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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A minimal supersymmetric SU(5) missing-partner model

We explore a missing-partner model based on the minimal SU(5) gauge group with 75, 50 and 50¯ Higgs representations, assuming a super-GUT CMSSM scenario in which soft supersymmetry-breaking parameters are universal at some high scale Min above the GUT scale MGUT. We identify regions of parameter space that are consistent with the cosmological dark matter density, the measured Higgs mass and the experimental lower limit on τ(p → K + ν). These constraints can be satisfied simultaneously along stop coannihilation strips in the super-GUT CMSSM with tanβ ~ 3.5–5 where the input gaugino mass m 1/2 ~15–25 TeV, corresponding after strong renormalization by the large GUT Higgs representations between M in and M GUT to m LSP ,m t ~ 1 ~ 2.5–5 TeV and m g ~ ~ 13–20 TeV, with the light-flavor squarks significantly heavier. We find that τ(p → K + ν) ≲ 3 × 10 34 years throughout the allowed range of parameter space, within the range of the next generation of searches with the JUNO, DUNE and Hyper-Kamiokande experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Flipped SU(5) GUT phenomenology: proton decay and $\mathbf {g_\mu - 2}$

We consider proton decay and $\mathbf {g_\mu - 2}$ in flipped SU(5) GUT models. We first study scenarios in which the soft supersymmetry-breaking parameters are constrained to be universal at some high scale M in above the standard GUT scale where the QCD and electroweak SU(2) couplings unify. In this case the proton lifetime is typically > rsim10 36 years, too long to be detected in the foreseeable future, and the supersymmetric contribution to $\mathbf {g_\mu - 2}$ is too small to contribute significantly to resolving the discrepancy between the experimental measurement and data-driven calculations within the Standard Model. However, we identify a region of the constrained flipped SU(5) parameter space with large couplings between the 10- and 5-dimensional GUT Higgs representations where p → e + π 0 decay may be detectable in the Hyper-Kamiokande experiment now under construction, though the contribution to $\mathbf {g_\mu - 2}$ is still small. A substantial contribution to $\mathbf {g_\mu - 2}$ is possible, however, if the universality constraints on the soft supersymmetry-breaking masses are relaxed. We find a ‘quadrifecta’ region where observable proton decay co-exists with a (partial) supersymmetric resolution of the $\mathbf {g_\mu - 2}$ discrepancy and acceptable values of m h and the relic LSP density.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Systematics of the chemical freeze-out line in the high baryon density regime explored at SIS100

The systematic uncertainties of chemical freeze-out fits at SIS100 energies (Au+Au reactions at $\sqrt{s_{NN}}$ = 3 – 5 GeV) are studied using UrQMD simulations. Although hadron production in UrQMD does not occur on a sharp chemical freeze-out hyper-surface, the extracted fit quality is shown to be very good. The extracted chemical parameters depend on the selected hadron species as well as the underlying equation of state (EoS) of the matter. Including light nuclei and anti-protons in the fit increases the expected freeze-out temperature, while a stiffer EoS increases the obtained chemical potential. Similarly, the baryon densities extracted by the thermal fits depend on the choice of hadrons as well as the underlying equation of state. These results are important for the upcoming CBM@FAIR physics program and highlight that a degree of caution is advised when one relates the chemical freeze-out curve to features on the QCD phase diagram like the critical endpoint or a possible phase transition.

Hofmann, Emma Lilith [GSI Helmholtzzentrum für Sch↗
DOE OSTI2024

Observational constraints on early dark energy

In this paper, we review and update constraints on the Early Dark Energy (EDE) model from cosmological data sets, in particular Planck PR3 and PR4 cosmic microwave background (CMB) data and large-scale structure (LSS) data sets including galaxy clustering and weak lensing data from the Dark Energy Survey, Subaru Hyper Suprime-Cam and KiDS+VIKING-450, as well as BOSS/eBOSS galaxy clustering and Lyman-[Formula: see text] forest data. We detail the fit to CMB data, and perform the first analyses of EDE using the CAMSPEC and Hillipop likelihoods for Planck CMB data, rather than Plik, both of which yield a tighter upper bound on the allowed EDE fraction than that found with Plik. We then supplement CMB data with LSS data in a series of new analyses. All these analyses are concordant in their Bayesian preference for [Formula: see text]CDM over EDE, as indicated by marginalized posterior distributions. We perform a series of tests of the impact of priors in these results, and compare with frequentist analyses based on the profile likelihood, finding qualitative agreement with the Bayesian results. All these tests suggest prior volume effects are not a determining factor in analyses of EDE. This work provides both a review of existing constraints and several new analyses.

Astronomy & Astrophysics↗
DOE OSTI2022

Genetic programming for understanding cognitive biases that generate polarization in social networks

Recent studies have applied agent-based models to infer human-interpretable explanations of individual-scale behaviors that generate macro-scale patterns in complex social systems. Genetic programming has proven to be an ideal explainable AI tool for this purpose, where primitives may be expressed in an interpretable fashion and assembled into agent rules. Evolutionary model discovery (EMD) is a tool that combines genetic programming and random forest feature importance analysis, to infer individual-scale, human-interpretable explanations from agent-based models. We deploy EMD to investigate the cognitive biases behind the emergence of ideological polarization within a population. An agent-based model is developed to simulate a social network, where agents are able to create or sever links with one another, and update an internal ideological stance based on their neighbors' stances. Agent rules govern these actions and constitute of cognitive biases. A set of 7 cognitive biases are included as genetic program primitives in the search for rules that generate hyper-polarization among the population of agents. We find that heterogeneity in cognitive biases is more likely to generate polarized social networks. Highly polarized social networks are likely to emerge when individuals with confirmation bias are exposed to those with either attentional bias, egocentric bias, or cognitive dissonance.

Gunaratne, Chathika↗
DOE OSTI2025

ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods struggle with generalization across variables and geographies and are constrained by the quadratic complexity of Vision Transformer (ViT) self-attention. We introduce ORBIT-2, a scalable foundation model for global, hyper-resolution climate downscaling. ORBIT-2 incorporates two key innovations: (1) Residual Slim ViT (Reslim), a lightweight architecture with residual learning and Bayesian regularization for efficient, robust prediction; and (2) TILES, a tile-wise sequence scaling algorithm that reduces self-attention complexity from quadratic to linear, enabling long-sequence processing and massive parallelism. ORBIT-2 scales to 10 billion parameters across 65,536 GPUs, achieving up to 4.1 ExaFLOPS sustained throughput and 74–98% strong scaling efficiency. It supports downscaling to 0.9 km global resolution and processes sequences up to 4.2 billion tokens. On 7 km resolution benchmarks, ORBIT-2 achieves high accuracy with R2 scores in range of 0.98–0.99 against observation data.

Wang, Xiao [ORNL] (ORCID:0000000165451943)↗
DOE OSTI2020

Parallel Lattice Subpaving Map (plsm)

Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.

Fackler, Philip↗
DOE OSTI2024

Domain-decomposition nonlinear manifold reduced order model

This software combines nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD) techniques. NM-ROMs, which utilize a shallow, sparse autoencoder trained with full order model (FOM) snapshot data, approximate the FOM state on a nonlinear manifold. These models offer advantages over linear-subspace ROMs (LS-ROMs) particularly in scenarios with slowly decaying Kolmogorov n-width. However, the training of NM-ROMs involves a number of parameters that scale with the size of the FOM, and storing high-dimensional FOM snapshots can significantly increase the cost of ROM training for extreme-scale problems. To mitigate these costs, the software employs DD to partition the FOM into smaller subdomains, computes NM-ROMs for each, and then integrates these to form a global NM-ROM. This strategy offers multiple benefits: it enables parallel training of subdomain NM-ROMs, reduces the number of parameters needed, decreases the dimensional requirements of subdomain FOM training data, and allows for customization to the unique characteristics of each FOM subdomain. The use of a shallow, sparse autoencoder architecture in each subdomain NM-ROM facilitates the application of hyper-reduction (HR), simplifying the nonlinear complexities and enhancing computational speed. This software marks the inaugural application of NM-ROM combined with HR to a DD problem. It features an algebraic DD reformulation of the FOM, training of NM-ROMs with HR for each subdomain, and employs a sequential quadratic programming (SQP) solver for the evaluation of the coupled global NMROM. The effectiveness of the DD NM-ROM with HR is numerically demonstrated on the 2D steady-state Burgers' equation, showing an order of magnitude improvement in accuracy over the DD LS-ROM with HR.

Diaz, AlejandroN↗
DOE OSTI2023

GIIP (Gaussian Integral Inner Products)

SAND2024-08692O The Gaussian Integral Inner Products (GIIP) calculates the integral of squared difference of atomic density functions minimized over the orthogonal group. It uses the hyper-spherical coverings library to sample orthogonal group. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hardin, Thomas↗
DOE OSTI2025

CyRRL (Cyber Resilient Reinforcement Learning for grid voltage control) [SWR-24-115]

This codebase contains a multi-agent, actor-critic reinforcement learning implementation for cyber-resilient grid voltage control. It uses a 123-bus OpenDSS system as the environment, with three-phase power flow translating nodal power injections into solved nodal voltages. The reward function penalizes deviations from nominal voltage as well as reactive power dispatch, while encouraging agents to take actions that result in fast convergence to nominal conditions. The codebase models false data injection attacks and includes functionality for training, testing, hyper-parameter tuning, and visualization.

Murphy, Sinnott [National Renewable Energy Laborat↗
DOE OSTI2025

ORBIT-2 Weather and Climate Downscaling Software Repository

ORBIT-2 is a scalable foundation model for global, hyper-resolution climate and weather downscaling. ORBIT-2 incorporates two key innovations: (1) Residual Slim ViT (Reslim), a lightweight architecture with residual learning and Bayesian regularization for efficient, robust prediction; and (2) TILES, a tile-wise sequence scaling algorithm that reduces self-attention complexity from quadratic to linear, enabling long-sequence processing and massive parallelism. ORBIT-2 scales to 10 billion parameters across 65,536 GPUs, achieving up to 4.1 ExaFLOPS sustained throughput and 74–98% strong scaling efficiency. It supports downscaling to 0.9 km global resolution and processes sequences up to 4.2 billion tokens. On 7 km resolution benchmarks, ORBIT-2 achieves high accuracy with 𝑅2 scores in range of 0.98–0.99 against observation data.

Wang, Xiao [Oak Ridge National Laboratory]↗
DOE OSTI2026

HdsaLib

HdsaLib performs hyper-differential sensitivity analysis in optimization problems that are constrained by partial differential equation problems. The software aids researchers in understanding the impact of uncertainties on their optimization models. The tool has been applied for use in ice sheet modeling, fluid flow modeling, atmospheric tracer transport modeling, and subsurface flow modeling. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

van Bloemen Waanders, Bart [Sandia National Lab. (↗
DOE OSTI2024

Horizontal gene transfer of the Mer operon is associated with large effects on the transcriptome and increased tolerance to mercury in nitrogen-fixing bacteria

Abstract Background Mercury (Hg) is highly toxic and has the potential to cause severe health problems for humans and foraging animals when transported into edible plant parts. Soil rhizobia that form symbiosis with legumes may possess mechanisms to prevent heavy metal translocation from roots to shoots in plants by exporting metals from nodules or compartmentalizing metal ions inside nodules. Horizontal gene transfer has potential to confer immediate de novo adaptations to stress. We used comparative genomics of high quality de novo assemblies to identify structural differences in the genomes of nitrogen-fixing rhizobia that were isolated from a mercury (Hg) mine site that show high variation in their tolerance to Hg. Results Our analyses identified multiple structurally conserved merA homologs in the genomes of Sinorhizobium medicae and Rhizobium leguminosarum but only the strains that possessed a Mer operon exhibited 10-fold increased tolerance to Hg. RNAseq analysis revealed nearly all genes in the Mer operon were significantly up-regulated in response to Hg stress in free-living conditions and in nodules. In both free-living and nodule environments, we found the Hg-tolerant strains with a Mer operon exhibited the fewest number of differentially expressed genes (DEGs) in the genome, indicating a rapid and efficient detoxification of Hg from the cells that reduced general stress responses to the Hg-treatment. Expression changes in S. medicae while in bacteroids showed that both rhizobia strain and host-plant tolerance affected the number of DEGs. Aside from Mer operon genes, nif genes which are involved in nitrogenase activity in S. medicae showed significant up-regulation in the most Hg-tolerant strain while inside the most Hg-accumulating host-plant. Transfer of a plasmid containing the Mer operon from the most tolerant strain to low-tolerant strains resulted in an immediate increase in Hg tolerance, indicating that the Mer operon is able to confer hyper tolerance to Hg. Conclusions Mer operons have not been previously reported in nitrogen-fixing rhizobia. This study demonstrates a pivotal role of the Mer operon in effective mercury detoxification and hypertolerance in nitrogen-fixing rhizobia. This finding has major implications not only for soil bioremediation, but also host plants growing in mercury contaminated soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Gene content evolution in the arthropods

Background: Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Results: Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. Conclusions: These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.

Arthropods↗
DOE OSTI2020

RRNPP-type quorum-sensing systems regulate solvent formation, sporulation and cell motility in Clostridium saccharoperbutylacetonicum

Abstract Background Clostridium saccharoperbutylacetonicum N1-4 (HMT) is a strictly anaerobic, spore-forming Gram-positive bacterium capable of hyper-butanol production through the well-known acetone–butanol–ethanol fermentation process. Recently, five putative RRNPP-type QSSs (here designated as QSS1 to QSS5) were predicted in this bacterial strain, each of which comprises a putative RRNPP-type regulator (QssR1 to QssR5) and a cognate signaling peptide precursor (QssP1 to QssP5). In addition, both proteins are encoded by the same operon. The functions of these multiple RRNPP-type QSSs are unknown. Results To elucidate the function of multiple RRNPP-type QSSs as related to cell metabolism and solvent production in N1-4 (HMT), we constructed qssR -deficient mutants ΔR1, ΔR2, ΔR3 and ΔR5 through gene deletion using CRISPR–Cas9 and N1-4-dcas9-R4 (with the QssR4 expression suppressed using CRISPR–dCas9). We also constructed complementation strains by overexpressing the corresponding regulator gene. Based on systematic characterization, results indicate that QSS1, QSS2, QSS3, and QSS5 positively regulate the sol operon expression and thus solvent production, but they likely negatively regulate cell motility. Consequently, QSS4 might not directly regulate solvent production, but positively affect cell migration. In addition, QSS3 and QSS5 appear to positively regulate sporulation efficiency. Conclusions Our study provides the first insights into the roles of multiple RRNPP-type QSSs of C. saccharoperbutylacetonicum for the regulation of solvent production, cell motility, and sporulation. Results of this study expand our knowledge of how multiple paralogous QSSs are involved in the regulation of essential bacterial metabolism pathways.

09 BIOMASS FUELS↗
DOE OSTI2024

Data for Harnessing the Potential of Oilcane Waste Mud for Recovering Biobased Waxes

Oilcane is an engineered sugarcane with the ability to hyper-accumulate vegetative lipids. It is processed to obtain juice and bagasse as a potential substrate for the production of biofuels and biochemicals. The juice comprises solid particles that are separated as waste mud before the fermentation of the juice. In this study, the oilcane waste mud (OWM) generated from 1000 liters of oilcane juice was quantified and evaluated as a potential resource for recovering biobased waxes. Hexane and ethyl acetate were evaluated as two different solvents for extracting waxes from OWM followed by its purification using acetone. The extracted biobased wax samples were characterized for their chemical and thermal profiles which were then compared with commercial natural waxes. Detailed mass balance shows that 53.6 ± 2.6 kg (dry basis) of solid OWM gets generated upon processing 1000 L (~1068 kg) of oilcane juice. Hexane and ethyl acetate led to a crude wax yield of 25.6 ± 0.2% and 16.6 ± 0.4% (wt/wt, dry basis) respectively from OWM at the end of 8 h. The relative purification of the wax samples was reported in the range of 58%–65% (wt/wt). The purified OWM wax has a melting point of 74.7°C. The waste mud was valorized as a source of biobased waxes with characteristic chemical and thermal profiles comparable to commercial natural waxes (carnauba and beeswax). Considering the decline in the supply of petroleum wax in the future coupled with the switch to “greener” alternative products by consumers, OWM could be a valuable source of natural wax in the industrial sector reducing the dependence on petroleum waxes. Eventually, recovering biobased wax as a co-product from OWM would bring in an additional stream of revenue leading to the development of a zero-waste biorefinery based on bioenergy crops.

Biomass Analytics↗
DOE OSTI2022

Data for Bioprocessing, Recovery, and Mass Balance of Vegetative Lipids from Metabolically Engineered ‘Oilcane’ Demonstrates Its Potential as an Alternative Feedstock for Drop-In Fuel Production

Plant oils are increasingly in demand as renewable feedstocks for biodiesel and biochemicals. Currently, oilseeds are the primary source of plant oils. Although the vegetative tissues of plants express lipid metabolism pathways, they do not hyper-accumulate lipids. Elevated synthesis, storage, and accumulation of lipids in vegetative tissues have been achieved by metabolic engineering of sugarcane to produce “oilcane.” This study evaluates the potential of oilcane as a renewable feedstock for the co-production of lipids and fermentable sugars. Oilcane was grown under favorable climatic and field conditions in Florida (FLOC) as well as during an abbreviated growing season, outside its typical growing region, in Illinois (ILOC). The potential lipid yield of 0.35 tons/ha was projected from the hyperaccumulation of fatty acids in the stored vegetative biomass of FLOC, which is approaching the lipid yield of soybean (0.44 tons/ha). Processing of the vegetative tissues of oilcane recovered 0.20 tons/ha, which represents the recovery of 55% of the total lipids from FLOC. Chemical-free hydrothermal bioprocessing of ILOC and FLOC bagasse and leaves at 180 °C for 10 min prevented the degeneration of in situ plant lipids. This allowed the recovery of lipids at the end of the bioprocess with a major fraction of lipids remaining in the biomass residues after pretreatment and saccharification. Improvements through refined biomass processing, crop management, and metabolic engineering are expected to boost lipid yields and make oilcane a prime feedstock for the production of biodiesel.

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