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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

OC6 Project Phase IV: Validation of Numerical Models for Novel Floating Offshore Wind Support Structures

The fourth phase of the Offshore Code Comparison, Collaboration, Continued, with Correlation and unCertainty (OC6) aims to assess the ability of the tools to model a novel floating wind design. The design that was selected for this project is the TetraSpar designed by Stiesdal Offshore Technologies. The platform is a unique design that features a spar like stability with a very low center of gravity, but does not require deep-water ports. This combination is achieved with a system made of two separate steel structures, a hull at the water’s surface that supports the wind turbine tower, and a keel that is suspended below the main body. This lower keel has a very high density and drives the total platform’s low center of gravity. Scaled model tests of the TetraSpar design were performed in 2018-2019 by the University of Maine. The tests were performed with 1:43 Froude scaling. The data collected in the model tests provide a detailed description of the response of the platform in various controlled and relatively well understood conditions. Comparison with these data provides a good opportunity for validation of numerical models. The OC6 Phase IV work will focus on the specific parameters used in these scaled model tests. The load cases (LC) considered in this project are as follows: LC 1.X - Equilibrium and Static Offset Tests LC 2.X - Platform Free Decays LC 3.X - Turbine Thrust (Wind Only) LC 4.X - Regular and Irregular Waves (Wave only) LC 5.X - Combined Wind and Wave Loading

17 WIND ENERGY↗
DOE OSTI2023

Non-reactive facet specific adsorption as a route to remediation of chlorinated organic contaminants

The present work quantifies metal-contaminant interactions between palladium substrates and three salient chlorinated organic contaminants, namely trichloroethylene 1,3,5-trichlorobenzene (TCB), and 3,3′,4,4′-tetrachlorobiphenyl (PCB77). Given that Pd is one of the conventional catalytically active materials known for contaminant removal, maximizing catalytic efficiency through optimal adsorption dynamics reduces the cost of remediation of contaminants that are persistent water pollutants chronically affecting public health. Adsorption efficiency analyses from all-atom molecular dynamics (MD) simulations advance the understanding of reaction mechanisms available from density functional theory (DFT) calculations to an extractable feature scale that can fit the parametric design of supported metal catalytic systems and feed into high throughput catalyst selection. Data on residence time, site-specific adsorption, binding energies, packing geometries, orientation profiles, and the effect of adsorbate size show the anomalous behaviour of organic contaminant adsorption on the undercoordinated {110} surface as compared to the {111} and {100} surfaces. The intermolecular interaction within contaminants from molecular dynamics simulation exhibits refreshing results than ordinary single molecule density functional theory calculation. Since complete adsorption and dechlorination is an essential step for chlorinated organic contaminant remediation pathways, the presented profiles provide essential information for designing efficient remediation systems through facet-controlled palladium nanoparticles.

Guo, Hao↗
DOE OSTI2022

BASS. XXIV. The BASS DR2 Spectroscopic Line Measurements and AGN Demographics

We present the second catalog and data release of optical spectral line measurements and active galactic nucleus (AGN) demographics of the BAT AGN Spectroscopic Survey, which focuses on the Swift-BAT hard X-ray detected AGNs. We use spectra from dedicated campaigns and publicly available archives to investigate spectral properties of most of the AGNs listed in the 70 month Swift-BAT all-sky catalog; specifically, 743 of the 746 unbeamed and unlensed AGNs (99.6%). We find a good correspondence between the optical emission line widths and the hydrogen column density distributions using the X-ray spectra, with a clear dichotomy of AGN types for N H = 10 22 cm –2 . Based on optical emission-line diagnostics, we show that 48%–75% of BAT AGNs are classified as Seyfert, depending on the choice of emission lines used in the diagnostics. The fraction of objects with upper limits on line emission varies from 6% to 20%. Roughly 4% of the BAT AGNs have lines too weak to be placed on the most commonly used diagnostic diagram, [O iii ]λ5007/Hβ versus [N ii ]λ6584/Hα, despite the high signal-to-noise ratio of their spectra. This value increases to 35% in the [O iii ]λ5007/[O ii ]λ3727 diagram, owing to difficulties in line detection. Compared to optically selected narrow-line AGNs in the Sloan Digital Sky Survey, the BAT narrow-line AGNs have a higher rate of reddening/extinction, with Hα/Hβ > 5 (~36%), indicating that hard X-ray selection more effectively detects obscured AGNs from the underlying AGN population. Finally, we present a subpopulation of AGNs that feature complex broad lines (34%, 250/743) or double-peaked narrow emission lines (2%, 17/743).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spectrally selective fundamental core mode suppression in optical fibre containing absorbing rods

The feasibility of making a wavelength-selective fibre filter using fibre with absorbing rods in its silica cladding has been demonstrated theoretically for the first time. The technique described in this paper is of great practical interest for designing fibre lasers and amplifiers emitting at wavelengths where lasing is impeded by the presence of more energetically favourable radiative transitions in the active medium. In addition, the approach proposed here can be used for stimulated Raman scattering suppression. The unique feature of the fundamental core mode suppression mechanism examined is that there is a (bending) controlled spectral width of a region where excess losses are produced. (selection of papers presented at the international workshop on fibre lasers (20 – 24 September 2020, Novosibirsk))

36 MATERIALS SCIENCE↗
DOE OSTI2025

Introducing metal–sulfur active sites in metal–organic frameworks via post-synthetic modification for hydrogenation catalysis

Metal–sulfur active sites play a central role in catalytic processes such as hydrogenation and dehydrogenation, yet the majority of active sites in these compounds reside on the surfaces and edges of catalyst particles, limiting overall efficiency. Here we present a strategy to embed metal–sulfur active sites into metal–organic frameworks (MOFs) by converting bridging or terminal chloride ligands into hydroxide and subsequently into sulfide groups through post-synthetic modification. We apply this method to two representative MOF families: one featuring one-dimensional metal–chloride chains and another containing discrete multinuclear metal clusters. Crystallographic and spectroscopic analyses confirm structural integrity and sulfide incorporation, and the transformation is monitored by in situ total scattering methods. The sulfided MOFs display enhanced catalytic activity in the selective hydrogenation of nitroarenes using molecular hydrogen. Density functional theory calculations indicate that sulfur incorporation promotes homolytic metal–ligand bond cleavage and facilitates H 2 activation. This work establishes an approach to construct MOFs featuring accessible metal–sulfide sites.

Catalyst synthesis↗
DOE OSTI2023

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

Among many agricultural practices proposed to cut carbon emissions in the next 30 years is the deposition of carbon in soils as plant matter. Adding rooting traits as part of a sequestration strategy would result in significantly increased carbon sequestration. Integrating these traits into production agriculture requires a belowground phenotyping method compatible with high-throughput breeding (i.e., rapid, inexpensive, reliable, and non-destructive). However, methods that fulfill these criteria currently do not exist. We hypothesized that ground-penetrating radar (GPR) could fill this need as a phenotypic selection tool. In this study, we employed a prototype GPR antenna array to scan and discriminate the root and rhizome mass of the perennial sorghum hybrid PSH09TX15. B-scan level time/discrete frequency analyses using continuous wavelet transform were utilized to extract features of interest that could be correlated to the biomass of the subsurface roots and rhizome. Time frequency analysis yielded strong correlations between radar features and belowground biomass (max R −0.91 for roots and −0.78 rhizomes, respectively) These results demonstrate that continued refinement of GPR data analysis workflows should yield an applicable phenotyping tool for breeding efforts in contexts where selection is otherwise impractical.

Wolfe, Matthew↗
DOE OSTI2020

Determination of latent dimensionality in international trade flow

Currently, high-dimensional data is ubiquitous in data science, which necessitates the development of techniques to decompose and interpret such multidimensional (aka tensor) datasets. Finding a low dimensional representation of the data, that is, its inherent structure, is one of the approaches that can serve to understand the dynamics of low dimensional latent features hidden in the data. Moreover, decomposition methods with non-negative constraints are shown to extract more insightful factors. Nonnegative RESCAL is one such technique, particularly well suited to analyze self-relational data, such as dynamic networks found in international trade flows. Particularly, non-negative RESCAL computes a low dimensional tensor representation by finding the latent space containing multiple modalities. Furthermore, estimating the dimensionality of this latent space is crucial for extracting meaningful latent features. Here, to determine the dimensionality of the latent space with non-negative RESCAL, we propose a latent dimension determination method which is based on clustering of the solutions of multiple realizations of non-negative RESCAL decompositions. We demonstrate the performance of our model selection method on synthetic data. We then apply our method to decompose a network of international trade flows data from International Monetary Fund and shows that with a correct latent dimension determination, the resulting features are able to capture relevant empirical facts from economic literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Near-Gapless Penicillium fuscoglaucum Genome Enables the Discovery of Lifestyle Features as an Emerging Post-Harvest Phytopathogen

Penicillium spp. occupy many diverse biological niches that include plant pathogens, opportunistic human pathogens, saprophytes, indoor air contaminants, and those selected specifically for industrial applications to produce secondary metabolites and lifesaving antibiotics. Recent phylogenetic studies have established Penicillium fuscoglaucum as a synonym for Penicillium commune, which is an indoor air contaminant and toxin producer and can infect apple fruit during storage. During routine culturing on selective media in the lab, we obtained an isolate of P. fuscoglaucum Pf_T2 and sequenced its genome. The Pf_T2 genome is far superior to available genomic resources for the species. Our assembly exhibits a length of 35.1 Mb, a BUSCO score of 97.9% complete, and consists of five scaffolds/contigs representing the four expected chromosomes. It was determined that the Pf_T2 genome was colinear with a type specimen P. fuscoglaucum and contained a lineage-specific, intact cyclopiazonic acid (CPA) gene cluster. For comparison, a highly virulent postharvest apple pathogen, P. expansum strain TDL 12.1, was included and showed a similar growth pattern in culture to our Pf_T2 isolate but was far more aggressive in apple fruit than P. fuscoglaucum. The genome of Pf_T2 serves as a major improvement over existing resources, has superior annotation, and can inform forthcoming omics-based work and functional genetic studies to probe secondary metabolite production and disparities in aggressiveness during apple fruit decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bipolar Membrane Capacitive Deionization for the Selective Capture of Lithium Ions from Brines and Conversion to Lithium Hydroxide

Meeting the increasing demand for lithium in vehicle electrification and renewable energy storage requires innovations in lithium-ion (Li + ) separations. Traditional solar evaporation methods for lithium recovery are slow and consume tremendous volumes of water and secondary chemicals (acids and bases). This study introduces a bipolar membrane capacitive deionization (BPM-CDI) unit for direct lithium extraction and LiOH production without the external addition of acids and bases. Utilizing de-lithiated lithium-iron-phosphate (LFP) coated carbon cloth electrodes, the BPM-CDI unit demonstrates selective Li + capture over competing ions. Molecular dynamics simulations and H-cell experiments elucidate pH inversion mechanisms during Li + release, yielding LiOH. The BPM-CDI platform efficiently removes Li + from synthetic brines featuring 8x higher Mg 2+ concentrations (200 ppm Mg 2+ ) and 26x higher Na + concentrations (682 ppm Na + ), achieving a LiOH concentration of 124 ppm (36 ppm Li + ) after 8 cycles of recirculation. Post-mortem analysis confirms electrode integrity and stability. BPM-CDI integrated with selective electrodes is a promising electrochemical separation-reactor platform for lithium recovery while producing LiOH.

Kulkarni, Tanmay↗
DOE OSTI2022

Factorization of Binary Matrices: Rank Relations, Uniqueness and Model Selection of Boolean Decomposition

The application of binary matrices are numerous. Representing a matrix as a mixture of a small collection of latent vectors via low-rank decomposition is often seen as an advantageous method to interpret and analyze data. In this work, we examine the factorizations of binary matrices using standard arithmetic (real and nonnegative) and logical operations (Boolean and $\mathbb{Z}$ 2 ). We examine the relationships between the different ranks, and discuss when factorization is unique. In particular, we characterize when a Boolean factorization X = W$\land$H has a unique W, a unique H (for a fixed W), and when both W and H are unique, given a rank constraint. We introduce a method for robust Boolean model selection, called BMFk, and show on numerical examples that BMFk not only accurately determines the correct number of Boolean latent features but reconstruct the pre-determined factors accurately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Solar Thermal Energy Planner (STEP 1): A New Decision Support Tool for Solar Industrial Process Heat Applications

Solar thermal technologies are a promising technology to supply low-cost thermal energy to industrial processes, but there are often significant barriers to entry to industrial owners considering these technologies for their energy demands. To overcome this barrier and convey economic value to customers, NREL and Sandia National Laboratories developed Solar Thermal Energy Planner (STEP 1), a new web-based decision support tool for solar industrial process heat systems. At SolarPACES 2024, the STEP 1 tool was still under development; progress, methodologies, and a preliminary case study was presented. With the STEP 1 tool launch in May 2025, in this work, the initial version of the full public tool will be presented with demonstrations of its capabilities using a few case studies. First, the user's process heat needs such as location, process media (e.g., steam, air), process temperature, land availability, electricity and fuel costs, among other parameters. STEP 1 features a mapping interface that allows users to draw land and roof boundaries. The process media and temperature inform technology selection criteria modules that determine the appropriate solar thermal collection technologies, as well as congruent heat transfer media (e.g., hot water, oil, salt). Once the solar thermal technology selected, its nominal thermal production for the given site is characterized using NREL's System Advisor Model (SAM). Then, a modified version of NREL's REopt optimal sizing and dispatch optimization tool determines cost-optimal sizing. Within minutes, the user receives the results of the technoeconomics analysis, including the size and performance of the cost-optimal solar-plus-storage system. The cost of the system is compared to business-as-usual (e.g., an existing, standalone natural gas boiler). Users can download key results to store for sensitivity analyses. Examples of flat plate collector, parabolic trough, and molten salt tower applications with and without PV hybridization for different industrial facility types are presented in this work. The STEP 1 tool aims to reduce barriers to the adoption of solar heating solutions stemming from a lack of familiarity and technical background with solar system design options and costs among industry stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2022

In Hot Water! The Challenges and Barriers of Decarbonizing Water Heating in Multifamily Buildings: Preprint

Domestic hot water heating is responsible for 32% of the total energy consumption in multifamily buildings and offers a significant decarbonization opportunity. An extensive market assessment was conducted to understand and document key technical and economic barriers to electrification of domestic water heating in multifamily buildings throughout the U.S. Through the program, 77 interviews were conducted to understand key market drivers and technical challenges associated with electrification of water heating systems in both retrofit and new construction scenarios. Interviewees encompassed a wide range of stakeholders in the ecosystem surrounding water heating systems, including suppliers, manufacturers, designers, owners, utilities, and developers. This paper documents key interview takeaways, including an extensive list of market barriers, technical challenges, and sought-after technology attributes that can inform pertinent design criteria for electric water heating research, development, and deployment efforts. Among economics and energy efficiency features, interviewees overwhelmingly alluded to space constraints, cold air exhaust, and lack of clear guidance regarding distributed versus centralized design selections as key challenges associated with mass adoption of electric water heating. Owners and developers seek systems with minimal footprint, which maximize rentable space and profits. Moreover, distributed heat pump solutions should balance ducting costs that mitigate cold exhaust entrainment into conditioned zones. Lastly, the market needs clear guidance regarding the selection of distributed versus central electric hot water systems.

challenges of water heating electrification↗
DOE OSTI2025

NREL Tools and Partnership Opportunities for Rural Electric Cooperatives in the United States

Rural electric cooperatives provide power to more than 42 million Americans, many of whom reside in rural and persistent poverty counties. As these co-ops invest in modernizing their energy infrastructure, they play a crucial role in ensuring affordable electricity, enhancing system resilience, and supporting economic development in their communities. To aid in this transition, NREL offers a suite of tools and partnership opportunities designed to help co-ops address evolving resource, affordability, and reliability needs. This factsheet covers already published content on select NREL tools and their most relevant applications for co-op decision-making and investment planning. Additionally, it features case studies demonstrating how rural co-ops can collaborate with NREL to advance both energy and economic development goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

DRiFT - Release 1.0.0 Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP [1], and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator [2], gas [3], and semiconductor features [4], the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts [5, 6]. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

DRiFT - Release 1.1.1: Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator, gas, and semiconductor features, the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A robust and multifunctional calcium coordination polymer as a selective fluorescent sensor for acetone and iron (+3) and as a tunable proton conductor

A multifunctional calcium coordination polymer (Ca-CP) formulated as [(CH 3 ) 2 NH 2 ][Ca(Me 2 tcpbH)(H 2 O)] (1) has been synthesized and characterized. Compound 1 features a robust and novel three-dimensional (3D) network with cage-like cavities. The high thermal and moisture stability of the title compound makes it a good candidate for possible environment or energy related applications. Fluorescence (FL) studies demonstrate that 1 shows emission with a maximum at 350 nm under 270 nm excitation. The title compound acts as a selective and sensitive fluorescent sensor for the detection of acetone and Fe 3+ ions at low concentrations. The FL intensity quenching percentage and the concentration ratio of Fe 3+ /Fe 2+ showed a linear relation with a Fe 3+ concentration as low as 50 μM in Fe 2+ aqueous solutions, offering an easy way to probe the extent of Fe 2+ oxidation. Moreover, due to the relatively high hydration character of Ca 2+ , the terminal water molecules and undeprotonated carboxylate groups form a strong hydrogen-bonded network within the structure, facilitating its tunable proton conduction under various humidity and temperature conditions. The proton conducting mechanism has been investigated using PXRD, IR, and EA methods.

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

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2023

Microstructural evolution of rapidly solidified hypoeutectic Al 10Cu alloy during non-isothermal annealing transients induced by nano-second laser pulses

The evolution of characteristic nonequilibrium features presenting in morphologically distinct regions of rapid solidification (RS) microstructures in a hypoeutectic Al—10Cu (atomic %) in response to non-isothermal annealing transients has been studied by transmission electron microscopy (TEM). The capabilities of the Movie-Mode Dynamic TEM (MM-DTEM) instrument were used to expose select regions of the RS microstructure to sequences of rapid heating and cooling transients induced by nanosecond laser pulses while permitting in-situ observation. Partial melting, microstructural scale coarsening, morphological changes of the nonequilibrium features in the multi-phase RS microstructure, and solid-state phase transformation were observed. Heterogeneous nucleation of nanoscale θ-Al 2 Cu phase involved metastable supersaturated α-Al and the θ'-Al 2 Cu phases, establishing different sets of orientation relationships for the stable θ-Al 2 Cu and α-Al phases. Replacement of banded morphology grains that formed under conditions driven farthest from equilibrium by an equiaxed nanocrystalline structure comprised of α-Al phase, the primary solidification product, and an intergranular network of Al 2 Cu crystals has been attributed to local remelting. Here the experimental approach explored, permitted discovery of mechanistic details of location-specific transformation pathways activated in the multi-phase RS microstructure of hypoeutectic Al—Cu during subsequent nonisothermal transients.

36 MATERIALS SCIENCE↗