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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Symbolic diagnostics to interpret and analyze neural network models

Embedded machine-learned models (EMLMs) have the promise to improve the predictive accuracy of engineering simulators in environments of national interest. EMLMs often comprise complex input-output maps (e.g., neural networks), which make them unamenable to rigorous analysis and generally difficult to interpret. In the face of decades of theory, this lack of interpretability is a significant barrier to building confidence in these models. This work outlines an approach to interpret EMLMs using sparse polynomial regression for comparison with theoretical understanding. To do so, we build on the concept of Locally Interpretable Model-agnostic Explanations (LIME) using physics-informed clustering, prototype selection, and library construction. While general, we demonstrate our method on tensor-basis neural networks used in Reynolds-Averaged Navier-Stokes simulations of hypersonic fluid flows. Results are presented for a simulated toy model and for direct numerical simulations (DNS) of turbulent flows over a flat plate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗
DOE OSTI2025

dCache CI/CD migration to Kubernetes

For over two decades, the dCache project has provided open-source to satisfy ever-more demanding storage requirements. More than 80 sites worldwide rely on dCache to provide services for LHC experiments, Belle-II, Eu- XFEL, and others. This can be achieved only with a well-established process from a whiteboard, where ideas are created through development, packaging, and testing. The project’s build and test infrastructure is based on Jenkins CI and a set of virtual machines. This infrastructure is maintained by dCache developers. With the introduction of the DESY-central Gitlab server, the developers have started migrating from VM-based testing to container-based deployments in the onsite Kubernetes cluster. As a result, we have packaged dCache containers and Helm charts that can be used by other sites to reproduce our test and build steps quickly or to evaluate new releases on their pre-production systems and, eventually, become a standard model of dCache deployment at the sites. This paper describes the challenges we have faced, the techniques we used to solve them, and the issues that still need to be addressed.

Mkrtchyan, Tigran [DESY]↗
DOE OSTI2024

Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics↗
DOE OSTI2026

An analytic approximation to the covariance between pre- and post-reconstruction galaxy two-point statistics

We present a simple analytic approximation for the covariance between pre-reconstruction galaxy power spectrum measurements and post-reconstruction two-point correlation functions. This cross-covariance is essential for joint analyses that combine full-shape clustering information with baryon acoustic oscillation (BAO) measurements, as commonly performed in modern spectroscopic surveys. Our model builds on the disconnected contribution to the covariance and accounts for the damping of correlations due to the BAO reconstruction process. We validate our analytic prescription against numerical simulations from the Dark Energy Spectroscopic Instrument (DESI), testing both idealized cubic geometries and realistic survey configurations including complex footprints and fiber assignment effects. Despite neglecting survey window functions in the analytic calculation, we find excellent agreement with simulation-based covariances and demonstrate that cosmological parameter constraints are virtually unchanged when using our approximation. Our results show that the pre-post cross-covariance is sufficiently small that even approximate treatments are adequate for cosmological inference, opening a pathway toward fully analytic covariance matrices for next-generation galaxy surveys.

baryon acoustic oscillations↗
DOE OSTI2022

Genotype–environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Abstract Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush ( Catharus guttatus ), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ternary aromatic and anti-aromatic clusters derived from the hypho species [Sn 2 Sb 5 ] 3-

Heterometallic clusters have attracted broad interests in the synthetic chemistry due to their various coordination modes and potential applications in heterogeneous catalysis. Here we report the synthesis, experimental, and theoretical characterizations of four ternary clusters ([M 2 (CO) 6 Sn 2 Sb 5 ] 3- (M = Cr, Mo), and [(MSn 2 Sb 5 ) 2 ] 4- , (M = Cu, Ag)) in the process of capturing the hypho - [Sn 2 Sb 5 ] 3- in ethylenediamine (en) solution. We show that the coordination of the binary anion to transition-metal ions or fragments provides additional stabilization due to the formation of locally σ-aromatic units, producing a spherical aromatic shielding region in the cages. While in the case of [Mo 2 (CO) 6 Sn 2 Sb 5 ] 3- stabilization arises from locally σ-aromatic three-centre and five-centre two-electron bonds, aromatic islands in [(AgSn 2 Sb 5 ) 2 ] 4- and [(CuSn 2 Sb 5 ) 2 ] 4- render them globally antiaromatic. This work describes the coordination chemistry of the versatile building block [Sn 2 Sb 5 ] 3- , thus providing conceptual advances in the field of metal-metal bonding in clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Dependence of Olefin Hydrogenation and Isomerization Rates on Zirconium Metal–Organic Framework Structure

Zirconium metal–organic frameworks (Zr-MOFs) are a structurally diverse and well-defined class of materials studied in heterogeneous catalysis. Previously, we showed that partial dehydration of the Zr 6 O 8 node in NU-1000 results in heterolytic H 2 cleavage over adjacent Lewis acid and base sites, leading to catalytic conversion of 1-butene. In this work, given the ubiquity of the Zr 6 O 8 node as a secondary building unit (SBU) in Zr-MOFs, with many different potential MOF topologies and capping ligands surrounding the cluster, we study the influence of thermal pretreatments and MOF topology (MOF-808, NU-1000, UiO-66, and NU-1000-NDC) on the activity of the Zr 6 O 8 cluster for H 2 activation and 1-butene hydrogenation and isomerization. Diffuse reflectance IR in the presence of H 2 and pyridine shows that both thermal pretreatment and MOF topology affect the Brønsted acidity of protons generated from H 2 activation and their resulting activity for olefin conversion. High isomerization activity of dehydrated NU-1000 is correlated with the formation of μ 3 OH species after H 2 activation. Additionally, catalytic studies show that the geometry of open coordination sites on individual Zr 6 O 8 nodes influences butene hydrogenation. For this reason, MOF-808 gives anomalously low hydrogenation activity, despite its relatively high total number of open coordination sites, as calculated either from its crystal structure or from NH 3 adsorption. Furthermore, these results reiterate the importance of pretreatment in defining MOF catalytic activity and demonstrate that MOF topology, outside of simply affecting node accessibility, influences reactivity at individual nodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Charliecloud 101

This workshop will provide participants with background and hands-on experience to use basic containers for HPC applications. We will discuss what containers are, why they matter for HPC, and how they work. We’ll give an overview of Charliecloud, the unprivileged container solution from HPC Division, and walk participants through installing it on their own compute resource. Participants will build toy containers and a real HPC application, and then run them in parallel on an HPC Division cluster. This will be a highly interactive workshop with lots of Q&A.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS2012

Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers-to-classifiers. The new capability has the potential to greatly expand the in situ analysis abilities of sensor networks. Classifiers seeking to categorize incoming data into different types of events can operate in tandem with clusterers that are sensitive to the occurrence of new kinds of events not known to the classifiers. In contrast to current approaches that treat these operations as independent components, a hybrid collaborative learning system can enable them to learn from each other.

Wagstaff, Kiri L.↗
DOE OSTI2020

Phylogenomic analysis of 589 metagenome-assembled genomes encompassing all major prokaryotic lineages from the gut of higher termites

“Higher” termites have been able to colonize all tropical and subtropical regions because of their ability to digest lignocellulose with the aid of their prokaryotic gut microbiota. Over the last decade, numerous studies based on 16S rRNA gene amplicon libraries have largely described both the taxonomy and structure of the prokaryotic communities associated with termite guts. Host diet and microenvironmental conditions have emerged as the main factors structuring the microbial assemblages in the different gut compartments. Additionally, these molecular inventories have revealed the existence of termite-specific clusters that indicate coevolutionary processes in numerous prokaryotic lineages. However, for lack of representative isolates, the functional role of most lineages remains unclear. We reconstructed 589 metagenome-assembled genomes (MAGs) from the different gut compartments of eight higher termite species that encompass 17 prokaryotic phyla. By iteratively building genome trees for each clade, we significantly improved the initial automated assignment, frequently up to the genus level. We recovered MAGs from most of the termite-specific clusters in the radiation of, for example, Planctomycetes, Fibrobacteres, Bacteroidetes, Euryarchaeota, Bathyarchaeota, Spirochaetes, Saccharibacteria, and Firmicutes, which to date contained only few or no representative genomes. Moreover, the MAGs included abundant members of the termite gut microbiota. This dataset represents the largest genomic resource for arthropod-associated microorganisms available to date and contributes substantially to populating the tree of life. More importantly, it provides a backbone for studying the metabolic potential of the termite gut microbiota, including the key members involved in carbon and nitrogen biogeochemical cycles, and important clues that may help cultivating representatives of these understudied clades.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

De novo protein design of photochemical reaction centers

Abstract Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here, we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Aerosol Models for the CALIPSO Lidar Inversion Algorithms

We use measurements and models to develop aerosol models for use in the inversion algorithms for the Cloud Aerosol Lidar and Imager Pathfinder Spaceborne Observations (CALIPSO). Radiance measurements and inversions of the AErosol RObotic NETwork (AERONET1, 2) are used to group global atmospheric aerosols using optical and microphysical parameters. This study uses more than 105 records of radiance measurements, aerosol size distributions, and complex refractive indices to generate the optical properties of the aerosol at more 200 sites worldwide. These properties together with the radiance measurements are then classified using classical clustering methods to group the sites according to the type of aerosol with the greatest frequency of occurrence at each site. Six significant clusters are identified: desert dust, biomass burning, urban industrial pollution, rural background, marine, and dirty pollution. Three of these are used in the CALIPSO aerosol models to characterize desert dust, biomass burning, and polluted continental aerosols. The CALIPSO aerosol model also uses the coarse mode of desert dust and the fine mode of biomass burning to build a polluted dust model. For marine aerosol, the CALIPSO aerosol model uses measurements from the SEAS experiment 3. In addition to categorizing the aerosol types, the cluster analysis provides all the column optical and microphysical properties for each cluster.

Omar, Ali H.↗
DOE OSTI2026

Inference of the linear matter power spectrum at z = 0 using DESI DR1 Full-Shape data

Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D linear matter power spectrum at redshift z = 0 using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the ΛCDM model, and compare it to the result assuming the w 0 w a CDM model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. Implementation of the EFT approach improves the modelling of the galaxy power spectrum, providing a more robust consistency test of the assumed cosmological model. By casting both CMB and galaxy clustering observations, spanning distinct redshift regimes, into k-space, we can identify discrepancies between the datasets of different redshifts, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with ΛCDM, this work extends the analysis with higher-quality data to further test the expansion histories of both ΛCDM and w 0 w a CDM. Our findings show that both ΛCDM and w 0 w a CDM provide consistent fits to the linear matter power spectrum recovered from DESI DR1 data.

cosmological parameters from LSS↗
DOE OSTI2023

Multi–Step Nucleation of a Crystalline Silicate Framework via a Structurally Precise Prenucleation Cluster

Hierarchical nucleation pathways are ubiquitous in the synthesis of minerals and materials. In the case of zeolites and metal–organic frameworks, pre-organized multi-ion “secondary building units” (SBUs) have been proposed as fundamental building blocks. However, detailing the progress of multi-step reaction mechanisms from monomeric species to stable crystals and defining the structures of the SBUs remains an unmet challenge. Furthermore, combining in situ nuclear magnetic resonance, small-angle X-ray scattering, and atomic force microscopy, we show that crystallization of the framework silicate, cyclosilicate hydrate, occurs through an assembly of cubic octameric Q 3 8 polyanions formed through cross-linking and polymerization of smaller silicate monomers and other oligomers. These Q 3 8 are stabilized by hydrogen bonds with surrounding H 2 O and tetramethylammonium ions (TMA + ). When Q 3 8 levels reach a threshold of ≈32 % of the total silicate species, nucleation occurs. Further growth proceeds through the incorporation of [(TMA) x (Q 3 8 )•n H 2 O] (x–8) clathrate complexes into step edges on the crystals.

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

What Makes a Bifurcase? Insights from a NADH-Dependent Reduced Ferredoxin: NADP+ Oxidoreductase (Nfn) and Homologs

NADH-dependent ferredoxin:NADP+ oxidoreductases (Nfn) is an enzyme family that engage in flavin-based electron bifurcation (FBEB), a mode of energy conservation utilized by life. The protein comprises one large (NfnL) and one small (NfnS) subunits. Thermoanaerobacterium sacchaloryticum (Tsac) is an anaerobic thermophilic bacterium that - with known involvement of Tsac Nfn - can produce ethanol in high, commercially viable concentrations. We sought to investigate the activity and energetic landscape of Tsac Nfn to determine how the enzyme effectuates FBEB. Tsac NfnS, NfnL, and the partner ferredoxin (Tsac Fd) were recombinantly expressed, purified, and reconstituted with iron-sulfur cluster and FAD cofactors. Electron paramagnetic resonance (EPR) was utilized for all proteins. Spectroelectrochemistry was performed with NfnL. Square-wave voltammetry was conducted on NfnL and Fd. Spectrophotometric activity was assayed for NfnL with or without NfnS. Our group continues to investigate the Nfn from Pyrococcus furiosus (Pf Nfn). Unlike Pf NfnS, Tsac NfnS can be stably expressed, purified, and reconstituted in the absence of its partner NfnL, allowing for this subunit to be characterized separately. The energetic profile of FBEB in Tsac Nfn is overall similar to that of Pf NfnL, with some differences: (1) the proximal cluster is at a lower potential (-780 mV vs -711), (2) the bifurcating FAD is at a higher potential (-406 mV vs -436 mV), and (3) Tsac Fd has two [4Fe-4S] clusters at -550 and -410 mV, unlike Pf Fd with a single cluster at approximately 400 mV. Activity assays indicate that the two enzymes perform FBEB in a similar way. Our work continues to build upon the new field of FBEB by demonstrating that the energetic landscape between distantly related archael (Pf) and bacterial (Tsac Nfn) are largely similar. This equips us to understand design principles for FBEB, allowing us to modulate the process in vivo for specific metabolic outcomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Communication: A mean field platform for excited state quantum chemistry

We present a mean field theory for excited states that is broadly analogous to ground state Hartree-Fock theory. Like Hartree-Fock, our approach is deterministic, state-specific, applies a variational principle to a minimally correlated ansatz, produces energy stationary points, relaxes the orbital basis, has a Fock-build cost-scaling, and can serve as the foundation for correlation methods such as perturbation theory and coupled cluster theory. To emphasize this last point, we pair our mean field approach with an excited state analog of second order Møller-Plesset theory and demonstrate that in water, formaldehyde, neon, and stretched lithium fluoride, the resulting accuracy far exceeds that of configuration interaction singles and rivals that of equation of motion coupled cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗