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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Laser-diagnostic mapping of temperature and soot statistics in a 2-m diameter turbulent pool fire

We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting 2-m base diameter turbulent pool fire, burning a 10%-toluene / 90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized to obtain radial profiles of temperature and soot probability density functions (pdf) as well as estimates of temperature/soot joint statistics at three vertical heights above the surface of the methanol/toluene fuel pool. Results are presented both in the fuel vapor-dome region at ¼ base diameter and in the actively burning region at ½ and ¾ diameters above the fuel surface. The spatial evolution of the soot and temperature pdfs is discussed and profiles of the temperature and soot mean and rms statistics are provided. Joint temperature/soot statistics are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations.

42 ENGINEERING↗
DOE OSTI2020

Hedonic Price Estimates of Lake Water Quality: Valued Attribute, Instrumental Variables, and Ecological-Economic Benefits

We estimate the effect of lake water quality on residential housing prices using cross-sectional data on water clarity from 113 lakes across the United States. An instrumental-variables approach is developed to address potential endogeneity bias in the water-clarity variable. Three lake-based physical variables serve as instrumental variables: total nitrogen concentration in lake water, total phosphorus concentration in lake water, and water temperature near the lake surface. The econometric results include three methodological findings: the instruments are valid and strong; the ordinary-least-squares estimate of the coefficient on the water-clarity variable is unbiased; and water clarity is the attribute of water quality valued in the housing market. The estimated water-clarity effect shows that a one-tenth of a meter change in water clarity leads to a one-percent change in housing price, or an elasticity of 0.20 at mean clarity. Coupling this effect with estimates of an ecological production function, a lake-specific benefit index is developed that shows the effect on housing values of bringing lakes into compliance with the US Environmental Protection Agency's regional recommendations for phosphorous concentration in lake waters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An evaluation of tri-valent oxide (Cr 2 O 3 ) as a grain enlarging dopant for UO 2 nuclear fuels fabricated under reducing environment

A study was performed to evaluate the microstructure and crystallography of nominally 500–2000 Cr 2 O 3 -doped UO 2 fabricated in a temperature range of 1150–1750°C under reducing experimental conditions. We observed an increase in grain size of the samples with the increase in heat treating temperature as expected. For a given sintering temperature (1700–1750°C), an increase in the grain size was also observed with the increase in Cr 2 O 3 concentration up to a value of ~1000–1200 wppm. A decrease in fission gas release as a function of grain size was estimated for the Cr 2 O 3 -doped UO 2 samples assuming specified post-irradiation annealing conditions. A nearly linear decrease was obtained in the lattice parameter of the Cr 2 O 3 -doped UO 2 fcc phase with the increase in Cr 2 O 3 concentration, especially up to a nominal value of 1000 wppm. The lattice parameter decrease was also persistent with the increase in the average grain size as a result of addition of Cr 2 O 3 into the UO 2 lattice. An increase in the crystallite size and a decrease in the microstrain of the $fcc$ phase were observed with the increase in the average grain size of the samples, indicating a higher crystallinity of the Cr 2 O 3 -doped samples than that of the undoped UO 2 sample.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Uniform-in-phase-space data selection with iterative normalizing flows

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Optimization of nonlinear turbulence in stellarators

We present new stellarator equilibria that have been optimized for reduced turbulent transport using nonlinear gyrokinetic simulations within the optimization loop. The optimization routine involves coupling the pseudo-spectral GPU-native gyrokinetic code GX with the stellarator equilibrium and optimization code DESC . Since using GX allows for fast nonlinear simulations, we directly optimize for reduced nonlinear heat fluxes. To handle the noisy heat flux traces returned by these simulations, we employ the simultaneous perturbation stochastic approximation (SPSA) method that only uses two objective function evaluations for a simple estimate of the gradient. We show several examples that optimize for both reduced heat fluxes and good quasi-symmetry as a proxy for low neoclassical transport. Finally, we run full transport simulations using the T3D stellarator transport code to evaluate the changes in the macroscopic profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Ab Initio Molecular Dynamics of Uranium Incorporated in Goethite (α-FeOOH): Interpretation of X-ray Absorption Spectroscopy of Trace Polyvalent Metals

Incorporation of economically or environmentally consequential polyvalent metals into iron (oxyhydr)oxides has applications in environmental chemistry, remediation, and materials science. A primary tool for characterizing the local coordination environment of such metals, and therefore building models to predict their behavior, is extended X-ray absorption fine structure spectroscopy (EXAFS). Accurate structural information can be lacking, yet is required to constrain and inform data interpretation. In this regard, ab initio molecular dynamics (AIMD) was used to calculate the local coordination environment of minor amounts of U incorporated in the structure of goethite (α-FeOOH). U oxidation state (VI, V, and IV) and charge compensation scheme (CCS) were varied. Simulated trajectories were used to calculate the U LIII-edge EXAFS function and fit experimental EXAFS data for U incorporated into goethite under reducing conditions. Calculations that closely matched the U EXAFS of the well-characterized mineral uraninite (UO2), and constrained the S02 parameter to be 0.909, validated the approach. The results for the U-goethite system indicated that U(V) substituted for structural Fe(III) in octahedral uranate coordination. Charge balance was achieved by the loss of one structural proton coupled to injection of one electron into the solid (–1 H+, + 1 e-). The ability of AIMD to model higher-energy states thermally accessible at room temperature is particularly relevant for protonated systems such as goethite, where proton transfers between adjacent octahedra had a dramatic effect on the calculated EXAFS. Vibrational effects as a function of temperature were also estimated using AIMD, allowing separate quantification of thermal and configurational disorder. In summary, coupling AIMD structural modeling and EXAFS experiments enables modeling of the redox behavior of polyvalent metals that are incorporated in conductive materials such as iron (oxyhydr)oxides, with applications over a broad swath of chemistry and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DONKEY: A Flexible and Accurate Algorithm for Clustering

We propose an accurate clustering algorithm suitable for the varied and multidimensional data sets that correspond to temporal snapshots from on-the-fly nonadiabatic trajectory-based simulations of photoexcited dynamics. The algorithm approximates the underlying probability density function using variable kernel density estimation, with local maxima corresponding to cluster centers. Each data point is then assigned to one of the maxima by employing a maximization procedure. Finally, clusters artificially separated by minor fluctuations in the probability density are merged. The algorithm does not require parameter tuning, which ensures flexibility and reduces the risk of bias. It is tested on several synthetic data sets, where it consistently outperforms conventional clustering algorithms. As a final example, the algorithm is applied to the excited dynamics of the norbornadiene ⇌ quadricyclane (C 7 H 8 ) molecular photoswitch, demonstrating how distinct reaction pathways can be identified.

algorithms↗
DOE OSTI2020

A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Towards Prediction of Non-Radiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields

Many emerging technologies depend on human’s ability to control and manipulate the excited-state properties of molecular systems. These technologies include fluorescent labeling in biomedical imaging, light harvesting in photovoltaics, and electroluminescence in light-emitting devices. All of these systems suffer from non-radiative loss pathways that dissipate electronic energy as heat, which causes the overall system efficiency to be directly linked to quantum yield (Φ) of the molecular excited state. Unfortunately, Φ is very difficult to predict from first principles because the description of a slow non-radiative decay mechanism requires an accurate description of long-timescale excited-state quantum dynamics. In the present study, we introduce an efficient semi-empirical method of calculating the fluorescence quantum yield (Φ fl ) for molecular chromophores, which converts simple electronic energies computed using time-dependent density functional theory (TDDFT) into an estimate of Φ fl . As with all machine learning strategies, the algorithm needs to be trained on fluorescent dyes for which Φ fl ’s are known, so as to provide a black-box method which can later predict Φfl’s for chemically similar chromophores that have not been studied experimentally. Here, as a first illustration of how our proposed algorithm can be trained, we examine a family of 25 naphthalene derivatives. The simplest application of the energy gap law is found to be inadequate to explain the rates of internal conversion (IC) or intersystem crossing (ISC) – the electronic properties of at least one higher-lying electronic state (S n or T n ) or one far-from-equilibrium geometry are typically needed to obtain accurate results. Indeed, the key descriptors turn out to be the transition state between the Franck–Condon minimum and a distorted local minimum near an S 0 /S 1 conical intersection (which governs IC) and the magnitude of the spin-orbit coupling (which governs ISC). The resulting Φ fl ’s are predicted with reasonable accuracy (~ 22%), making our approach a promising ingredient for high-throughput screening and rational design of the molecular excited states with desired Φ fl ’s. We thus conclude that our model, while semi-empirical in nature, does in fact extract sound physical insight into the challenge of describing non-radiative relaxations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coherent Spins in van der Waals Semiconductor GeS 2 at Ambient Conditions

Optically active spin defects in van der Waals (vdW) materials have emerged as versatile quantum sensors, enabling applications for a wide range of quantum phenomena in condensed matter systems. Their ease of exfoliation and compatibility with device integration make them promising candidates for future quantum technologies. Here we report the observation and room-temperature coherent control of ensemble spin defects in the high-temperature crystalline phase of germanium disulfide (β-GeS 2 ), a two-dimensional (2D) semiconductor with low nuclear spin density. The defects exhibit spin-1/2 behavior, and their dynamics can be explained by a weakly coupled spin-pair model. We implement dynamical decoupling techniques to extend the coherence time (T 2 ) by a factor of 20. Finally, we use density functional theory (DFT) calculations to estimate the structures and spin densities of two possible spin defect candidates. This work will help to expand the field of quantum sensing with spin defects in 2D materials.

2D materials↗
DOE OSTI2020

Emergence of unprecedented climate change in projected future precipitation

The future time of emergence when precipitation changes due to anthropogenic influences begins to continuously exceed the previous maximum value is defined as the ‘tipping year’ Historical experiments and future experiments simulated by state-of-the-art climate models were utilized. A total of 510,000 time series from year 1856 to 2095 were generated by sampling the natural internal variability in precipitation. The time evolutions of internal variability in the whole time period were estimated from the combination of past and future experiments with preindustrial control experiments. A large ensemble size enabled an estimation of the probability density function of the tipping year at each grid point, providing precise information on the uncertainty of the projection. The tipping year of average precipitation emerges earlier in high latitudes than in lower latitudes. In some regions in lower latitudes and mid-latitudes, the tipping year of intense precipitation emerges faster than that of average precipitation. The tipping years of average and intense precipitation are earlier for higher anthropogenic forcing scenarios than for lower scenarios. The global average of the tipping year for intense precipitation might be attributed to the enhancement of the thermodynamic effect (moisture) rather than the dynamic effect (vertical motion).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Revisiting the pseudo-supercritical path method: An improved formulation for the alchemical calculation of solid–liquid coexistence

Alchemical free energy calculations via molecular dynamics have been applied to obtain thermodynamic properties related to solid–liquid equilibrium conditions, such as melting points. In recent years, the pseudo-supercritical path (PSCP) method has proved to be an important approach to melting point prediction due to its flexibility and applicability. In the present work, we propose improvements to the PSCP alchemical cycle to make it more compact and efficient through a concerted evaluation of different potential energies. The multistate Bennett acceptance ratio (MBAR) estimator was applied at all stages of the new cycle to provide greater accuracy and uniformity, which is essential concerning uncertainty calculations. In particular, for the multistate expansion stage from solid to liquid, we employed the MBAR estimator with a reduced energy function that allows affine transformations of coordinates. Free energy and mean derivative profiles were calculated at different cycle stages for argon, triazole, propenal, and the ionic liquid 1-ethyl-3-methyl-imidazolium hexafluorophosphate. Comparisons showed a better performance of the proposed method than the original PSCP cycle for systems with higher complexity, especially the ionic liquid. Furthermore, a detailed study of the expansion stage revealed that remapping the centers of mass of the molecules or ions is preferable to remapping the coordinates of each atom, yielding better overlap between adjacent states and improving the accuracy of the methodology.

25 ENERGY STORAGE↗
DOE OSTI2024

Optically multiplexed neutron time-of-flight technique for inertial confinement fusion

Neutron time-of-flight (nTOF) detectors are crucial in diagnosing the performance of inertial confinement fusion (ICF) experiments, which implode targets of deuterium–tritium fuel to achieve thermonuclear conditions. These detectors utilize the fusion neutron energy spectrum to extract key measurements, including the hotspot ion temperature and fuel areal density. Previous work [Danly et al., Rev. Sci. Instrum. 94, 043502 (2023)] has demonstrated adding 1D spatial resolution to an nTOF-like detector using a neutron aperture and streak camera to measure the ion temperature profile of an ICF implosion. By contrast, the study presented herein explores modifying the 1D detector to use a fast photomultiplier tube (PMT) to validate the design of a 2D spatially resolved instrument based on reconstruction from 1D profiles. The modification would collect time-of-flight traces from separate scintillators in an imaging array with one PMT using optical fibers of varying lengths to time-multiplex the signals. This technique has been demonstrated in ride-along experiments on the OMEGA laser with 20 fiber-coupled scintillator channels connected to a Photek PMT210. Results provide constraints on the fiber lengths and PMT gating requirements to promote pulse fidelity throughout all channels. Calibration of the detector to fixed nTOFs can provide a preliminary estimate of the instrument response function (IRF), although measurement of the IRF is currently under way. These results suggest that nTOF signals can potentially be time-multiplexed with fibers so long as the design is strategic to mitigate signal-to-noise reduction, modal dispersion, and charge build-up in the PMT, which has implications beyond ion temperature imaging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

On the synchrotron emission in kinetic simulations of runaway electrons in magnetic confinement fusion plasmas

Developing avoidance or mitigation strategies of runaway electrons (REs) in magnetic confinement fusion (MCF) plasmas is of crucial importance for the safe operation of ITER. In order to develop these strategies, an accurate diagnostic capability that allows good estimates of the RE distribution function in these plasmas is needed. Synchrotron radiation (SR) of RE in MCF, besides of being one of the main damping mechanisms for RE in the high energy relativistic regime, is routinely used in current MCF experiments to infer the parameters of RE energy and pitch angle distribution functions. In the present paper we address the long standing question about what are the relationships between different REs distribution functions and their corresponding synchrotron emission simultaneously including: full-orbit effects, information of the spectral and angular distribution of SR of each electron, and basic geometric optics of a camera. We study the spatial distribution of the SR on the poloidal plane, and the statistical properties of the expected value of the synchrotron spectra of REs. Here we observe a strong dependence of the synchrotron emission measured by the camera on the pitch angle distribution of runaways, namely we find that crescent shapes of the spatial distribution of the SR as measured by the camera relate to RE distributions with small pitch angles, while ellipse shapes relate to distributions of runaways with larger the pitch angles. A weak dependence of the synchrotron emission measured by the camera with the RE energy, value of the q-profile at the edge, and the chosen range of wavelengths is observed. Furthermore, we find that oversimplifying the angular dependence of the SR changes the shape of the synchrotron spectra, and overestimates its amplitude by approximately 20 times for avalanching runaways and by approximately 60 times for mono-energetic distributions of runaways.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

pKPDB: a protein data bank extension database of p Ka and pI theoretical values

Abstract Summary pKa values of ionizable residues and isoelectric points of proteins provide valuable local and global insights about their structure and function. These properties can be estimated with reasonably good accuracy using Poisson–Boltzmann and Monte Carlo calculations at a considerable computational cost (from some minutes to several hours). pKPDB is a database of over 12 M theoretical pKa values calculated over 120k protein structures deposited in the Protein Data Bank. By providing precomputed pKa and pI values, users can retrieve results instantaneously for their protein(s) of interest while also saving countless hours and resources that would be spent on repeated calculations. Furthermore, there is an ever-growing imbalance between experimental pKa and pI values and the number of resolved structures. This database will complement the experimental and computational data already available and can also provide crucial information regarding buried residues that are under-represented in experimental measurements. Availability and implementation Gzipped csv files containing p Ka and isoelectric point values can be downloaded from https://pypka.org/pKPDB. To query a single PDB code please use the PypKa free server at https://pypka.org. The pKPDB source code can be found at https://github.com/mms-fcul/pKPDB. Supplementary information Supplementary data are available at Bioinformatics online.

Reis, Pedro B. P. S. (ORCID:0000000335636239)↗
DOE OSTI2022

Regression of exchangeable relational arrays

Relational arrays represent measures of association between pairs of actors, often in varied contexts or over time. Trade flows between countries, financial transactions between individuals, contact frequencies between school children in classrooms and dynamic protein-protein interactions are all examples of relational arrays. Elements of a relational array are often modelled as a linear function of observable covariates. Uncertainty estimates for regression coefficient estimators, and ideally the coefficient estimators themselves, must account for dependence between elements of the array, e.g., relations involving the same actor. Existing estimators of standard errors that recognize such relational dependence rely on estimating extremely complex, heterogeneous structure across actors. This paper develops a new class of parsimonious coefficient and standard error estimators for regressions of relational arrays. Here we leverage an exchangeability assumption to derive standard error estimators that pool information across actors, and are substantially more accurate than existing estimators in a variety of settings. This exchangeability assumption is pervasive in network and array models in the statistics literature, but not previously considered when adjusting for dependence in a regression setting with relational data. We demonstrate improvements in inference theoretically, via a simulation study, and by analysis of a dataset involving international trade.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Chromatic effects on the PSF and shear measurement for the Roman Space Telescope High-Latitude Wide Area Survey

Weak gravitational lensing (WL) is a key cosmological probe that requires precise measurement of galaxy images to infer shape distortions, or shear, and constrain cosmology. Accurate estimation of the point spread function (PSF) is crucial for shear measurement, but the wavelength dependence of the PSF introduces chromatic biases that can systematically impact shear inference. We focus on biases arising from spectral energy distribution (SED) differences between stars, used for PSF modelling, and galaxies, used for shear measurement. We investigate these effects in Roman’s four design reference mission WL bands (Y106, J129, H158, F184) and wide filter (W146). Using Roman-like image simulations, we quantify the induced shear biases and compare them to requirements on those biases. Multiplicative biases over all galaxies hover around ~0.2 per cent in the WL bands and 2 per cent in the wide filter, exceeding the mission requirement of |m| < 0.032 per cent and relaxed requirement of |m| < 0.1 per cent⁠. In individual redshift bins, biases can reach 0.4–0.9 per cent for the WL bands and 3–6 per cent for the wide filter. Additive biases remain acceptable in the WL bands but exceed systematic limits in the wide filter. We develop and test PSF-level corrections, showing that a first-order correction reduces biases within survey requirements for the WL bands; however, higher-order terms are necessary for the wide filter. Our results highlight the necessity of chromatic corrections for precision WL with Roman and provide a framework for mitigating these biases. Finally, we compare analytical colour-based corrections to self-organizing maps and find that both methods effectively reduce biases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Remote detection of radioactive material using a short-pulse CO 2 laser

Detection of radioactive material at distances greater than the radiated particle range is an important goal with applications in areas such as national defense and disaster response. Here, we demonstrate avalanche-breakdown-based remote detection of a 3.6 mCi α-particle source at a standoff distance of 10 m, using 70 ps, long-wave infrared (λ = 9.2 µm) CO 2 laser pulses. This is ∼10 times longer than our previous results using a mid-IR laser. The primary detection method is direct backscatter from microplasmas generated in the laser focal volume. The backscatter signal is amplified as it propagates back through the CO 2 laser chain, enhancing sensitivity by >100 times. Here we also characterize breakdown plasmas with fluorescence imaging, and present a simple model to estimate backscattered signals as a function of the seed density profile in the laser focal volume. All of this is achieved with a relatively long-drive laser focal geometry (f/200) that is readily scalable to >100 m.

43 PARTICLE ACCELERATORS↗