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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ~9 % and ~7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (~39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ~66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr –1 ) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Artificial neural networks estimate evapotranspiration for Miscanthus × giganteus as effectively as empirical model but with fewer inputs

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthu s × giganteus ( M . × giganteus ) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET. A combination of air temperature (T a ) and solar radiation (R s ) was chosen as inputs due to the highest R 2 for FFN (R 2 = 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only T a for NARX (R 2 = 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R 2 = 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The interplay of DNA repair context with target sequence predictably biases Cas9-generated mutations

Abstract Repair of double-stranded breaks generated by CRISPR/Cas9 is highly dependent on the flanking DNA sequence. To learn about interactions between DNA repair and target sequence, we measure frequencies of over 236,000 distinct Cas9-generated mutational outcomes at over 2800 synthetic target sequences in 18 DNA repair deficient mouse embryonic stem cells lines. We classify the outcomes in an unbiased way, finding a specialised role forPrkdc(DNA-PKcs protein) andPolmin creating 1 bp insertions matching the nucleotide on the protospacer-adjacent motif side of the break, a variable involvement ofNbnandPolqin the creation of different deletion outcomes, and uni-directional deletions dependent on both end-protection and end-resection. Using our dataset, we build predictive models of the mutagenic outcomes of Cas9 scission that outperform the current standards. This work improves our understanding of DNA repair gene function, and provides avenues for more precise modulation of Cas9-generated mutations.

Science & Technology - Other Topics↗
DOE OSTI2022

Understanding Phase and Interfacial Effects of Spall Fracture in Additively Manufactured Ti-5Al-5V-5Mo-3Cr

Additive manufactured Ti-5Al-5V-5Mo-3Cr (Ti-5553) is being considered as an AM repair material for engineering applications because of its superior strength properties compared to other titanium alloys. Here, we describe the failure mechanisms observed through computed tomography, electron backscatter diffraction (EBSD), and scanning electron microscopy (SEM) of spall damage as a result of tensile failure in as-built and annealed Ti-5553. We also investigate the phase stability in native powder, as-built and annealed Ti-5553 through diamond anvil cell (DAC) and ramp compression experiments. We then explore the effect of tensile loading on a sample containing an interface between a Ti-6Al-V4 (Ti-64) baseplate and additively manufactured Ti-5553 layer. Post-mortem materials characterization showed spallation occurred in regions of initial porosity and the interface provides a nucleation site for spall damage below the spall strength of Ti-5553. Preliminary peridynamics modeling of the dynamic experiments is described. Finally, we discuss further development of Stochastic Parallel PARticle Kinteic Simulator (SPPARKS) Monte Carlo (MC) capabilities to include the integration of alpha (α)-phase and microstructural simulations for this multiphase titanium alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evidence of Dirac Quantum Spin Liquid in YbZn 2⁢ GaO 5

The emergence of a quantum spin liquid (QSL), a state of matter that can result when electron spins are highly correlated but do not become ordered, has been the subject of a considerable body of research in condensed matter physics [1,2]. Spin liquid states have been proposed as hosts for high-temperature superconductivity [3] and can host topological properties with potential applications in quantum information science [4]. The excitations of most quantum spin liquids are not conventional spin waves but rather quasiparticles known as spinons, whose existence is well established experimentally only in one-dimensional systems; the unambiguous experimental realization of QSL behavior in higher dimensions remains challenging. Here, in this work, we investigate the novel compound $YbZn_{2}GaO_{5}$, which hosts an ideal triangular lattice of effective spin-1/2 moments with no detectable inherent chemical disorder. Thermodynamic and inelastic neutron scattering measurements performed on high-quality single crystal samples of $YbZn_{2}GaO_{5}$ exclude the possibility of long-range magnetic ordering down to 0.06 K, demonstrate a quadratic power law for the specific heat and reveal a continuum of magnetic excitations in parts of the Brillouin zone. Both low-temperature thermodynamics and inelastic neutron scattering spectra suggest that $YbZn_{2}GaO_{5}$ is a U(1) Dirac QSL with spinon excitations concentrated at certain points in the Brillouin zone. We advanced these results by performing additional specific heat measurements under finite fields, further confirming the theoretical expectations for a Dirac QSL on the triangular lattice of $YbZn_{2}GaO_{5}$.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Electron–Nuclear Dynamics Accompanying Proton-Coupled Electron Transfer

Although photoinduced proton-coupled electron transfer (PCET) plays an essential role in photosynthesis, a full understanding of the mechanism is still lacking due to the complex nonequilibrium dynamics arising from the strongly coupled electronic and nuclear degrees of freedom. Here we report the photoinduced PCET dynamics of a biomimetic model system investigated by means of transient IR and two-dimensional electronic–vibrational (2DEV) spectroscopies, IR spectroelectrochemistry (IRSEC), and calculations utilizing long-range-corrected hybrid density functionals. This collective experimental and theoretical effort provides a nuanced picture of the complicated dynamics and synergistic motions involved in photoinduced PCET. In particular, the evolution of the 2DEV line shape, which is highly sensitive to the mixing of vibronic states, is interpreted by accurate computational modeling of the charge separated state and is shown to represent a gradual change in electron density distribution associated with a dihedral twist that occurs on a 120 fs time scale.

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

Unraveling Reactivity Differences: Room-Temperature Ring-Opening Metathesis Polymerization (ROMP) versus Frontal ROMP

Here, in this study, we explore the distinct reactivity patterns between frontal ring-opening metathesis polymerization (FROMP) and room-temperature solventless ring-opening metathesis polymerization (ROMP). Despite their shared mechanism, we find that FROMP is less sensitive to inhibitor concentration than room-temperature ROMP. By increasing the initiator-to-monomer ratio for a fixed inhibitor/initiator quantity, we find reduction in the ROMP background reactivity at room temperature (i.e., increased resin pot life). At elevated temperatures where inhibitor dissociation prevails, accelerated frontal polymerization rates are observed because of the concentrated presence of the initiator. Surprisingly, the strategy of employing higher initiator loading enhances both pot life and front speeds, which leads to FROMP rates exceeding prior reported values by over 5 times. This counterintuitive behavior is attributed to an increase in the proximity of the inhibitor to the initiator within the bulk resin and to whether the temperature favors coordination or dissociation of the inhibitor. A rapid method was developed for assessing resin pot life, and a straightforward model for active initiator behavior was established. Modified resin systems enabled direct ink writing of robust thermoset structures at rates much faster than previously possible.

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

Vertical-Axis Wind Turbine Steady and Unsteady Aerodynamics for Curved Deforming Blades

Vertical-axis wind turbines’ simpler design and low center of gravity make them ideal for floating wind applications. However, efficient design optimization of floating systems requires fast and accurate models. Low-fidelity vertical-axis turbine aerodynamic models, including double multiple streamtube and actuator cylinder theory, were created during the 1980s. Commercial development of vertical-axis turbines all but ceased in the 1990s until around 2010 when interest resurged for floating applications. Despite the age of these models, the original assumptions (2-D, rigid, steady, straight bladed) have not been revisited in full. When the current low-fidelity formulations are applied to modern turbines in the unsteady domain, aerodynamic load errors nearing 50% are found, consistent with prior literature. However, a set of steady and unsteady modifications that remove the majority of error is identified, limiting it near 5%. This paper shows how to reformulate the steady models to allow for unsteady inputs including turbulence, deforming blades, and variable rotational speed. A new unsteady approximation that increases numerical speed by 5–10× is also presented. Combined, these modifications enable full-turbine unsteady simulations with accuracy comparable to higher-fidelity vortex methods, but over 5000× faster.

17 WIND ENERGY↗
DOE OSTI2021

Velocity-Space Hybridization of Direct Simulation Monte Carlo and a Quasi-Particle Boltzmann Solver

This paper presents a new method for modeling rarefied gas flows based on hybridization of direct simulation Monte Carlo (DSMC) and discrete velocity method (DVM)-based quasi-particle representations of the velocity distribution function. It is aimed at improving the resolution of the tails of the distribution function (compared with DSMC) and computational efficiency (compared with DVM). Details of the method, such as the collision algorithm and the particle merging scheme, are discussed. The hybrid approach is applied to the study of noise in a Maxwellian distribution, computation of electron-impact ionization rate coefficient, as well as numerical simulation of a supersonic Couette flow. The hybrid-based solver is compared with pure DSMC and DVM approaches in terms of accuracy, computational speed, and memory use. It is shown that such a hybrid approach can provide a lower computational cost than a pure DVM approach, while being able to retain accuracy in modeling high-velocity tails of the distribution function. For problems where trace species have a significant impact on the flow physics, the proposed method is shown to be capable of providing better computational efficiency and accuracy compared with standard fixed-weight DSMC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-Temperature Thermodynamics of Uranium from Ab Initio Modeling

We present high-temperature thermodynamic properties for uranium in its γ phase (γ-U) from first-principles, relativistic, and anharmonic theory. The results are compared to CALPHAD modeling. The ab initio electronic structure is obtained from density-functional theory (DFT) that includes spin–orbit coupling and an added self-consistent orbital-polarization (OP) mechanism for more accurate treatment of magnetism. The first-principles method is coupled to a lattice dynamics scheme that is used to model anharmonic lattice vibrations, namely, Self-Consistent Ab Initio Lattice Dynamics (SCAILD). The methodology can be summarized in the acronym DFT + OP + SCAILD. Upon thermal expansion, γ-U develops non-negligible magnetic moments that are included for the first time in thermodynamic theory. The all-electron DFT approach is shown to model γ-U better than the commonly used pseudopotential method. In addition to CALPHAD, DFT + OP + SCAILD thermodynamic properties are compared with other ab initio and semiempirical modeling and experiments. Our first-principles approach produces Gibbs free energy that is essentially identical to CALPHAD. The DFT + OP + SCAILD heat capacity is close to CALPHAD and most experimental data and is predicted to have a significant thermal dependence due to the electronic contribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Computationally Guided Discovery of Axis-Dependent Conduction Polarity in NaSnAs Crystals

Most electronic materials exhibit a single dominant charge carrier type, either holes or electrons, along all crystallographic directions. However, there are a small number of compounds, mostly metals, that exhibit simultaneous p-type and n-type conduction behavior along different crystallographic directions. We demonstrate that the experimental discovery of semiconductors with this axis-dependent conduction polarity can be facilitated by identifying a large anisotropy of either the electron or hole effective masses (m*) or both, providing the electron and hole masses dominate along different crystallographic directions. We calculated the layered semiconductor NaSnAs to have a lower electron m* in-plane than the cross-plane and a very large hole m* in-plane and small hole m* cross-plane. We established the growth of >3 mm-sized NaSnAs crystals via Sn flux and confirmed the band gap to be 0.65 eV, in agreement with theory. NaSnAs exhibits p-type thermopowers cross-plane and n-type thermopowers in-plane, confirming that the large anisotropy in the effective mass at the band edges is an excellent indicator for axis-dependent conduction polarity. Altogether, this work shows that the discovery of semiconductors with such a phenomenon can be accelerated by computationally evaluating the anisotropic curvatures of the band edges, paving the way for their future discovery and application.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

A2SD: Accelerating Scientific Innovation Through Autonomous Discovery Systems

The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.

Taufer, Michela [University of Tennessee, Knoxvill↗
DOE OSTI2020

Development and evaluation of a list mode neutron coincidence collar for spatial response measurements of fresh fuel assemblies

A traditional safeguards neutron coincidence counting system, the Neutron Coincidence Collar, has been modified to incorporate individual preamplifiers on each of its 18 3He tubes in active interrogation mode. When used with list mode data acquisition (LMDA) and analysis, a signal from each 3He tube can be recorded and analyzed to allow a spatial response measurement to be performed on an item based on count rate and 3He tube location within the system. The ultimate goal of this project is to demonstrate the capabilities of a list mode response matrix for the nondestructive assay of fresh nuclear fuel assemblies. To enable partial defect detection of fuel pin locations and absences within an assembly, the project aims to extend well-established correlated neutron analysis techniques on a preexisting Neutron Coincidence Collar by extracting a greater number of useful signatures from the system than are currently generated. LMDA, combined with the addition of multiple preamplifiers, facilitates this capability by increasing the number of simultaneous signals that can be measured; this allows an in-depth analysis of neutron coincidence events to determine a fissioning item’s location based on the measured doubles count rate in various channel logic coincidence combinations. All of this can be done from a single measurement pulse train in offline analysis, which is the major benefit provided by LMDA. Through various stages of development and testing, a Mirion Technologies model JCC-71 Neutron Coincidence Collar has been successfully retrofit with modern electronics designed in-house at Oak Ridge National Laboratory, matching preexisting JAB-01 electronics performance, while maintaining the original system footprint. This paper presents these various stages of development and experimental evaluation of the proof of concept system.

Moore, Angela S.↗
DOE OSTI2023

Geochemical constraints on bacteriophage infectivity in terrestrial environments

Abstract Lytic phages can be potent and selective inhibitors of microbial growth and can have profound impacts on microbiome composition and function. However, there is uncertainty about the biogeochemical conditions under which phage predation modulates microbial ecosystem function, particularly in terrestrial systems. Ionic strength is critical for infection of bacteria by many phages, but quantitative data is limited on the ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in the environment, we do not know how this variability influences the impact of phage predation on microbiome function. Here, we measured the half-maximal effective concentrations (EC50) of 80 different inorganic ions for the infection of E. coli with two canonical dsDNA and ssRNA phages, T4 and MS2, respectively. Many alkaline earth metals and alkali metals enabled lytic infection but the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate-reducing microbiome, we found that the ability of lytic phages to influence nitrate reduction end-products depended upon the carbon source as well as ionic strength. For all phage:host pairs, the ion EC50s for phage infection exceeded the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where phages most influence terrestrial microbial functional ecology in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and nutrients are available to support the growth of specific phage hosts.

Carlson, Hans K. (ORCID:0000000215835313)↗
DOE OSTI2025

2024 Buildings Technology Baseline: Dataset Documentation

The Buildings Technology Baseline is a curated and regularly updated dataset of current and projected performance, retail, and installed price data for all major building energy technologies needed to enable cost/benefit analyses. Building technology analyses require an up-to-date understanding of installation costs and cost-effectiveness of key building energy efficiency technologies. The dataset was assembled by Guidehouse during fiscal year 2024. Data was gathered from the 2024 National Residential Efficiency Measures Database (NREMDB), the 2023 Energy Information Administration Updated Buildings Sector Appliance and Equipment Costs and Efficiencies ("EIA Building Data Report"), DOE Lighting Market Model, the 2023 RSMeans database, and the 2020 Grid-Interactive Efficient Building Technology Cost, Performance, and Lifetime Characteristics ("GEB Data Report"), Lawrence Berkeley National Laboratory, various literature, as well as new data from online retailers, stakeholder interviews, and contractor databases in 2023 and 2024. The dataset has been reviewed by subject matter experts at NREL and DOE. The 2024 dataset release is intended to be a starting point for interested users to provide feedback. This database is not intended to provide specific cost estimates for a specific project. The cost estimates do not include any rebates or tax incentives that may be available for the measures. Rather, it is meant to help determine which measures may be more cost-effective. The National Renewable Energy Laboratory (NREL) makes every effort to ensure accuracy of the data; however, NREL does not assume any legal liability or responsibility for the accuracy or completeness of the information.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗