Search NASA⌕ Search

SEARCH · Search NASA

Results for “MULTIPLICATION FACTORS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mitigating coherent loss in superconducting circuits using molecular self-assembled monolayers

In planar superconducting circuits, decoherence due to materials imperfections, especially two-level-system (TLS) defects at different interfaces, is a primary hurdle for advancing quantum computing and sensing applications. Traditional methods for mitigating TLS loss, such as etching oxide layers at metal and substrate interfaces, have proven to be inadequate due to the persistent challenge of oxide regrowth. In this work, we introduce a novel approach that employs molecular self-assembled monolayers (SAMs) to chemically bind at different interfaces of superconducting circuits. This technique is specifically tested here on coplanar waveguide (CPW) resonators, in which this method not only impedes oxide regrowth after surface etching but can also tailors the dielectric properties at different resonators interfaces. The deployment of SAMs results in a consistent improvement in the measured quality factors across multiple resonators, surpassing those with only oxide-etched resonators. The efficiency of our approach is supported by microwave measurements of multiple devices conducted at millikelvin temperatures and correlated with detailed X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) characterizations of SAM-passivated resonators. The compatibility of SAMs materials with the established fabrication techniques offers a promising route to improve the performance of superconducting quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Revisiting the role of Zr doping in Ni-rich layered cathodes for lithium-ion batteries

We report the realization of high performance Ni-rich layered cathodes remains a challenge because of the multiple degradation factors that concurrently operate during battery cycling. In particular, depletion of oxygen charge and consequent lattice oxygen instability at deep charge state accelerate the subsequent chemomechanical degradation mechanisms. Among the proposed methodologies, doping has proven to be effective in enhancing the cathode cycle life by stabilizing the layered structure. Herein, we achieved the electrochemically stabilized Ni-rich LiNi 0.92 Co 0.04 Mn 0.04 O 2 through Zr doping, resulting in a 15% increase of the capacity retention after 100 cycles. In-depth investigations are conducted to unveil the effects of Zr doping on the layered cathode, and in particular, the critical role of Zr doping on the lattice oxygen stability is systematically studied. By combining state-of-the-art magnetometer characterization, X-ray analysis, and first-principles calculation, we reveal that Zr doping positively contributes the to lattice oxygen stability by alleviating the oxygen charge loss at deep charge, thereby improving the cathode electrochemical reversibility. Our findings provide an insight into the Zr doping mechanism and help to design the Ni-rich layered oxides for future applications.

25 ENERGY STORAGE↗
DOE OSTI2022

A Sobering Examination of the Feasibility of Aqueous Aluminum Batteries

Recent reports on aqueous aluminum (Al) batteries boast encouraging metrics including high energy density, nonflammability, and low raw material cost. However, the poorly understood solvation environment around the trivalent aluminum ions (Al3+) raises uncertainty regarding their feasibility. Furthermore, the corrosiveness of the acidic solutions and degree of hydration of aluminum trifluoromethanesulfonate (Al(OTf)3) salt is routinely mischaracterized. This study provides a rigorous examination of aqueous Al electrolytes, with the first compelling evidence for a dynamic octahedral solvation structure around Al3+ dominated by labile water and OH-, without Al-OTf contact ion pairs, at high concentrations. This solvation behavior and the concomitant electrostatic hydrolysis differs greatly from previously reported water-in-salt electrolytes, and occurs due to the high charge density of the Lewis acidic Al3+. Nuclear magnetic resonance spectroscopy and other physicochemical measurements quantitatively reveal how species activity evolves with concentration. The high proton activity observed in transport and electrochemical measurements constitutes a prohibitive barrier to the feasibility of rechargeable aluminum batteries with aqueous electrolyte.

Pastel, Glenn R.↗
DOE OSTI2024

Light-enhanced oxygen degradation of MAPbBr 3 single crystal

Organometal halide perovskites are promising materials for optoelectronic applications, whose commercial realization depends critically on their stability under multiple environmental factors. In this study, a methylammonium lead bromide (MAPbBr 3 ) single crystal was cleaved and exposed to simultaneous oxygen and light illumination under ultrahigh vacuum (UHV). The exposure process was monitored using X-ray photoelectron spectroscopy (XPS) with precise control of the exposure time and oxygen pressure. It was found that the combination of oxygen and light accelerated the degradation of MAPbBr 3 , which could not be viewed as a simple addition of that by oxygen-only and light-only exposures. The XPS spectra showed significant loss of carbon, bromine, and nitrogen at an oxygen exposure of 10 10 Langmuir with light illumination, approximately 17 times of the additive effects of oxygen-only and light-only exposures. It was also found that the photoluminescence (PL) emission was much weakened by oxygen and light co-exposure, while previous reports had shown that PL was substantially enhanced by oxygen-only exposure. Measurements using a scanning electron microscope (SEM) and focused ion beam (FIB) demonstrated that the crystal surface was much roughened by the co-exposure. Furthermore, Density functional theory (DFT) calculations revealed the formation of superoxide and oxygen induced gap state, suggesting the creation of oxygen radicals by light illumination as a possible microscopic driving force for enhanced degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Direct Measurement of ICRF-Enhanced Plasma Potentials on WEST Using Reciprocating Emissive Probes

An extensive documentation of ICRF-enhanced plasma potentials has been conducted over two experimental campaigns on the WEST tokamak using reciprocating emissive probes magnetically connected to two ICRF antennas. The collected data spans a wide range of antenna electrical settings (coupled power, toroidal phasing, left–right power balance) and plasma parameters (density at the antenna limiter above and below the lower hybrid resonance, plasma current, minority fraction). By scanning the edge safety factor across multiple probe plunges, the magnetic connection between the probe and the antenna varied, enabling the construction of a 2D map of the plasma and floating potentials around an active ICRF antenna. This dataset will be used to validate RF simulation tools equipped with the sheath boundary condition and used to predict RF rectified potentials and ICRF-induced impurity sputtering in future machines. This paper presents the diagnostic and some initial measurements, while the rest will be reported elsewhere.

Diab, Raymond [Massachusetts Inst. of Technology (↗
DOE OSTI2021

Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity

Significance Epidemics generally spread through a succession of waves that reflect factors on multiple timescales. Here, we develop a general approach bridging across these timescales and demonstrate how to incorporate population heterogeneity into a wide class of epidemiological models. We demonstrate that a fragile state of transient collective immunity emerges during early, high-paced stages of the epidemic, leading to suppression of individual epidemic waves. However, this state is not an indication of lasting herd immunity: Subsequent waves may emerge due to stochastic changes in individual social activity. Parameters of transient collective immunity are estimated using empirical data from the COVID-19 epidemic in several US locations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A theoretical index for understanding distinct land relative humidity trends in observations, reanalyses, and models

Land surface relative humidity (RH) is a key variable in the coupled land–atmosphere system that profoundly influences terrestrial hydroclimate and ecosystems. Yet historical changes in land RH are not well understood due to limited observations, biased reanalyses, and the lack of a framework for interpreting RH changes under multiple influencing factors. Here, we show that the spatiotemporal variability of land RH and its distinct historical trends among observations, reanalyses, and Earth system models are captured by a simple index based on the ratio of precipitation (P) to a modified potential evapotranspiration formulated independently of RH (PET°). The index provides a physical calibration of biased land RH in reanalyses and a quantitative framework for interpreting land RH changes. Over 1973–2024, land RH has decreased substantially, owing to the intrinsic rise in PET° with temperature and little increase in land precipitation. Reanalyses overestimate the observed RH decrease, consistent with exaggerated surface warming and precipitation decline. The index captures this coherent bias and enables a calibration using observed precipitation and temperature. Models simulate a wide range of land RH trends, but nearly all runs underrepresent the historical drying. The index captures the model spread and discrepancy and attributes them to contributions of precipitation and PET°. Weaker land RH decreases in models arise mainly from weaker subtropical precipitation declines, linked to muted intensification of subtropical highs and biased subtropical climatology. The model–observation discrepancy is unlikely explained by internal variability, implying model underestimation of forced RH decrease and a drier land future than current projections.

Earth system models↗
DOE OSTI2020

Low-energy magnons in the chiral ferrimagnet Cu 2 OSeO 3 : A coarse-grained approach

We report a comprehensive neutron scattering study of low energy magnetic excitations in the breathing pyrochlore helimagnetic Cu2OSeO3. Fully documenting the four lowest energy magnetic modes that leave the ferrimagnetic configuration of the “strong tetrahedra” intact (| ℏ ω| < 13 meV), we find gapless quadratic dispersion at the Γ point for energies above 0.2 meV, two doublets separated by 1.6(2) meV at the R point, and a bounded continuum at the X point. Our constrained rigid spin cluster model relates these features to Dzyaloshinskii-Moriya (DM) interactions and the incommensurate helical ground state. Combining conventional spin wave theory with a spin cluster form factor accurately reproduces the measured equal time structure factor through multiple Brillouin zones. An effective spin Hamiltonian describing complex anisotropic intercluster interactions is obtained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Combined Effects of Electric Vehicle Charging and Rooftop Solar Integration on Voltage Imbalance in Residential Distribution Networks

Residential electric vehicle (EV) chargers, as single phase loads, contribute to unbalanced voltage drops across phases, while rooftop solar systems, as single phase generators, can exacerbate voltage imbalance by causing unbalanced voltage increases. This paper investigates combined effects of residential EV charging and rooftop solar generation on voltage imbalance in residential distribution grids. The study examines these simultaneous impacts using the IEEE 8500-node test system, enhanced with a secondary network to realistically model the EV chargers and rooftop solar integration. To account for the variability and uncertainty in the EV charging loads and solar generation, a Monte Carlo approach is employed to capture and quantify the simultaneous impact of the EV charging and rooftop solar integration. In this approach, multiple influencing factors are considered, including state-of-charge (SOC), maximum charging power levels, and geographic distribution of chargers. The results provide practical insights for utilities and stakeholders, offering expectations for planning and operating strategies that effectively manage the increasing adoption of EVs and solar power while maintaining grid reliability.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2024

Historical Power Outages of the United States and the Social Vulnerability Index

Several works have been documented in the literature to study the societal effect of power outages and to analyze their correlation with the Social Vulnerability Index (SVI). Because the SVI is calculated based on the summed rank of multiple vulnerability factors for environmental hazards, it can include factors irrelevant to power outages caused by extreme events. This work performs a detailed correlation analysis for social vulnerability and power outages by considering different SVI themes (e.g., socioeconomic status, household composition, racial and ethnic minority status, and housing and transportation) and power outages with and without a threshold for extreme weather events. Although there is some relation between specific themes and aspects of power outages and the SVI in the results, there is no strong distinction between power outage durations and low vs. high SVI values. These results point to the need for further research that grounds the specific factors and methods used to develop SVI and related indices to energy services and power systems disruptions.

Bhusal, Narayan↗
DOE OSTI2022

Root responses to elevated CO 2 , warming and irrigation in a semi-arid grassland: Integrating biomass, length and life span in a 5-year field experiment

Plant roots mediate the impacts of environmental change on ecosystems, yet knowledge of root responses to environmental change is limited because few experiments evaluate multiple environmental factors and their interactions. Inferences about root functions are also limited because root length dynamics are rarely measured. Using a 5-year experiment in a mixed-grass prairie, we report the responses of root biomass, length and life span to elevated carbon dioxide (CO 2 ), warming, elevated CO 2 and warming combined, and irrigation. Root biomass was quantified using soil cores and root length dynamics were assessed using minirhizotrons. By comparing root dynamics with published results for soil resources and above-ground productivity, we provide mechanistic insights into how climate change might impact grassland ecosystems. In the upper soil layer, 0–15 cm depth, both irrigation and elevated CO 2 alone increased total root length by twofold, but irrigation decreased root biomass and elevated CO 2 had only small positive effects on root biomass. The large positive effects of irrigation and elevated CO 2 alone on total root length were due to increases in both root length production and root life span. The increased total root length and life span under irrigation and elevated CO 2 coincided with apparent shifts from water limitation of plant growth to nitrogen limitation. Warming alone had minimal effects on root biomass, length and life span in this shallow soil layer. Warming and elevated CO 2 combined increased root biomass and total root length by c. 25%, but total root length in this treatment was lower than expected if the effects of CO 2 and warming alone were additive. Treatment effects on total root length and root life span varied with soil depth and root diameter. Synthesis. Sub-additive effects of CO 2 and warming suggest studies of elevated CO 2 alone might overestimate the future capacity of grassland root systems to acquire resources. In this mixed-grass prairie, elevated CO 2 with warming stimulated total root length and root life span in deeper soils, likely enhancing plant access to more stable pools of growth-limiting resources, including water and phosphorus. Therefore, these root responses help explain previous observations of higher, and more stable, above-ground productivity in these projected climate conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗
DOE OSTI2020

Fundamental Behavior of ENSO Phase Locking

El Niño–Southern Oscillation (ENSO) events tend to peak at the end of the calendar year, a phenomenon called ENSO phase locking. This phase locking is a fundamental ENSO property that is determined by its basic dynamics. The conceptual ENSO recharge oscillator (RO) model is adopted to examine the ENSO phase-locking behavior in terms of its peak time, strength of phase locking, and asymmetry between El Niño and La Niña events. The RO model reproduces the main phase-locking characteristics found in observations, and the results show that the phase locking of ENSO is mainly dominated by the seasonal modulation of ENSO growth/decay rate. In addition, the linear/nonlinear mechanism of ENSO phase preference/phase locking is investigated using RO model. The difference between the nonlinear phase-locking mechanism and linear phase-preference mechanism is largely smoothed out in the presence of noise forcing. Further, the impact on ENSO phase locking from annual cycle modulation of the growth/decay rate, stochastic forcing, nonlinearity, and linear frequency are examined in the RO model. The preferred month of ENSO peak time depends critically on the phase and strength of the seasonal modulation of the ENSO growth/decay rate. Furthermore, the strength of phase locking is mainly controlled by the linear growth/decay rate, the amplitude of seasonal modulation of growth/decay rate, the amplitude of noise, the SST-dependent factor of multiplicative noise, and the linear frequency. The asymmetry of the sharpness of ENSO phase locking is induced by the asymmetric effect of state-dependent noise forcing in El Niño and La Niña events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Recipes for a Successful Exit for Clean- and Hard-tech Startups

This study demonstrates the combinations of multiple causal factors that formulate a startup’s strategy to successfully “exit”, namely “recipes for a successful exit,” in the clean- and hard-tech sector. We identify seven key causal factors (i.e., causal conditions) that impact startup success, including commercial readiness, investor interactions, favorable industry, non-financial support, straightforward development path, experienced team, and visibility to investors. We also investigate the combinations of selective causal conditions that can provide further synergetic impact. We conduct the fuzzy-set qualitative comparative analysis (fsQCA) on seven US clean and hard-tech startups that exited between 2005 and 2016. The successful companies all demonstrate distinctive characteristics based on three general categories (1) robust ecosystem; (2) heavy-lifting team; or (3) external opportunity. Across these three categories, commercial readiness and strong investor interactions are necessary conditions for all exit cases. But there are important differences that drive success in each category, such as the interaction with non-financial support (in the robust ecosystem case), experienced team (in the heavy-lifting team case), and favorable industry (in the external opportunity case). Furthermore, our findings are meant to support entrepreneurs in reaching an exit by optimizing the given internal and external circumstances, and policymakers to build a robust ecosystem that can increase the success rate of the clean- and hardtech development.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Randomized Algorithms for Linear Solvers

Recently, randomized algorithms in numerical linear algebra, specifically those centered around random sketching, have gained traction in primarily theoretical research due to their potential to significantly reduce problem dimensionality at the cost of an O(1) multiplicative distortion factor. It has been assumed that this sketching can be done efficiently, but thorough investigation into how precisely to do it has been neglected. Moreover, the theory-based community has argued for sketching’s ability to reduce computational cost via complexity analysis, but has not researched how it affects the stability of the algorithms. At Sandia, efficient linear solvers that scale well on modern HPC architectures while maintaining stability are imperative for practical applications. In this LDRD, we developed a random sketching strategy that is substantially faster than existing ones, and demonstrate its superior performance in practice on a NVIDIA H100 GPU. Moreover, we show how this can be used to significantly outperform existing linear least squares solvers while improving the solver’s stability as well. Additionally, we demonstrate how this sketching strategy can be used to make a fast, stable QR factorization that can subsequently be used in s-step and block Krylov solvers. Finally, we incorporate a sketching-based block orthogonalization scheme into s-step GMRES, which is stable and faster than existing approaches on the Perlmutter supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Experimental Warming Changes Phenology and Shortens Growing Season of the Dominant Invasive Plant Bromus tectorum (Cheatgrass)

Bromus tectorum (cheatgrass) has successfully invaded and established throughout the western United States. Bromus tectorum grows early in the season and this early growth allows B. tectorum to outcompete native species, which has led to dramatic shifts in ecosystem function and plant community composition after B. tectorum invades. If the phenology of native species is unable to track changing climate as effectively as B. tectorum’s phenology then climate change may facilitate further invasion. To better understand how B. tectorum phenology will respond to future climate, we tracked the timing of B. tectorum germination, flowering, and senescence over a decade in three in situ climate manipulation experiments with treatments that increased temperatures (2°C and 4°C above ambient), altered precipitation regimes, or applied a combination of each. Linear mixed-effects models were used to analyze treatment effects on the timing of germination, flowering, senescence, and on the length of the vegetative growing season (time from germination to flowering) in each experiment. Altered precipitation treatments were only applied in early years of the study and neither precipitation treatments nor the treatments’ legacies significantly affected B. tectorum phenology. The timing of germination did not significantly vary between any warming treatments and their respective ambient plots. However, plots that were warmed had advances in the timing of B. tectorum flowering and senescence, as well as shorter vegetative growing seasons. The phenological advances caused by warming increased with increasing degrees of experimental warming. The greatest differences between warmed and ambient plots were seen in the length of the vegetative growing season, which was shortened by approximately 12 and 7 days in the +4°C and +2°C warming levels, respectively. The effects of experimental warming were small compared to the effects of interannual climate variation, suggesting that interactive controls and the timing of multiple climatic factors are important in determining B. tectorum phenology. Taken together, these results help elucidate how B. tectorum phenology may respond to future climate, increasing our predictive capacity for estimating when to time B. tectorum control efforts and how to more effectively manage this exotic annual grass.

54 ENVIRONMENTAL SCIENCES↗