SEARCH · Search NASA

Results for “difference”

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.

SourceResearch connectionFrom yearThrough year

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

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. Here, this work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron–sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks.

09 BIOMASS FUELS↗

DOE OSTI2024

Analysis and Comparison of Different Metrics of DC-DC Converters to Determine Fuel Cell Stack Architectures in Heavy Duty Fuel Cell Vehicle Applications

This paper presents a comparative study of the DC-DC converters used in heavy-duty fuel cell electric vehicles for different input fuel cell stack configurations and voltages in terms of various important metrics including efficiency, cost, weight and power density. Contrary to conventional use of an interleaved boost topology, the analysis presented in this paper demonstrates that improved converter metrics can be achieved for an interleaved buck topology that uses a different input fuel cell stack. An insight to the optimal choice of number of interleaved phases for each metric is also presented. Results presented in the tables and plots convey the findings.

Mukherjee, Subho↗

DOE OSTI2025

Quantum Approximate Optimization Algorithm on Different Qubit Systems

Solving optimization problems is critical across many research domains, but the high dimensionality of parameter spaces often poses significant challenges. The Quantum Approximate Optimization Algorithm (QAOA) has emerged as a promising approach for accelerating optimization in the Noisy Intermediate-Scale Quantum (NISQ) era by leveraging both classical and quantum computational resources. However, its performance can vary depending on the underlying quantum hardware architecture. In this work, we evaluate the performance of QAOA on different quantum hardware platforms, specifically, superconducting transmon qubits and trapped-ion qubits, targetting real-world optimization problems formulated as fully connected Quadratic Unconstrained Binary Optimization (QUBO) instances. We evaluate both the solution quality and time-to-solution using dense QUBO matrices. Furthermore, we show that large-scale problems, such as a 100-bit QUBO instance, can be effectively tackled by integrating quantum computing with high-performance computing (HPC) resources. This study provides practical insights into the strengths and limitations of different qubit technologies and advances the application of quantum computing in solving real-world optimization problems.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗

DOE OSTI2024

Effect of different grain boundary diffusion alloys on magnetic properties of Dy-free sintered NdFeB magnet

Dy-free sintered magnets were fabricated by blending Neo powder with different grain boundary diffusion alloy powders. Cu, CeAl and CeAlCu have a negative effect on H cj of magnets, while PrAlCu and AlCuGa have a positive effect. The PrAlCu-added magnet achieves the best magnetic properties among all magnets with the additions of different diffusion alloys. With increasing PrAlCu from 0-10 wt.%, H cj of the magnets gradually increases from the original 14.5 kOe to 19.2 kOe. The magnet with 7.5 wt.% PrAlCu obtains a H cj of 18 kOe and (BH) max of 39.1 MGOe. It is found that Pr and Cu in PrAlCu alloy is mainly distributed at grain boundary and triple junctions, leading to a reduced coupling among grains, thus an enhanced H cj . Here, the grain boundary engineering by adding an appropriate alloy is an effective method to improve H cj of Dy-free NdFeB magnets.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Photosynthetic responses of switchgrass to light and CO 2 under different precipitation treatments

Switchgrass ( Panicum virgatum L .) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO 2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO 2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO 2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO 2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO 2 response curves. Precipitation change did not influence the maximum net photosynthetic rate ( P max ) but influenced other model parameters including quantum yield ( α ), convexity ( θ ), dark respiration ( Rd ), light compensation point ( LCP ), and saturated light point ( LSP ). Specifically, the mean P max of five precipitation treatments was 17.6 μmol CO 2 m −2 s −1 , and the ambient treatment tended to have a higher P max . The +33% treatment had the highest α , and the ambient treatment had lower θ and LCP , higher Rd , and relatively lower LSP . Furthermore, precipitation significantly influenced all model parameters of CO 2 response. The ambient treatment had the highest P max , largest α , and lowest θ , R d , and CO 2 compensation point LCP . Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.

09 BIOMASS FUELS↗

DOE OSTI2025

Microstructure Scale Lithium-Ion Battery Modeling: Part I. On Through-Plane Heterogeneity, Impact of Mesh Representation, and Differences between Macro- and Microscale Models

Li-ion battery performance and degradation are strongly correlated with the electrode microstructures and can be modeled at different scales, each with their own limitations. Herein, we compare predictions achieved with a macro- and a micro-scale model, that is, respectively, neglecting or considering the microstructural heterogeneity of the composite electrodes, on virtual numerically generated and real microstructures. While both models are in relative agreement at the low charge rates, differences arise for fast charging scenarios and especially for the real, highly heterogenous, microstructures. The microscale model predicts that electrolyte concentration saturation and depletion, respectively, at the back of the cathode and of the anode are exacerbated, and that lithium plating occurs earlier for real microstructures. The present work also indicates that the mesh representation significantly impacts the microscale model predictions, and consequently that microscale models should add surface area as a parameter to consider explicitly surface roughness. This article is the first of a series, with subsequent entries further investigating in-plane heterogeneities, lithium plating, and the impact of microstructure representativity on model predictions.

25 ENERGY STORAGE↗

DOE OSTI2025

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗

DOE OSTI2024

Chickpea NCR13 disulfide cross-linking variants exhibit profound differences in antifungal activity and modes of action

Small cysteine-rich antifungal peptides with multi-site modes of action (MoA) have potential for development as biofungicides. In particular, legumes of the inverted repeat-lacking clade express a large family of nodule-specific cysteine-rich (NCR) peptides that orchestrate differentiation of nitrogen-fixing bacteria into bacteroids. These NCRs can form two or three intramolecular disulfide bonds and a subset of these peptides with high cationicity exhibits antifungal activity. However, the importance of intramolecular disulfide pairing and MoA against fungal pathogens for most of these plant peptides remains to be elucidated. Our study focused on a highly cationic chickpea NCR13, which has a net charge of +8 and contains six cysteines capable of forming three disulfide bonds. NCR13 expression in Pichia pastoris resulted in formation of two peptide folding variants, NCR13_PFV1 and NCR13_PFV2, that differed in the pairing of two out of three disulfide bonds despite having an identical amino acid sequence. The NMR structure of each PFV revealed a unique three-dimensional fold with the PFV1 structure being more compact but less dynamic. Surprisingly, PFV1 and PFV2 differed profoundly in the potency of antifungal activity against several fungal plant pathogens and their multi-faceted MoA. PFV1 showed significantly faster fungal cell-permeabilizing and cell entry capabilities as well as greater stability once inside the fungal cells. Additionally, PFV1 was more effective in binding fungal ribosomal RNA and inhibiting protein translation in vitro. Furthermore, when sprayed on pepper and tomato plants, PFV1 was more effective in reducing disease symptoms caused by Botrytis cinerea, causal agent of gray mold disease in fruits, vegetables, and flowers. In conclusion, our work highlights the significant impact of disulfide pairing on the antifungal activity and MoA of NCR13 and provides a structural framework for design of novel, potent antifungal peptides for agricultural use.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Investigation of cosmic ray impact on transmon qubits with different materials through fast decay detection at Fermilab’s SQMS laboratory

Noise sources affecting superconducting qubits, such as cosmic rays and ambient gamma radiation, have garnered attention for their potential impact. These radiations deposit energy in the qubit's substrate, generating high-energy phonons that break Cooper pairs, leading to the formation of quasi-particles. When these quasi-particles tunnel across Josephson junctions, they induce qubit de-excitation, causing relaxation errors. In this study, we employ a fast feedback mechanism for performing qubit reset to detect decay events with high time resolution. This capability along with frequency multiplexed readout allows us to explore error correlations across time and space. Transmon qubits, manufactured within the Superconducting Quantum Materials and Systems (SQMS) center [1], are investigated at the above-ground lab. We study the impact of cosmic rays on qubits with different encapsulations, geometries, and locations on the same or different chips. We present preliminary findings and discuss the implications for the performance of contemporary quantum hardware.

Roy, Tanay↗

DOE OSTI2025

A Review and Comparison of Different Sensitivity Analysis Techniques in Practice

There exist many methods for sensitivity analysis readily available to the practitioner. While each seeks to help the modeler answer the same general question – How do sources of uncertainty or changes in the model inputs relate to uncertainty in the output? – different methods are associated with different assumptions, constraints, and required resources, leading to conclusions that may vary in interpretability and level of detail. Thus, it is crucial that the practitioner selects the desired sensitivity analysis method judiciously, making sure to match the selected approach to the specifics of their problem and to their desired objectives. In this chapter, we provide a practical overview of a collection of widely used, widely available sensitivity analysis methods. We focus on global sensitivity approaches, which seek to characterize how uncertainty in the model output may be allocated to sources of uncertainty in model inputs across the entire input space. Generally, this will require the practitioner to specify a probability distribution over the input space. On the other hand, methods for local sensitivity analysis do not require this specification but they have more limited utility, providing insight into sources of uncertainty associated only with a particular, specified location in the input space. Our hope is that this chapter may serve as a decision-making tool for practitioners, helping to guide the selection of a sensitivity analysis approach that will best fit their needs. To support this goal, we have selected a suite of approaches to cover, which, while not exhaustive, we believe provides a flexible and robust sensitivity analysis toolkit. All methods included are widely used and available in standard software packages.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies

This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Comparative study of the effects of prenatal sevoflurane exposure at different cortical stages on forebrain development and maturation in offspring

Introduction Brain development involves several critical stages, such as proliferation, neuronal migration, axonal pathfinding, and connection formation. Sevoflurane, a γ -aminobutyric acid (GABA) receptor agonist, is widely used as an inhaled general anesthetic. However, its impact on brain development has raised increasing concerns, particularly regarding prenatal exposure. This study aims to investigate the effects of prenatal sevoflurane exposure (PSE) at different cortical stages, focusing on its impact on the migration of glutamatergic and GABAergic neurons and neuronal behavior in offspring. Methods PSE was administered at two critical prenatal stages: embryonic day (E) 12.5 and E18.5. Double in situ hybridization was used to identify the coexpression of GABA receptors in Pax6- and Mash1-positive cells in the forebrain. The radial migration of glutamatergic neurons and the tangential migration of GABAergic neurons were analyzed. Behavioral tests, including the open-field test, elevated plus-maze test, forced swim test, tail suspension test, sucrose preference test, and Morris water maze, were performed on offspring to assess anxiety-like behaviors, depression, and learning and memory impairments. Results PSE inhibits the radial migration of glutamatergic neurons and promotes the tangential migration of GABAergic neurons. Specifically, early exposure (E12.5) inhibited the expression of the Pax6–Tbr2–Tbr1 cascade and the radial migration of Tbr1 in the ventral prefrontal cortex (PFC), whereas late exposure (E18.5) inhibited this process on the dorsal side. In addition, offspring mice with PSE exhibited increased anxiety-like behaviors, rather than depression, as demonstrated by reduced time spent in the center of the open-field test and in the open arms of the elevated plus-maze test. No significant differences were observed in the forced swim test, tail suspension test, or sucrose preference test. Furthermore, learning and memory impairments were observed in the Morris water maze. Conclusion Our results indicate that PSE at E12.5 and E18.5 leads to abnormalities in the migration of glutamatergic and GABAergic neurons, affecting long-term anxiety-like behaviors and causing learning and memory impairments in offspring mice.

Wang, Tianyuan↗

DOE OSTI2024

Light-Induced Charge Separation in Photosystem I from Different Biological Species Characterized by Multifrequency Electron Paramagnetic Resonance Spectroscopy

Photosystem I (PSI) serves as a model system for studying fundamental processes such as electron transfer (ET) and energy conversion, which are not only central to photosynthesis but also have broader implications for bioenergy production and biomimetic device design. In this study, we employed electron paramagnetic resonance (EPR) spectroscopy to investigate key light-induced charge separation steps in PSI isolated from several green algal and cyanobacterial species. Following photoexcitation, rapid sequential ET occurs through either of two quasi-symmetric branches of donor/acceptor cofactors embedded within the protein core, termed the A and B branches. Using high-frequency (130 GHz) time-resolved EPR (TR-EPR) and deuteration techniques to enhance spectral resolution, we observed that at low temperatures prokaryotic PSI exhibits reversible ET in the A branch and irreversible ET in the B branch, while PSI from eukaryotic counterparts displays either reversible ET in both branches or exclusively in the B branch. Furthermore, we observed a notable correlation between low-temperature charge separation to the terminal [4Fe-4S] clusters of PSI, termed F A and F B , as reflected in the measured F A /F B ratio. These findings enhance our understanding of the mechanistic diversity of PSI’s ET across different species and underscore the importance of experimental design in resolving these differences. Though further research is necessary to elucidate the underlying mechanisms and the evolutionary significance of these variations in PSI charge separation, this study sets the stage for future investigations into the complex interplay between protein structure, ET pathways, and the environmental adaptations of photosynthetic organisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

Dong, Yize 一泽董 [Harvard-Smithsonian Center for Ast↗

DOE OSTI2025

Application of PRIM for understanding patterns in carbon dioxide model-observation differences

Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.

Gerken, Tobias [James Madison Univ., Harrisonburg,↗

DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: difference_image dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the difference_image dataset type. These are images created by subtracting a template image from a visit image. This release contains 15,972 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1965

Test strips detect different CO2 concentrations in closed compartments

Four different test strips, using crystal violet for one pair of strips and basic fuchsin as a dye for the second pair, give unambiguous colorimetric indications of four different concentrations of carbon dioxide in the atmosphere of a closed compartment. Tetraethylene pentamine is used as a dye decoloring agent.

Source record↗

NASA NTRS1966

Single projector accommodates slides of different size and format

Projector with two adjustable external units accommodates slides of different size and format. One external unit is the holder for different size slides and includes mounting means for appropriate condensing lens and heat filters. The other unit is a turret lens assembly. The machine is easily adaptable to rear-screen and front-screen projection over various distances.

Gates, G. M.↗