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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transient pattern formation in an active matter contact poisoning model

Abstract One of the most notable features in repulsive particle based active matter systems is motility-induced-phase separation (MIPS) where a dense, often crystalline phase and low density fluid coexist. Most active matter studies involve time-dependent activity; however, there are many active systems where individual particles transition from living or moving to dead or nonmotile due to lack of fuel, infection, or poisoning. Here we consider an active matter particle system at densities where MIPS does not occur. When we add a small number of infected particles that can poison other particles, rendering them nonmotile, we find a rich variety of time dependent pattern formation, including MIPS, a wetting phase, and a fragmented state formed when mobile particles plow through a nonmotile packing. We map the patterns as a function of time scaled by epidemic duration, and show that the pattern formation is robust for a wide range of poisoning rates and activity levels. We also show that pattern formation does not occur in a random death model, but requires the promotion of nucleation by contact poisoning. Our results should be relevant to biological and active matter systems where there is some form of poisoning, death, or transition to nonmotility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗
DOE OSTI2020

Basic Energy Sciences Program Update

This brochure describes updates to the BES program in FY 2019, including new awards, strategic planning activities, and recognition of BES Principal Investigators. It also describes select research highlights from the three divisions in BES.

14 SOLAR ENERGY↗
NASA NTRS1994

Physiological time-series analysis: what does regularity quantify?

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity that appears to have potential application to a wide variety of physiological and clinical time-series data. The focus here is to provide a better understanding of ApEn to facilitate its proper utilization, application, and interpretation. After giving the formal mathematical description of ApEn, we provide a multistep description of the algorithm as applied to two contrasting clinical heart rate data sets. We discuss algorithm implementation and interpretation and introduce a general mathematical hypothesis of the dynamics of a wide class of diseases, indicating the utility of ApEn to test this hypothesis. We indicate the relationship of ApEn to variability measures, the Fourier spectrum, and algorithms motivated by study of chaotic dynamics. We discuss further mathematical properties of ApEn, including the choice of input parameters, statistical issues, and modeling considerations, and we conclude with a section on caveats to ensure correct ApEn utilization.

NASA Discipline Cardiopulmonary↗
NASA NTRS1981

NASA's Biomedical Research Program

The biomedical research program has been established to investigate the major physiological and psychological problems encountered by man when he undertakes spaceflight. The program seeks to obtain a better definition of each problem, an understanding of its underlying mechanism, and ultimately a means of prevention. In pursuing these goals the program also includes a major effort to develop the research tools and procedures it needs where these are not being developed elsewhere. After almost twenty years of manned spaceflight activities and after a much longer period of space related ground-based research, the program now recognizes two characteristics of spaceflight which are truly unique to space. These are weightlessness and one specific form of radiation. In its present stage of maturity much of the research focuses on mechanisms underlying the basic responses of man and animals to weightlessness. The program consists of nine elements. Eight of these are referable to specific physiological problems that have either been encountered in previous manned spaceflight or which are anticipated to occur as spaceflights last longer, traverse steeper orbital inclinations, or are otherwise different from previous missions. The ninth addresses problems that have neither arisen nor can be reasonably predicted but are suspected on the basis of theoretical models, ground-based animal research, or for other reasons. The program's current emphasis is directed toward the motion sickness problem because of its relevance to Space Shuttle operations. Increased awareness and understanding of the radiation hazard has resulted in more emphasis being placed on the biological effects of high energy, high mass number particulate radiation and upon radiation protection . Cardiovascular and musculoskeleta1 studies are pursued in recognition of the considerable fundamental knowledge that must be acquired in these areas before effective countermeasures to the effects of repetitive or long-term flight can be devised. Major new avenues of research will deal with the psychological accompaniments of spaceflight and with mathematical modelling of physiological systems.

Ahn, Chung-Hae↗
DOE OSTI2024

Impacts of Vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 Variants Alpha and Delta on Coronavirus Disease 2019 Transmission Dynamics in Four Metropolitan Areas of the United States

To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. In conclusion, estimated takeoff times are consistent with genomic surveillance data.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1996

Preliminary Work in Obtaining Site-Directed Mutants of Hen Egg White Lysozyme

Protein crystal growth studies are recognized as a critical endeavor in the field of molecular biotechnology. The scientific applications of this field include the understanding of how enzymes function and the accumulation of accurate information of atomic structures, a key factor in the process of rational drug design. NASA has committed substantial investment and resources to the field of protein crystal growth and has conducted many microgravity protein crystal growth experiments aboard shuttle flights. Crystals grown in space tend to be larger, denser and have a more perfect habit and geometry. These improved properties gained in the microgravity environment of space result largely from the reduction of solutal convection, and the elimination of sedimentation at the growing crystal surface. Shuttle experiments have yielded many large, high quality crystals that are suitable for high resolution X-ray diffraction analysis. Examples of biologically important macromolecules which have been successfully crystallized during shuttle missions include: lysozyme, isocitrate lyase, gamma-interferon, insulin, human serum albumin and canavalin. Numerous other examples are also available. In addition to obtaining high quality crystals, investigators are also interested in learning the mechanisms by which the growth events take place. Crystallization experiments indicate that for the enzyme HEWL, measured growth rates do not follow mathematical models for 2D nucleation and dislocation-led growth of tetragonal protein crystals. As has been suggested by the laboratory of Marc L. Pusey, a possible explanation for the disagreement between observation and data is that HEWL tetraconal crystals form by aggregated units of lysozyme in supersaturated solutions. Surface measurement data was shown to fit very well with a model using an octamer unit cell as the growth unit. According to this model, the aggregation pathway and subsequent crystal growth is described by: monomer < ------ > dimer < ------- > tetramer < ------ > octamer < ------ > higher order. It is believed that multimer aggregation of lysozyme occurs by interaction at specific binding sites on the surface of the protein crystals. If the presence of discrete binding sites and the aggregation hypothesis is true, then it follows that the alteration of the binding site(s) should have significant effect on the measurements obtained during growth experiments. Site-directed mutagenesis allows the specific alteration of proteins by replacement, deletion or addition of specific amino acid residues. This report outlines the approach for this strategy and the progress made thus far toward that end.

Holmes, Leonard D.↗
NASA NTRS2007

Stochastic Effects in Computational Biology of Space Radiation Cancer Risk

Estimating risk from space radiation poses important questions on the radiobiology of protons and heavy ions. We are considering systems biology models to study radiation induced repair foci (RIRF) at low doses, in which less than one-track on average transverses the cell, and the subsequent DNA damage processing and signal transduction events. Computational approaches for describing protein regulatory networks coupled to DNA and oxidative damage sites include systems of differential equations, stochastic equations, and Monte-Carlo simulations. We review recent developments in the mathematical description of protein regulatory networks and possible approaches to radiation effects simulation. These include robustness, which states that regulatory networks maintain their functions against external and internal perturbations due to compensating properties of redundancy and molecular feedback controls, and modularity, which leads to general theorems for considering molecules that interact through a regulatory mechanism without exchange of matter leading to a block diagonal reduction of the connecting pathways. Identifying rate-limiting steps, robustness, and modularity in pathways perturbed by radiation damage are shown to be valid techniques for reducing large molecular systems to realistic computer simulations. Other techniques studied are the use of steady-state analysis, and the introduction of composite molecules or rate-constants to represent small collections of reactants. Applications of these techniques to describe spatial and temporal distributions of RIRF and cell populations following low dose irradiation are described.

Cucinotta, Francis A.↗
DOE OSTI2025

Plant Roots and the Fate of Mineral-Associated Soil Carbon (Final Report)

Atmospheric CO 2 concentrations continue to rise due to human activities, but there are also natural mechanisms operating in ecosystems that can store carbon in soil long-term. The organic carbon derived from organisms in soil becomes associated with minerals, where it can be protected for thousands of years. Plants are particularly important contributors of carbon belowground, via their roots. The long-term protection of carbon contributed to soil has great value to humans as climate change looms. But, to keep growing, living plants and soil microbes also need to be able to access and recycle soil nutrients that are stored along with the carbon. In this DOE-funded work, Cardon (MBL), Keiluweit (UMass Amherst/University of Lausanne), Malmstrom (MSU), and Riley (LBNL) used lab and greenhouse experiments coupled with mathematical modeling to determine mechanisms by which plant roots and their associated microbes can dislodge organic matter from soil minerals, making its components available for recycling, but also making its carbon vulnerable to re-release to the atmosphere as CO 2 .

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

A review of human physiological and performance changes associated with desynchronosis of biological rhythms

This review discusses the effects, in the aerospace environment, of alterations in approximately 24-h periodicities (circadian rhythms) upon physiological and psychological functions and possible therapies for desynchronosis induced by such alterations. The consequences of circadian rhythm alteration resulting from shift work, transmeridian flight, or altered day lengths are known as desynchronosis, dysrhythmia, dyschrony, jet lag, or jet syndrome. Considerable attention is focused on the ability to operate jet aircraft and manned space vehicles. The importance of environmental cues, such as light-dark cycles, which influence physiological and psychological rhythms is discussed. A section on mathematical models is presented to enable selection and verification of appropriate preventive and corrective measures and to better understand the problem of dysrhythmia.

Winget, C. M.↗
NASA NTRS2010

Analysis of Ancient Fluvial Patterns on the Surface of Mars

This project involves the study of ancient fluvial patterns on the surface of Mars, including raised curvilinear features (RCFs) and negative relief channels. It requires the use of geological images provided by the Mars Reconnaissance Orbiter to determine how water shaped the surface of Mars in the form of rivers, lakes and/or oceans approximately 3.5 billion years ago, during the Noachian period. The role of the intern is to examine the images and record the corresponding measurements of ancient river systems in an Excel spreadsheet to assist in determining the Noachian water cycle on Mars. Resources used to make these measurements include the Arena software, hand-drawn sketch maps, Microsoft Word, Microsoft Excel and the images provided by the Mars Reconnaissance Orbiter. The Context Imager (CTX) returns black and white images at a resolution of six meters per pixel. The camera can take images with a width of 30 km and a length of 160 km. Seventeen images were observed in total. Images are analyzed and notes are taken concerning their terminal deposits, stream ordering and drainage pattern. The Arena software is utilized to make the images more visible by allowing control of contrast and magnification. Once the image is adjusted, measurements: length, average width, drainage basin area, sinuous ridge area are recorded, at a magnification of one, through using the line segment and polygon tools. After an image has been analyzed and measured, a sketch map is drawn in order to clearly identify the various segments, basins and terminal deposits the intern observed. Observations are used to further classify the fluvial patterns; their drainage pattern is defined as dendritic, parallel, trellis, rectangular, radial, centripetal, deranged or discordant. Once observational notes are completed, mathematical relations are used to determine drainage density, stream frequency, theoretic basin area and sinuosity index. These data will be added to a larger data set that will yield a comprehensive view of early Mars drainage systems. The data obtained from the work conducted will be used to characterize the nature and behavior of water on the surface of Mars. Thorough understanding of the Martian water cycle will serve as biologically significant information. Through working on this project, I acquired insight into the study of planet Mars, and skills in the Arena software as well as the organization of a vast amount of data.

Jethani, Henna↗
DOE OSTI2023

Vessel Rupture Thresholds for Vessel–Bubble Interactions Using an Earthworm Vasculature Model

Intravenous microbubble oscillation in the presence of ultrasound has the potential to yield a wide range of therapeutic benefits. However, the likelihood of vessel damage caused by mechanical effects has not been quantified as a function of the numerous important parameters in therapeutic ultrasound procedures. In this study, we examined the effects of microbubbles injected into the vasculature of the earthworm. It was found that the elastic properties of earthworm blood vessels are similar to those of arteries in older humans, and that earthworms are well suited to the large number of experiments necessary to investigate safety of procedures involving microbubble oscillation in sonicated vessels. Microbubbles were infused into earthworm vessels, and the rupture time during sonication was recorded as a function of ultrasound frequency, pulse repetition frequency and acoustic pressure. A modified mechanical index (MMI) was defined that successfully captured the trends in rupture probability and rupture time for the different parameter values, creating a database of vessel rupture thresholds. In the absence of bubbles, the product of MMI squared and rupture time was approximately constant, indicating a possible radiation-force effect. Here, the MMI was an effective correlating parameter in the presence of bubbles, though the mathematical dependence is not yet apparent. The results of the study are expected to be valuable in designing more refined studies in vertebrate models, as well as informing computational models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Online MCMC Thinning with Kernelized Stein Discrepancy

A fundamental challenge in Bayesian inference is efficient representation of a target distribution. Many nonparametric approaches do so by sampling a large number of points using variants of Markov chain Monte Carlo (MCMC). Here, we propose an MCMC variant that retains only those posterior samples which exceed a kernelized Stein discrepancy (KSD) threshold, which we call KSD thinning. We establish the convergence and complexity trade-offs for several settings of KSD thinning as a function of the KSD threshold parameter, sample size, and other problem parameters. We provide experimental comparisons against other online nonparametric Bayesian methods that generate low-complexity posterior representations. We observe superior consistency/complexity trade-offs across a range of settings including MCMC sampling on two Bayesian inference problems from the biological sciences, and 10 × inference speedup and storage reduction for Bayesian neural networks with no loss of accuracy and no increase in training time. Our code is available at https://github.com/colehawkins/KSD-Thinning.

Bayesian inference↗
DOE OSTI2020

Improving Excited-State Potential Energy Surfaces via Optimal Orbital Shapes

In this work, we demonstrate that, rather than resorting to high-cost dynamic correlation methods, qualitative failures in excited-state potential energy surface predictions can often be remedied at no additional cost by ensuring that optimal molecular orbitals are used for each individual excited state. This approach also avoids the weighting choices required by state-averaging and dynamic weighting and obviates their need for expensive wave function response calculations when relaxing excited-state geometries. Although multistate approaches are of course preferred near conical intersections, other features of excited-state potential energy surfaces can benefit significantly from our single-state approach. In three different systems, including a double bond dissociation, a biologically relevant amino hydrogen dissociation, and an amino-to-ring intramolecular charge transfer, we show that state-specific orbitals offer qualitative improvements over the state-averaged status quo.

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

Image processing tools for petabyte-scale light sheet microscopy data

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Crop models: integrating systems from the molecular to global for agricultural productivity and sustainability

Mathematical models that simulate crop growth in response to environmental conditions and management practices are essential tools for exploring agriculture-based strategies to address food security and environmental sustainability challenges. Early applications of crop models focused on supporting farmers in making management decisions. Applications have since expanded to estimating future impacts on local and global food production from changing climates. Emerging applications of crop models aim to leverage how these models integrate plant processes across biological scales to identify engineering or breeding strategies that account for environmentally-responsive dynamics at field scales and for exploring solutions to improve sustainability. In this review, we highlight recent studies across these four broad application areas and highlight potential future directions for the crop modeling field.

Piao, Ximin [Univ. of Illinois at Urbana-Champaign↗
DOE OSTI2024

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A general quantum algorithm for open quantum dynamics demonstrated with the Fenna-Matthews-Olson complex

Using quantum algorithms to simulate complex physical processes and correlations in quantum matter has been a major direction of quantum computing research, towards the promise of a quantum advantage over classical approaches. In this work we develop a generalized quantum algorithm to simulate any dynamical process represented by either the operator sum representation or the Lindblad master equation. We then demonstrate the quantum algorithm by simulating the dynamics of the Fenna-Matthews-Olson (FMO) complex on the IBM QASM quantum simulator. This work represents a first demonstration of a quantum algorithm for open quantum dynamics with a moderately sophisticated dynamical process involving a realistic biological structure. We discuss the complexity of the quantum algorithm relative to the classical method for the same purpose, presenting a decisive query complexity advantage of the quantum approach based on the unique property of quantum measurement.

97 MATHEMATICS AND COMPUTING↗