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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Can assembly bias explain the lensing amplitude of the BOSS CMASS sample in a Planck cosmology?

ABSTRACT In this paper, we investigate whether galaxy assembly bias can reconcile the 20–40 ${{\ \rm per\ cent}}$ disagreement between the observed galaxy projected clustering signal and the galaxy–galaxy lensing signal in the Baryon Oscillation Spectroscopic Survey CMASS galaxy sample. We use the suite of abacuscosmos lambda cold dark matter simulations at Planck best-fitting cosmology and two flexible implementations of extended halo occupation distribution (HOD) models that incorporate galaxy assembly bias to build forward models and produce joint fits of the observed galaxy clustering signal and the galaxy–galaxy lensing signal. We find that our models using the standard HODs without any assembly bias generalizations continue to show a 20–40 ${{\ \rm per\ cent}}$ overprediction of the observed galaxy–galaxy lensing signal. We find that our implementations of galaxy assembly bias do not reconcile the two measurements at Planck best-fitting cosmology. In fact, despite incorporating galaxy assembly bias, the satellite distribution parameter, and the satellite velocity bias parameter into our extended HOD model, our fits still strongly suggest a $\sim \! 34{{\ \rm per\ cent}}$ discrepancy between the observed projected clustering and galaxy–galaxy lensing measurements. It remains to be seen whether a combination of other galaxy assembly bias models, alternative cosmological parameters, or baryonic effects can explain the amplitude difference between the two signals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Could multiple voids explain the cosmic microwave background Cold Spot anomaly?

Understanding the observed Cold Spot (CS) (temperature of ~ -150 mu K at its centre) on the Cosmic Microwave Background (CMB) is an outstanding problem. Explanations vary from assuming it is just a ≳ 3σ primordial Gaussian fluctuation to the imprint of a supervoid via the Integrated Sachs-Wolfe and Rees-Sciama (ISW+RS) effects. Since single spherical supervoids cannot account for the full profile, the ISW+RS of multiple line-of-sight voids is studied here to mimic the structure of the cosmic web. Two structure configurations are considered. The first, through simulations of 20 voids, produces a central mean temperature of ~-50 mu K. In this model the central CS temperature lies at ~ 2σ but fails to explain the CS hot ring. An alternative multi-void model (using more pronounced compensated voids) produces much smaller temperature profiles, but contains a prominent hot ring. Arrangements containing closely placed voids at low redshift are found to be particularly well suited to produce CS-like profiles. We then measure the significance of the CS if CS-like profiles (which are fitted to the ISW+RS of multi-void scenarios) are removed. Furthermore, the CS tension with the LCDM model can be reduced dramatically for an array of temperature profiles smaller than the CS itself.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering

Abstract CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Explaining the extra crystal-field mode in 𝐴 ⁢Ce ⁢𝑋 2 (𝐴 = K, Rb, Na; 𝑋 = O, S, Se, Te)

A growing list of Ce-based magnets have shown an extra and heretofore unexplained crystal electric field (CEF) mode at high energies. We describe a process whereby an optical phonon can produce a split CEF mode well above the phonon energy. We use density functional theory and point-charge model calculations to estimate the phonon distortions and coupling to model this effect in KCeO 2 , showing that it accounts for the extra CEF mode observed. Furthermore, this mechanism is generic and may explain the extra modes observed on a variety of Ce 3+ compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Explaining Snowball-in-Hell Phenomena in Heavy-Ion Collisions Using a Novel Thermodynamic Variable

A loosely bound hadronic molecule produced by a relativistic heavy-ion collision has been described as a “snowball in hell” since it emerges from a hadron resonance gas whose temperature is orders of magnitude larger than the binding energy of the molecule. This remarkable phenomenon can be explained in terms of a novel thermodynamic variable called the “contact” that is conjugate to the binding momentum of the molecule. The production rate of the molecule can be expressed in terms of the contact density at the kinetic freeze-out of the hadron resonance gas. It approaches a nonzero limit as the binding energy goes to 0.

Relativistic heavy-ion collisions↗
DOE OSTI2018

Explaining Cold-Pulse Dynamics in Tokamak Plasmas Using Local Turbulent Transport Models

A long-standing enigma in plasma transport has been resolved by modeling of cold-pulse experiments conducted on the Alcator C-Mod tokamak. Controlled edge cooling of fusion plasmas triggers core electron heating on time scales faster than an energy confinement time, which has long been interpreted as strong evidence of nonlocal transport. Here, this Letter shows that the steady-state profiles, the cold-pulse rise time, and disappearance at higher density as measured in these experiments are successfully captured by a recent local quasilinear turbulent transport model, demonstrating that the existence of nonlocal transport phenomena is not necessary for explaining the behavior and time scales of cold-pulse experiments in tokamak plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Structures of the Porphyromonas gingivalis OxyR regulatory domain explain differences in expression of the OxyR regulon in Escherichia coli and P. gingivalis

Differences in OxyR regulated expression of oxidative stress genes between Escherichia coli and Porphyromonas gingivalis are explained by very minor differences in structure and amino-acid sequence of the respective oxidized and reduced OxyR regulatory domains. These differences affect OxyR quaternary structures and are predicted from model building of full length OxyR–DNA complexes to confer distinct modes of DNA binding on this transcriptional regulator. OxyR transcriptionally regulates Escherichia coli oxidative stress response genes through a reversibly reducible cysteine disulfide biosensor of cellular redox status. Structural changes induced by redox changes in these cysteines are conformationally transmitted to the dimer subunit interfaces, which alters dimer and tetramer interactions with DNA. In contrast to E. coli OxyR regulatory-domain structures, crystal structures of Porphyromonas gingivalis OxyR regulatory domains show minimal differences in dimer configuration on changes in cysteine disulfide redox status. This locked configuration of the P. gingivalis OxyR regulatory-domain dimer closely resembles the oxidized (activating) form of the E. coli OxyR regulatory-domain dimer. It correlates with the observed constitutive activation of some oxidative stress genes in P. gingivalis and is attributable to a single amino-acid insertion in P. gingivalis OxyR relative to E. coli OxyR. Modelling of full-length P. gingivalis, E. coli and Neisseria meningitidis OxyR–DNA complexes predicts different modes of DNA binding for the reduced and oxidized forms of each.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Intermolecular correlations are necessary to explain diffuse scattering from protein crystals

Conformational changes drive protein function, including catalysis, allostery, and signaling. X-ray diffuse scattering from protein crystals has frequently been cited as a probe of these correlated motions, with significant potential to advance our understanding of biological dynamics. However, recent work challenged this prevailing view, suggesting instead that diffuse scattering primarily originates from rigid body motions and could therefore be applied to improve structure determination. To investigate the nature of the disorder giving rise to diffuse scattering, and thus the potential applications of this signal, a diverse repertoire of disorder models was assessed for its ability to reproduce the diffuse signal reconstructed from three protein crystals. This comparison revealed that multiple models of intramolecular conformational dynamics, including ensemble models inferred from the Bragg data, could not explain the signal. Models of rigid body or short-range liquid-like motions, in which dynamics are confined to the biological unit, showed modest agreement with the diffuse maps, but were unable to reproduce experimental features indicative of long-range correlations. Extending a model of liquid-like motions to include disorder across neighboring proteins in the crystal significantly improved agreement with all three systems and highlighted the contribution of intermolecular correlations to the observed signal. These findings anticipate a need to account for intermolecular disorder in order to advance the interpretation of diffuse scattering to either extract biological motions or aid structural inference.

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

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
DOE OSTI2019

Plant phylogenetic history explains in-stream decomposition at a global scale

1. Evolutionary history and adaptation to climate shape plant traits. Some include leaf traits that influence litter quality. As a result, evolutionary history should affect litter decomposition, a crucial ecosystem process. In addition, litter decomposition is directly influenced by climate. Similarly, we expect plant phylogeny, adaptation and climate to jointly influence litter decomposition. These effects and their interactions have yet to be untangled at a global scale. 2. Here we introduce an analysis of variation in litter decomposition rates in rivers and streams across 285 published studies for 239 species (from ferns to angiosperms) distributed at 494 locations world-wide. We estimated the relative contributions of climatic conditions and phylogenetic heritage on litter decomposition rates, partitioning phylogenetic from climatic effects at the site and species levels using phylogenetic eigenvector analysis and phylogenetic linear mixed models. In addition, we modelled transitions in decomposition rates under a suite of multiple adaptive-regime Ornstein–Uhlenbeck models to test the hypothesis that natural selection has shaped clade-level litter decomposition rates. 3. Leaf litter decomposition rate exhibited a significant phylogenetic signal. Modelling decomposition rate as a function of location, climatic niche and phylogeny consistently recovered phylogeny alone as one of the top models in species-level analyses. Since many previous studies have focused on the same species across many locations, we also conducted analyses at the species × site level. Both phylogenetic and climatic factors were favoured in models of this analysis, but the single most important predictor for angiosperms and for all taxa analysed together was phylogeny alone. 4. Synthesis. For plant species distributed globally at nearly 500 locations we found that plant phylogenetic history is a critically important predictor of litter decomposition rate in rivers and streams, explaining more of the variance in decomposition than site or climatic regime. Thus, our study demonstrates the influence of evolutionary history on suites of plant traits that shape a key ecosystem process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Abstract Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F ST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout ( Oncorhynchus mykiss ) in the Columbia River Basin, USA . Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes ( N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Hand, Brian K.↗
DOE OSTI2022

Granal thylakoid structure and function: explaining an enduring mystery of higher plants

Summary In higher plants, photosystems II and I are found in grana stacks and unstacked stroma lamellae, respectively. To connect them, electron carriers negotiate tortuous multi‐media paths and are subject to macromolecular blocking. Why does evolution select an apparently unnecessary, inefficient bipartition? Here we systematically explain this perplexing phenomenon. We propose that grana stacks, acting like bellows in accordions, increase the degree of ultrastructural control on photosynthesis through thylakoid swelling/shrinking induced by osmotic water fluxes. This control coordinates with variations in stomatal conductance and the turgor of guard cells, which act like an accordion's air button. Thylakoid ultrastructural dynamics regulate macromolecular blocking/collision probability, direct diffusional pathlengths, division of function of Cytochrome b 6 f complex between linear and cyclic electron transport, luminal pH via osmotic water fluxes, and the separation of pH dynamics between granal and lamellar lumens in response to environmental variations. With the two functionally asymmetrical photosystems located distantly from each other, the ultrastructural control, nonphotochemical quenching, and carbon‐reaction feedbacks maximally cooperate to balance electron transport with gas exchange, provide homeostasis in fluctuating light environments, and protect photosystems in drought. Grana stacks represent a dry/high irradiance adaptation of photosynthetic machinery to improve fitness in challenging land environments. Our theory unifies many well‐known but seemingly unconnected phenomena of thylakoid structure and function in higher plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Can surface cracks and unipolar arcs explain breakdown and gradient limits?

The authors argue that the physics of unipolar arcs and surface cracks can help understand rf breakdown and vacuum arc data. They outline a model of the basic mechanisms involved in breakdown and explore how the physics of unipolar arcs and cracks can simplify the picture of breakdown and gradient limits in accelerators, tokamaks as well as laser ablation, micrometeorites, and other applications. Cracks are commonly seen in SEM images of arc damage and they are produced as the liquid metal cools. They can produce the required field enhancements to explain field emission data and can produce mechanical failure of the surface that would trigger breakdown events. Unipolar arcs can produce currents sufficient to short out rf structures, and can cause the sort of damage seen in SEM images. They should be unstable, and possibly self-quenching, as seen in optical fluctuations and surface damage. The authors describe some details and consider the predictions of this simple model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

MO-DE-BRA-06: 3D Image Acquisition and Reconstruction Explained with Online Animations

Purpose: Understanding the principles of 3D imaging and image reconstruction is fundamental to the field of medical imaging. Clinicians, technologists, physicists, patients, students, and inquisitive minds all stand to benefit from greater comprehension of the supporting technologies. To help explain the basic principles of 3D imaging, we developed multi-frame animations that convey the concepts of tomographic imaging. The series of free (gif) animations are accessible online, and provide a multimedia introduction to the main concepts of image reconstruction. Methods: Text and animations were created to convey the principles of analytic tomography in CT, PET, and SPECT. Specific topics covered included: principles of sinograms/image data storage, forward projection, principles of PET acquisitions, and filtered backprojection. A total of 8 animations were created and presented for CT, PET, and digital phantom formats. In addition, a free executable is also provided to allow users to create their own tomographic animations – providing an opportunity for interaction and personalization to help foster user interest. Results: Tutorial text and animations have been posted online, freely available to view or download. The animations are in first position in a google search of “image reconstruction animations”. The website currently receives approximately 200 hits/month, from all over the world, and the usage is growing. Positive feedback has been collected from users. Conclusion: We identified a need for improved teaching tools to help visualize the (temporally variant) concepts of image reconstruction, and have shown that animations can be a useful tool for this aspect of education. Furthermore, posting animations freely on the web has shown to be a good way to maximize their impact in the community. In future endeavors, we hope to expand this animated content, to cover principles of iterative reconstruction, as well as other phenomena relating to imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Natural Aerosols Explain Seasonal and Spatial Patterns of Southern Ocean Cloud Albedo

Small particles called aerosols act as nucleation sites for cloud drop formation, affecting clouds and cloud properties – ultimately influencing the cloud dynamics, lifetime, water path and areal extent that determine the reflectivity (albedo) of clouds. The concentration Nd of droplets in clouds that influences planetary albedo is sensitive to the availability of aerosol particles on which the droplets form. Natural aerosol concentrations not only affect cloud properties themselves, but also modulate the sensitivity of clouds to changes in anthropogenic aerosols. Here, it is shown that modeled natural aerosols, principally marine biogenic primary and secondary aerosol sources, explain more than half of the spatiotemporal variability in satellite-observed Nd. Enhanced Nd over regions of high biological activity is found to be driven primarily by high concentrations of sulfate aerosol at lower Southern Ocean latitudes (35-45°S) and by organic matter in sea spray aerosol at higher latitudes (45-55°S). Biogenic sources are estimated to increase the summertime mean reflected solar radiation in excess of 10 W m-2 over parts of the Southern Ocean, which is comparable to the annual mean increases expected from anthropogenic aerosols over heavily polluted regions of the Northern Hemisphere.

cloud droplet concentration↗
DOE OSTI2020

Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences

Data science has primarily focused on big data, but for many physics, chemistry, and engineering applications, data are often small, correlated and, thus, low dimensional, and sourced from both computations and experiments with various levels of noise. Typical statistics and machine learning methods do not work for these cases. Expert knowledge is essential, but a systematic framework for incorporating it into physics-based models under uncertainty is lacking. Here, we develop a mathematical and computational framework for probabilistic artificial intelligence (AI)–based predictive modeling combining data, expert knowledge, multiscale models, and information theory through uncertainty quantification and probabilistic graphical models (PGMs). We apply PGMs to chemistry specifically and develop predictive guarantees for PGMs generally. Our proposed framework, combining AI and uncertainty quantification, provides explainable results leading to correctable and, eventually, trustworthy models. The proposed framework is demonstrated on a microkinetic model of the oxygen reduction reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Loss of a satellite could explain Saturn’s obliquity and young rings

The origin of Saturn’s ~26.7° obliquity and ~100-million-year-old rings is unknown. The observed rapid outward migration of Saturn’s largest satellite, Titan, could have raised Saturn’s obliquity through a spin-orbit precession resonance with Neptune. We use Cassini data to refine estimates of Saturn’s moment of inertia, finding that it is just outside the range required for the resonance. We propose that Saturn previously had an additional satellite, which we name Chrysalis, that caused Saturn’s obliquity to increase through the Neptune resonance. Destabilization of Chrysalis’s orbit ~100 million years ago can then explain the proximity of the system to the resonance and the formation of the rings through a grazing encounter with Saturn.

Science & Technology - Other Topics↗
DOE OSTI2012

Contraction of electroweak model can explain the interactions neutrinos with matter

The very rare interactions neutrinos with matter and the dependence of the corresponding cross-section on neutrinos energy are explained as contraction of the gauge group of the Electroweak Model already at the level of classical gauge fields. Small contraction parameter is connected with the universal Fermi constant of weak interactions and neutrino energy as {sup 2}(s)=√(G{sub F{sup S}}).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗