetics and mechanism in cell culture (such as JFH-1) is lacking. We therefore set out to determine whether NS3 from the replicatively efficient genotype 2a strain JFH-1 displays novel functional or structural properties. Using biochemical assays for RNA binding and duplex unwinding, we show that JFH-1 NS3 binds RNA much more rapidly than the previously studied NS3 variants from genotype 1b. Unlike NS3 variants from other genotypes, JFH-1 NS3 binds RNA with high affinity in a functionally active form that is capable of immediately unwinding RNA duplexes without undergoing rate-limiting conformational changes that precede activation. Unlike other superfamily 2 (SF2) helicases, JFH-1 NS3 does not require long 3' overhangs, and it unwinds duplexes that are flanked by only a few nucleotides, as in the folded HCV genome. To understand the physical basis for this, we solved the crystal structure of JFH-1 NS3, revealing a novel conformation that contains an open, positively charged RNA binding cleft that is primed for productive interaction with RNA targets, potentially explaining robust replication by HCV JFH-1. Genotypes of HCV are as divergent as different types of flavivirus, and yet mechanistic features of HCV variants are presumed to be held in common. One of the most well-studied components of the HCV replication complex is a helicase known as nonstructural protein 3 (NS3). We set out to determine whether this important mechanical component possesses biochemical and structural properties that differ between common strains such as those of genotype 1b and a strain of HCV that replicates with exceptional efficiency (JFH-1, classified as genotype 2a). Indeed, unlike the inefficient genotype 1b NS3, which has been well studied, JFH-1 NS3 is a superhelicase with strong RNA affinity and high unwinding efficiency on a broad range of targets. Crystallographic analysis reveals architectural features that promote enhanced biochemical activity of JFH-1 NS3. These findings show that even within a single family of viruses, drift in sequence can result in the acquisition of radically new functional properties that enhance viral fitness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Engineering Kluyveromyces marxianus as a Robust Synthetic Biology Platform Host

Throughout history, the yeast Saccharomyces cerevisiae has played a central role in human society due to its use in food production and more recently as a major industrial and model microorganism, because of the many genetic and genomic tools available to probe its biology. However, S. cerevisiae has proven difficult to engineer to expand the carbon sources it can utilize, the products it can make, and the harsh conditions it can tolerate in industrial applications. Other yeasts that could solve many of these problems remain difficult to manipulate genetically. Here, we engineered the thermotolerant yeast Kluyveromyces marxianus to create a new synthetic biology platform. Using CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats with Cas9)-mediated genome editing, we show that wild isolates of K. marxianus can be made heterothallic for sexual crossing. By breeding two of these mating-type engineered K. marxianus strains, we combined three complex traits—thermotolerance, lipid production, and facile transformation with exogenous DNA—into a single host. The ability to cross K. marxianus strains with relative ease, together with CRISPR-Cas9 genome editing, should enable engineering of K. marxianus isolates with promising lipid production at temperatures far exceeding those of other fungi under development for industrial applications. These results establish K. marxianus as a synthetic biology platform comparable to S. cerevisiae, with naturally more robust traits that hold potential for the industrial production of renewable chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification

Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 10 12 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Early immune response to Coccidioides is characterized by robust neutrophil and fibrotic macrophage recruitment and differentiation

Coccidioidomycosis, or Valley fever, is an emerging respiratory disease caused by soil-dwelling fungi of the Coccidioides genus that is expected to spread from the southwest into the central U.S. by 2050. While 60% of infections are asymptomatic, the other 40% of patients experience a range of symptoms, from self-limiting pneumonia to life-threatening disseminated disease. The immunological events that underlie the progression to severe disease remain underdefined. Here, we probed the early immune response to Coccidioides using a high dose of an attenuated strain of Coccidioides posadasii in a mouse model of infection coupled with single-cell RNA sequencing. At 24 h post-infection, robust immune infiltration is detected in the lung, marked by high levels of inflammatory PD-L1 + neutrophils and fungal-contact-dependent pro-fibrotic Spp1 + macrophages. These findings elucidate the early dynamics of the host response to Coccidioides and provide a deeper understanding of host-pathogen interactions in the lung.

Coccidioides↗
DOE OSTI2020

A Holistic Algorithmic Approach to Improving Accuracy, Robustness, and Computational Efficiency for Atmospheric Dynamics

Atmospheric weather and climate models must perform simulations very quickly to be useful. Therefore, modelers have traditionally focused on reducing computations as much as possible. However, in our new era of increasingly compute-capable hardware, data movement is now the prohibiting expense. This study examines the computational benefits of a new algorithmic approach to modeling atmospheric dynamics on scales relevant to weather and climate simulation. Rather than minimizing computations, this new approach considers the larger problem more holistically, including spatial accuracy, temporal accuracy, robustness (i.e., oscillations), on-node efficiency, and internode data transfers together at once. Numerical experiments demonstrate how computations can be strategically increased to simultaneously address each of these constraints while reducing data movement to adapt to modern accelerated hardware. The new algorithm can achieve at times up to 80% peak floating point throughput in single precision on the Nvidia Tesla V100 GPU, where the traditional approach is shown to only achieve single-digit floating point efficiency. Further, the new algorithm is twice as fast as a standard Runge--Kutta time integrator, and high-order accuracy with Weighted Essentially Non-Oscillatory (WENO) limiting came at less than 30% additional runtime cost on a GPU, thus increasing the accuracy per degree of freedom.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Learning Robust Marking Policies for Adaptive Mesh Refinement

Here in this work, we revisit the marking decisions made in the standard adaptive finite element method (AFEM). Experience shows that a naïve marking policy leads to inefficient use of computational resources for adaptive mesh refinement (AMR). Consequently, using AMR in practice often involves ad-hoc or time-consuming offline parameter tuning to set appropriate parameters for the marking subroutine. To address these practical concerns, we recast AMR as a Markov decision process in which refinement parameters can be selected on-the-fly at run time, without the need for pre-tuning by expert users. In this new paradigm, the refinement parameters are also chosen adaptively via a marking policy that can be optimized using methods from reinforcement learning. We use the Poisson equation to demonstrate our techniques on h- and hp-refinement benchmark problems, and our experiments suggest that superior marking policies remain undiscovered for many classical AFEM applications. Furthermore, an unexpected observation from this work is that marking policies trained on one family of PDEs are sometimes robust enough to perform well on problems far outside the training family. For illustration, we show that a simple hp-refinement policy trained on 2D domains with only a single re-entrant corner can be deployed on far more complicated 2D domains, and even 3D domains, without significant performance loss. For reproduction and broader adoption, we accompany this work with an open-source implementation of our methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Lack of robustness and accuracy of many numerical schemes for phase-field simulations

In this paper, we study the stability, accuracy and convergence behavior of various numerical schemes for phase-field modeling through a simple ODE model. Both theoretical analysis and numerical experiments are carried out on this ODE model to demonstrate the limitation of most numerical schemes that have been used in practice. One main conclusion is that the first-order fully implicit scheme is the only robust algorithm for phase-field simulations while all other schemes (that have been analyzed) may have convergence issue if the time step size is not exceedingly small. More specifically, by rigorous analysis in most cases, we have the following conclusions: (i) The first-order fully implicit scheme converges to the correct steady state solution for all time step sizes. In the case of multiple solutions, one of the solution branches always converges to the correct steady state solution. (ii) The first-order convex splitting scheme, which is equivalent to the first-order fully implicit scheme with a different time scaling, always converges to the correct steady state solution but may seriously lack numerical accuracy for transient solutions. (iii) For the second-order fully implicit and convex splitting schemes, for any time step size $δt > 0$, there exists an initial condition $u_0$ , with $|u_0| > 1$, such that the numerical solution converges to the wrong steady state solution. (iv) For $|u_0|$ ≤ 1, all second-order schemes studied in this paper converge to the correct steady state solution although severe numerical oscillations occur for most of them if the time step size is not sufficiently small. (v) An unconditionally energy-stable scheme (such as the modified Crank–Nicolson scheme) is not necessarily better than a conditionally energy-stable scheme (such as the Crank–Nicolson scheme). Finally, most, if not all, of the above conclusions are expected to be true for more general Allen–Cahn and other phase-field models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Significant DBSCAN+: Statistically Robust Density-based Clustering

Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes and varying densities. As a classical topic in data mining and learning, a myriad of techniques have been developed to detect clusters with both varying shapes and densities (e.g., density-based, hierarchical, spectral, or deep clustering methods). However, the vast majority of these techniques do not consider statistical rigor and are susceptible to detecting spurious clusters formed as a result of natural randomness. On the other hand, scan statistic approaches explicitly control the rate of spurious results, but they typically assume a single “hotspot” of over-density and many rely on further assumptions such as a tessellated input space. To unite the strengths of both lines of work, we propose a statistically robust formulation of a multi-scale DBSCAN, namely Significant DBSCAN+, to identify significant clusters that are density connected. As we will show, incorporation of statistical rigor is a powerful mechanism that allows the new Significant DBSCAN+ to outperform state-of-the-art clustering techniques in various scenarios. We also propose computational enhancements to speed-up the proposed approach. Experiment results show that Significant DBSCAN+ can simultaneously improve the success rate of true cluster detection (e.g., 10–20% increases in absolute F1 scores) and substantially reduce the rate of spurious results (e.g., from thousands/hundreds of spurious detections to none or just a few across 100 datasets), and the acceleration methods can improve the efficiency for both clustered and non-clustered data.

Computer Science↗
DOE OSTI2023

Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput

Undoubtedly, quantum computing offers valuable acceleration for solving intricate problems. One of the primary hurdles lies in executing large-scale quantum applications on backend machines. Qubit noise, among other factors, dramatically influences the execution process. Implementing effective scheduling techniques for quantum circuits is crucial for practical quantum computing and preventing excessive waiting times. The quantum realm is distinct from classical computing in terms of optimization, performance, utilization, and waiting periods. Consequently, the parameters and components of quantum circuit scheduling diverge from those of classical computing. This paper presents Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput, a straightforward yet effective scheduling framework and policy that enhances noise resilience, throughput, and the fidelity of quantum circuits. Drawing inspiration from classical methods, our scheduling approach incorporates additional constraints tailored for quantum logic. The outcome demonstrates a substantial improvement in fidelity and resource management, which is vital for real-world quantum applications.

Baheri, Betis↗