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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Heterogeneous estimations of non-pharmaceutical mitigation behavior during the COVID-19 pandemic

The COVID-19 pandemic highlighted the importance of human behavior in mitigating the spread of disease. Nonetheless, human behavior is often overlooked in models of disease spread, particularly by underutilizing real-world data. We address this by estimating probabilities that individuals engage in behaviors that influence SARS-CoV-2 transmission risk during the COVID-19 pandemic, between September 2020 and June 2022. These behaviors include wearing a mask, using public transportation, spending time with others, avoiding contact with others, and going to work. Our estimates account for the age and sex of individuals and are generated for every county in the United States. We utilized multiple open-source datasets and United States Census data to produce these estimates. Multiple datasets were used for validation, showing our estimates demonstrated comparable accuracy and robustness. Our estimates aid in understanding human behavior dynamics during the COVID-19 pandemic and could be used to inform monthly or longer-term behavior in simulations of COVID-19. Moreover, the methods presented can be applied to other behaviors and features for future simulations of infectious disease.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

First on-line detection of radioactive fission isotopes produced by laser-accelerated protons

Abstract The on-going developments in laser acceleration of protons and light ions, as well as the production of strong bursts of neutrons and multi- $$\hbox {MeV}$$ MeV photons by secondary processes now provide a basis for novel high-flux nuclear physics experiments. While the maximum energy of protons resulting from Target Normal Sheath Acceleration is presently still limited to around $$100 \, \hbox {MeV}$$ 100 MeV , the generated proton peak flux within the short laser-accelerated bunches can already today exceed the values achievable at the most advanced conventional accelerators by orders of magnitude. This paper consists of two parts covering the scientific motivation and relevance of such experiments and a first proof-of-principle demonstration. In the presented experiment pulses of $$200 \, \hbox {J}$$ 200 J at $$\approx \, 500 \, \hbox {fs}$$ ≈ 500 fs duration from the PHELIX laser produced more than $$10^{12}$$ 10 12 protons with energies above $$15 \, \hbox {MeV}$$ 15 MeV in a bunch of sub-nanosecond duration. They were used to induce fission in foil targets made of natural uranium. To make use of the nonpareil flux, these targets have to be very close to the laser acceleration source, since the particle density within the bunch is strongly affected by Coulomb explosion and the velocity differences between ions of different energy. The main challenge for nuclear detection with high-purity germanium detectors is given by the strong electromagnetic pulse caused by the laser-matter interaction close to the laser acceleration source. This was mitigated by utilizing fast transport of the fission products by a gas flow to a carbon filter, where the $$\upgamma$$ γ -rays were registered. The identified nuclides include those that have half-lives down to $$39 \, \hbox {s}$$ 39 s . These results demonstrate the capability to produce, extract, and detect short-lived reaction products under the demanding experimental condition imposed by the high-power laser interaction. The approach promotes research towards relevant nuclear astrophysical studies at conditions currently only accessible at nuclear high energy density laser facilities.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Enabling deeper learning on big data for materials informatics applications

Abstract The application of machine learning (ML) techniques in materials science has attracted significant attention in recent years, due to their impressive ability to efficiently extract data-driven linkages from various input materials representations to their output properties. While the application of traditional ML techniques has become quite ubiquitous, there have been limited applications of more advanced deep learning (DL) techniques, primarily because big materials datasets are relatively rare. Given the demonstrated potential and advantages of DL and the increasing availability of big materials datasets, it is attractive to go for deeper neural networks in a bid to boost model performance, but in reality, it leads to performance degradation due to the vanishing gradient problem. In this paper, we address the question of how to enable deeper learning for cases where big materials data is available. Here, we present a general deep learning framework based on Individual Residual learning (IRNet) composed of very deep neural networks that can work with any vector-based materials representation as input to build accurate property prediction models. We find that the proposed IRNet models can not only successfully alleviate the vanishing gradient problem and enable deeper learning, but also lead to significantly (up to 47%) better model accuracy as compared to plain deep neural networks and traditional ML techniques for a given input materials representation in the presence of big data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comparative transcriptome analysis of cells from different areas reveals ROS responsive mechanism at sclerotial initiation stage in Morchella importuna

Morels are some of the most highly prized edible and medicinal mushrooms, with great economic and scientific value. Outdoor cultivation has been achieved and expanded on a large scale in China in recent years. Sclerotial formation is one of the most important phases during the morel life cycle, and previous reports indicated that reactive oxygen species (ROS) play an important role. However, ROS response mechanisms at sclerotial initiation (SI) stage are poorly understood. In this study, comparative transcriptome analyses were performed with sclerotial and hyphal cells at different areas in the same plate at SI stage. Gene expression was significantly different at SI stage between sclerotial formation and mycelia growth areas. GO and KEGG analyses indicated more vigorous metabolic characteristics in the hyphae area, while transcription process, DNA repair, and protein processing were enriched in sclerotial cells. Gene expression related to H 2 O 2 production was high in the hyphae area, while expression of H 2 O 2 -scavenging genes was high in sclerotial cells, leading to a higher H 2 O 2 concentration in the hyphal region than in the sclerotium. Minor differences were observed in gene expression of H 2 O 2 -induced signaling pathway in sclerotial and hyphal cells; however, expression levels of the target genes of transcription factor MSN2, important in the H 2 O 2 -induced signaling pathways, were significantly different. MSN2 enhanced stress response regulation in sclerotia by regulating these target genes. Small molecular HSPs were also found upregulated in sclerotial cells. This study indicated that sclerotial cells are more resistant to ROS stress than hyphal cells through transcriptional regulation of related genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Supercapacitance and superinductance of TiN and NbTiN films in the vicinity of superconductor-to-insulator transition

We investigate the low-temperature complex impedance of disordered insulating thin TiN and NbTiN films in the frequency region 400 Hz–1 MHz in close proximity to the superconductor–insulator transition (SIT). The frequency, temperature, and magnetic field dependencies of the real and imaginary parts of the impedance indicate that in full accord with the theoretical predictions and earlier observations, the films acquire self-induced electronic granularity and become effectively random arrays of superconducting granules coupled via Josephson links. Accordingly, the inductive component of the response is due to superconducting droplets, while the capacitive component results from the effective Josephson junctions capacitances. The impedance crosses over from capacitive to inductive behavior as films go across the transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Crystal structure of the CoV-Y domain of SARS-CoV-2 nonstructural protein 3

Abstract Replication of the coronavirus genome starts with the formation of viral RNA-containing double-membrane vesicles (DMV) following viral entry into the host cell. The multi-domain nonstructural protein 3 (nsp3) is the largest protein encoded by the known coronavirus genome and serves as a central component of the viral replication and transcription machinery. Previous studies demonstrated that the highly-conserved C-terminal region of nsp3 is essential for subcellular membrane rearrangement, yet the underlying mechanisms remain elusive. Here we report the crystal structure of the CoV-Y domain, the most C-terminal domain of the SARS-CoV-2 nsp3, at 2.4 Å-resolution. CoV-Y adopts a previously uncharacterized V-shaped fold featuring three distinct subdomains. Sequence alignment and structure prediction suggest that this fold is likely shared by the CoV-Y domains from closely related nsp3 homologs. NMR-based fragment screening combined with molecular docking identifies surface cavities in CoV-Y for interaction with potential ligands and other nsps. These studies provide the first structural view on a complete nsp3 CoV-Y domain, and the molecular framework for understanding the architecture, assembly and function of the nsp3 C-terminal domains in coronavirus replication. Our work illuminates nsp3 as a potential target for therapeutic interventions to aid in the on-going battle against the COVID-19 pandemic and diseases caused by other coronaviruses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Benefits of symbiotic ectomycorrhizal fungi to plant water relations depend on plant genotype in pinyon pine

Rhizosphere microbes, such as root-associated fungi, can improve plant access to soil resources, affecting plant health, productivity, and stress tolerance. While mycorrhizal associations are ubiquitous, plant–microbe interactions can be species specific. Here we show that the specificity of the effects of microbial symbionts on plant function can go beyond species level: colonization of roots by ectomycorrhizal fungi (EMF) of the genus Geopora has opposite effects on water uptake, and stomatal control of desiccation in drought tolerant and intolerant genotypes of pinyon pine (Pinus edulis Engelm.). These results demonstrate, for the first time, that microorganisms can have significant and opposite effects on important plant functional traits like stomatal control of desiccation that are associated with differential mortality and growth in nature. They also highlight that appropriate pairing of plant genotypes and microbial associates will be important for mitigating climate change impacts on vegetation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Observation of momentum-dependent charge density wave gap in a layered antiferromagnet ${\textrm{Gd}}{\textrm{Te}}_{3}$

Charge density wave (CDW) ordering has been an important topic of study for a long time owing to its connection with other exotic phases such as superconductivity and magnetism. The RTe 3 (R = rare-earth elements) family of materials provides a fertile ground to study the dynamics of CDW in van der Waals layered materials, and the presence of magnetism in these materials allows to explore the interplay among CDW and long range magnetic ordering. Here, we have carried out a high-resolution angle-resolved photoemission spectroscopy (ARPES) study of a CDW material GdTe 3 , which is antiferromagnetic below ~ 12 K, along with thermodynamic, electrical transport, magnetic, and Raman measurements. Our ARPES data show a two-fold symmetric Fermi surface with both gapped and ungapped regions indicative of the partial nesting. The gap is momentum dependent, maximum along $\overline{Γ}$ - $\overline{Z}$ and gradually decreases going towards $\overline{Γ}$ - $\overline{Z}$. Our study provides a platform to study the dynamics of CDW and its interaction with other physical orders in two- and three dimensions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Microbial inoculum effects on the rumen epithelial transcriptome and rumen epimural metatranscriptome in calves

Manipulation of the rumen microbial ecosystem in early life may affect ruminal fermentation and enhance the productive performance of dairy cows. The objective of this experiment was to evaluate the effects of dosing three different types of microbial inoculum on the rumen epithelium tissue (RE) transcriptome and the rumen epimural metatranscriptome (REM) in dairy calves. For this objective, 15 Holstein bull calves were enrolled in the study at birth and assigned to three different intraruminal inoculum treatments dosed orally once weekly from three to six weeks of age. The inoculum treatments were prepared from rumen contents collected from rumen fistulated lactating cows and were either autoclaved (control; ARF), processed by differential centrifugation to create the bacterial-enriched inoculum (BE), or through gravimetric separation to create the protozoal-enriched inoculum (PE). Calves were fed 2.5 L/d pasteurized waste milk 3x/d from 0 to 7 weeks of age and texturized starter until euthanasia at 9 weeks of age, when the RE tissues were collected for transcriptome and microbial metatranscriptome analyses, from four randomly selected calves from each treatment. The different types of inoculum altered the RE transcriptome and REM. Compared to ARF, 9 genes were upregulated in the RE of BE and 92 in PE, whereas between BE and PE there were 13 genes upregulated in BE and 114 in PE. Gene ontology analysis identified enriched GO terms in biological process category between PE and ARF, with no enrichment between BE and ARF. The RE functional signature showed different KEGG pathways related to BE and ARF, and no specific KEGG pathway for PE. We observed a lower alpha diversity index for RE microbiome in ARF (observed genera and Chao1 (p < 0.05)). Five microbial genera showed a significant correlation with the changes in host gene expression: Roseburia (25 genes), Entamoeba (two genes); Anaerosinus, Lachnospira, and Succiniclasticum were each related to one gene. sPLS-DA analysis showed that RE microbial communities differ among the treatments, although the taxonomic and functional microbial profiles show different distributions. Co-expression Differential Network Analysis indicated that both BE and PE had an impact on the abundance of KEGG modules related to acyl-CoA synthesis, type VI secretion, and methanogenesis, while PE had a significant impact on KEGGs related to ectoine biosynthesis and D-xylose transport. Our study indicated that artificial dosing with different microbial inocula in early life alters not only the RE transcriptome, but also affects the REM and its functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Relative importance of nonlinear electron-phonon coupling and vertex corrections in the Holstein model

Determining the range of validity of Migdal’s approximation for electron-phonon (e-ph) coupled systems is a long-standing problem. Many attempts to answer this question employ the Holstein Hamiltonian, where the electron density couples linearly to local lattice displacements. When these displacements are large, however, nonlinear corrections to the interaction must also be included, which can significantly alter the physical picture obtained from this model. Using determinant quantum Monte Carlo and the self-consistent Migdal approximation, we compared superconducting and charge-density-wave correlations in the Holstein model with and without second-order nonlinear interactions. We find a disagreement between the two cases, even for relatively small values of the e-ph coupling strength, and, importantly, that this can occur in the same parameter regions where Migdal’s approximation holds. Our results demonstrate that questions regarding the validity of Migdal’s approximation go hand in hand with questions of the validity of a linear e-ph interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

An economic perspective of the circular bioeconomy in the food and agricultural sector

Transforming the agri-food system from a “take-make-waste”, or linear production system, to a circular bioeconomy that reduces, recycles, recovers, reuses, and regenerates wastes and transitions from fossil to biobased fuels and products is being hailed as critical for meeting a growing population’s food and fuel needs in environmentally sustainable ways. While a transformation towards a circular bioeconomy is an appealing strategy to achieve multiple environmental goals, we argue that this strategy needs to go beyond a techno-centric focus and adopt an economic value-based lens to balance the desire for circularity with its costs, benefits, and distributional effects on society. This perspective analyzes the mechanisms that sustain the existing linear economy and proposes a novel social cost-benefit framework to determine the optimal level and path to circularity. We present five critical pathways to achieve a sustainable circular bioeconomy in a market economy consisting of decentralized decision-makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tunable, Bacterio-Instructive Scaffolds Made from Functional Graphenic Materials

The balance of bacterial populations in the human body is critical for human health. Researchers have aimed to control bacterial populations using antibiotic substrates. However, antibiotic materials that non-selectively kill bacteria can compromise health by eliminating beneficial bacteria, which leaves the body vulnerable to colonization by harmful pathogens. Due to their chemical tunablity and unique surface properties, graphene oxide (GO)-based materials – termed “functional graphenic materials” (FGMs) – have been previously designed to be antibacterial but have the capacity to actively adhere and instruct probiotics to maintain human health. Numerous studies have demonstrated that negatively and positively charged surfaces influence bacterial adhesion through electrostatic interactions with the negatively charged bacterial surface. We found that tuning the surface charge of FGMs provides an avenue to control bacterial attachment without compromising vitality. Using E. coli as a model organism for gram-negative bacteria, we demonstrate that negatively charged Claisen graphene (CG), a reduced and carboxylated FGM, is bacterio-repellent through electrostatic repulsion with the bacterial surface. Though positively charged poly-L-lysine (PLL) is antibacterial when free in solution by inserting into the bacterial cell wall, here, we found that covalent conjugation of PLL to CG (giving PLLn-G) masks the antimicrobial activity of PLL by restricting polypeptide mobility. This allows the immobilized positive charge of the PLLn-Gs to be leveraged for E. coli adhesion through electrostatic attraction. We identified the magnitude of positive charge of the PLLn-G conjugates, which is modulated by the length of the PLL peptide, as an important parameter to tune the balance between the opposing forces of bacterial adhesion and proliferation. We also tested adhesion of gram-positive B. subtilis to these FGMs and found that the effect of FGM charge is less pronounced. B. subtilis adheres nondiscriminatory to all FGMs, regardless of charge, but adhesion is scarce and localized. Overall, this work demonstrates that FGMs can be tuned to selectively control bacterial response, paving the way for future development of FGM-based biomaterials as bacterio-instructive scaffolds through careful design of FGM surface chemistry.

Eckhart, Karoline E.↗
DOE OSTI2020

Structural, electronic, and magnetic properties of Ni nanoparticles supported on the TiC(001) surface

Metals supported on transition metal carbides are known to exhibit good catalytic activity and selectivity, which is interpreted in terms of electron polarization induced by the support. In the present work we go one step further and investigate the effect that a titanium carbide (TiC) support has on the structural, electronic, and magnetic properties of a series of Ni nanoparticles of increasing size exhibiting a two- or three-dimensional morphology. Furthermore, the obtained results show that three-dimensional nanoparticles are more stable and easier to form than their homologous two-dimensional counterparts. Also, comparison to previous results indicates that, when used as the support, transition metal carbides have a marked different chemical activity with respect to oxides. The analysis of the magnetic moments of the supported nanoparticles evidences a considerable quenching of the magnetic moment that affects mainly the Ni atoms in close contact with the TiC substrate indicating that these atoms are likely to be responsible for the catalytic activity reported for these systems. Overall, the analysis of the electronic structure reveals the existence of chemical interactions between the Ni nanoparticles and the TiC support, even if the net charge transfer between both systems is negligible.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modulation of CO 2 adsorption in novel pillar-layered MOFs based on carboxylate–pyrazole flexible linker

Metal–organic frameworks (MOFs) have attracted significant attention as sorbents due to their high surface area, tunable pore volume and pore size, coordinatively unsaturated metal sites, and ability to install desired functional groups by post-synthetic modification. Herein, we report three new MOFs with pillar–paddlewheel structures that have been synthesized solvothermally from the mixture of the carboxylate–pyrazole flexible linker (H 2 L), 4,4-bipyridine (BPY)/triethylenediamine (DABCO), and Zn(II)/Cu(II) ions. The MOFs obtained, namely [Zn II (L)BPY], [Cu II (L)BPY], and [Cu II (L)DABCO], exhibit two-fold interpenetration and dinuclear paddle–wheel nodes. The Zn(II)/Cu(II) cations are coordinated by two equatorial L linkers that result in two-dimensional sheets which in turn are pillared by BPY or DABCO in the perpendicular direction to obtain a neutral three-dimensional framework that shows one-dimensional square channels. The three pillar-layered MOFs were characterized as microporous materials showing high crystalline stability after activation at 120 °C and CO 2 adsorption. All MOFs contain uncoordinated Lewis basic pyrazole nitrogen atoms in the framework which have an affinity toward CO 2 and hence could potentially serve as CO 2 adsorption material. The CO 2 uptake capacity was initially enhanced by replacing Zn with Cu and then replacing the pillar, going from BPY to DABCO. Overall, all the MOFs exhibit low isosteric heat (Q st ) of adsorption which signifies an advantage due to the energy required for the adsorption and regeneration processes.

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

Computational discovery of promising new n-type dopable ABX Zintl thermoelectric materials

Computational prediction of good thermoelectric (TE) performance in several n-type doped Zintl phases, combined with successful experimental realization, has sparked interest in discovering new n-type dopable members of this family of materials. However, most known Zintls are typically only p-type dopable; prior successes in finding n-type Zintl phases have been largely serendipitous. Here in this paper, we go beyond previously synthesized Zintl phases and perform chemical substitutions in known n-type dopable ABX Zintl phases to discover new ones. We use first-principles calculations to predict their stability, potential for TE performance as well as their n-type dopability. Using this approach, we find 17 new ABX Zintl phases in the KSnSb structure type that are predicted to be stable. Several of these newly predicted phases (KSnBi, RbSnBi, NaGeP) are found to exhibit promising n-type TE performance and are n-type dopable. We propose these compounds for further experimental studies, especially KSnBi and RbSnBi, which are both predicted to be good TE materials with high electron concentrations due to self-doping by native defects, when grown under alkali-rich conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Safety issues of defective lithium-ion batteries: identification and risk evaluation

Lithium-ion batteries inevitably suffer minor damage or defects caused by external mechanical abusive loading, e.g. , penetration, deformation, and scratch without triggering a hard/major short circuit. The replacement of cells becomes a dilemma if the safety risk of the defective batteries remains unknown. Herein, by introducing a representative defect form, i.e. , screw indentation, we demonstrate the safety characteristics of defective batteries. We prove that defective batteries have a significantly increased thermal risk and deteriorated mechanical integrity, but can go undetected due to prompt voltage recovery and insignificant local temperature increase. We discover that the voltage curve within the first few cycles contains sufficient information to identify defective batteries from otherwise good ones and propose methodologies to monitor the cells. Capacity loss and current leakage are two characteristics that can be estimated using the voltage curve. According to the defect size and position, the capacity loss could be 1 to 10 2 mA h and the leakage current could be 5–50 mA. Results remove the barriers for defective battery safety risk evaluation, enabling identification, monitoring, and early warning of minor damaged batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Surface characterization and methane activation on SnO x /Cu 2 O/Cu(111) inverse oxide/metal catalysts

To activate methane at low or medium temperatures is a difficult task and a pre-requisite for the conversion of this light alkane into high value chemicals. In this work, we report the preparation and characterizations of novel SnO x /Cu 2 O/Cu(111) interfaces that enable low-temperature methane activation. Scanning tunneling microscopy identified small, well-dispersed SnO x nanoclusters on the Cu 2 O/Cu(111) substrate with an average size of 8 Å, and such morphology was sustained up to 450 K in UHV annealing. Ambient pressure X-ray photoelectron spectroscopy showed that hydrocarbon species (CH x groups), the product of methane activation, were formed on SnO x /Cu 2 O/Cu(111) at a temperature as low as 300 K. An essential role of the SnO x –Cu 2 O interface was evinced by the SnO x coverage dependence. Systems with a small amount of tin oxide, 0.1–0.2 ML coverage, produced the highest concentration of adsorbed CH x groups. Calculations based on density functional theory showed a drastic reduction in the activation barrier for C–H bond cleavage when going from Cu 2 O/Cu(111) to SnO x /Cu 2 O/Cu(111). On the supported SnO x , the dissociation of methane was highly exothermic (ΔE ~ –35 kcal mol –1 ) and the calculated barrier for activation (~20 kcal mol –1 ) could be overcome at 300–500 K, target temperatures for the conversion of methane to high value chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enhanced descriptor identification and mechanism understanding for catalytic activity using a data-driven framework: revealing the importance of interactions between elementary steps

We report accurate identification of descriptors for catalytic activities has long been essential to the in-depth understanding of catalysis and recently to set the basis for catalyst screening. However, commonly used methods suffer from low accuracy in predictability. This study reports an enhanced approach to accurately identify the descriptors from a kinetic dataset using a machine learning (ML) surrogate model. CO hydrogenation to methanol over Cu-based catalysts was taken as a case study. Our model captures not only the contribution from individual elementary steps but also the interaction between relevant steps within a reaction network, which was found to be essential for high accuracy. As a result, six effective descriptors are identified, which are accurate enough to ensure the trained gradient boosted regression (GBR) model for good prediction of the methanol turnover frequency (TOF) over metal (M)-doped Cu(111) model surfaces (M = Au, Cu, Pd, Pt, Ni). More importantly, going beyond the purely mathematical ML model, the catalytic role of each identified descriptor can be revealed by using model-agnostic interpretation tools, which enhances the insight into the promoting effect of alloying. The trained GBR model outperforms the conventional derivative-based methods in terms of both the predictability and the mechanism understanding. It opens alternative possibilities toward accurate descriptor-based rational catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗