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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 OSTI2025

The construction of large-scale structure catalogs for the Dark Energy Spectroscopic Instrument

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Cross-shell excited configurations in the structure of 34 Si

The cross-shell excited states of 34 Si have been investigated via β decays of the 4 − ground state and the 1 + isomeric state of 34 Al. Since the valence protons and valence neutrons occupy different major shells in the ground state as well as the intruder 1 + isomeric state of 34 Al, intruder levels of 34 Si are populated via allowed β decays. Spin assignments to such intruder levels of 34 Si were established through γ-γ angular correlation analysis for the negative-parity states. The configurations of such intruder states play crucial roles in our understanding of the N = 20 shell gap evolution. A configuration interaction model derived from the FSU Hamiltonian was utilized in order to interpret the intruder states in 34 Si. Furthermore, shell model interaction derived from a more fundamental theory with the valence space in medium similarity renormalization group method was also employed to interpret the structure of 34 Si.

20 ≤ A ≤ 38↗
DOE OSTI2024

Determination of the spins and parities for the 0$^{+}_{4}$ and 0$^{+}_{5}$ states in 100 Zr

Here, two 0 + states at 1294.5 and 1774.0 keV, together with three 2 + and one 4 + levels, were identified or unambiguously spin-parity assigned for the first time in 100 Zr utilizing γ-ray spectroscopy and γ–γ angular correlation techniques with the Gammasphere spectrometer, following the β – decay of neutron-rich, mass-separated 100,100m Y isotopes. Comparisons with recent Monte Carlo shell-model calculations indicate that these two states are candidates for the bandhead of a sequence in a shape-coexisting spherical minimum predicted to be located around ≈1500 keV. According to the measured relative B(E2) relative transition probabilities, the 0$^+_5$ state exhibits decay properties which more closely align with those predicted for a spherical shape, while the 0$^+_4$ level is suggested to be associated with a weakly deformed shape similar to one related to the 0$^+_2$ state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

1994 SEMCOG Household-Based Person Trip Survey

The Southeast Michigan Council of Governments contracted with the Applied Management & Planning Group to conduct a travel behavior survey of 7,361 households from March 28, 1994, to June 10, 1994. The primary purpose of this study was to provide the council with a new database of travel behavior to assist in updating the region's transportation models. This data collection includes demographic, socioeconomic, travel, and mobile source emissions models for projecting future patterns of development, travel, congestion, and air pollution. Information about household characteristics and travel was collected using a one-day, activity-focused diary and a separate household survey. In an activity diary, respondents recorded 65,535 trips during the assigned the day.

1Hz data↗
DOE OSTI2024

Determination of the spins and parities for the $0^+_4$ and $0^+_5$ states in $^{100}Zr$

Two 0 + states at 1294.5 and 1774.0 keV, together with three 2 + and one 4 + levels, were identified or unambiguously spin-parity assigned for the first time in 100 Zr utilizing γ-ray spectroscopy and γ-γ angular correlation techniques with the Gammasphere spectrometer, following the β - decay of neutron-rich, mass separated 100,100m Y isotopes. Comparisons with recent Monte Carlo Shell-Model (MCSM) calculations indicate that these two states are candidates for the bandhead of a sequence in a shape-coexisting spherical minimum predicted to be located around ≈1500 keV. According to the measured relative B(E2) relative transition probabilities, the 0+ 5 state exhibits decay properties which more closely align with those predicted for a spherical shape, while the $0^+_4$ level is suggested to be associated with a weakly-deformed shape similar to one related to the $0^+_2$ state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Determination of the spins and parities for the $0$$^{+}_{4}$ and $0$$^{+}_{5}$ states in 100 Zr

Two 0 + states at 1294.5 and 1774.0 keV, together with three 2 + and one 4 + levels, were identified or unambiguously spin-parity assigned for the first time in 100 Zr utilizing γ-ray spectroscopy and γ-γ angular correlation techniques with the Gammasphere spectrometer, following the β¯ decay of neutron-rich, mass separated 100,100m Y isotopes. Comparisons with recent Monte Carlo Shell-Model (MCSM) calculations indicate that these two states are candidates for the bandhead of a sequence in a shape-coexisting spherical minimum predicted to be located around ≈1500 keV. According to the measured relative B(E2) relative transition probabilities, the $0$$^{+}_{5}$ state exhibits decay properties which more closely align with those predicted for a spherical shape, while the $0$$^{+}_{4}$ level is suggested to be associated with a weakly-deformed shape similar to one related to the $0$$^{+}_{2}$ state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Fast and efficient identification of anomalous galaxy spectra with neural density estimation

ABSTRACT Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the probabilistic auto-encoder, to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae, and overlapping objects. Conditional modelling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available.

Böhm, Vanessa↗
DOE OSTI2024

Transporter annotations are holding up progress in metabolic modeling

Mechanistic, constraint-based models of microbial isolates or communities are a staple in the metabolic analysis toolbox, but predictions about microbe-microbe and microbe-environment interactions are only as good as the accuracy of transporter annotations. A number of hurdles stand in the way of comprehensive functional assignments for membrane transporters. These include general or non-specific substrate assignments, ambiguity in the localization, directionality and reversibility of a transporter, and the many-to-many mapping of substrates, transporters and genes. In this perspective, we summarize progress in both experimental and computational approaches used to determine the function of transporters and consider paths forward that integrate both. Investment in accurate, high-throughput functional characterization is needed to train the next-generation of predictive tools toward genome-scale metabolic network reconstructions that better predict phenotypes and interactions. More reliable predictions in this domain will benefit fields ranging from personalized medicine to metabolic engineering to microbial ecology.

Casey, John↗
DOE OSTI2020

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Overall, our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

42 ENGINEERING↗
DOE OSTI2025

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗
DOE OSTI2025

Investigating Np(VI) Nitrate Speciation Control through Temperature and Optical Spectroscopy

Numerous areas of nuclear processing, such as radioisotope production, nuclear waste remediation, and separations, depend upon the speciation of f-elements in the solution state. However, fundamental knowledge of the actinides─particularly Np─lags behind most of the elements on the periodic table. Despite the importance of Np(VI) chemistry in separations and nuclear processing, its speciation in HNO 3 remains uncertain. This work addresses some of these gaps by investigating the effect of HNO 3 concentration and temperature on the spectra and speciation of the Np(VI) nitrate system. Six samples of Np in 1 to 10 M HNO 3 were prepared and treated with (NH 4 ) 2 [Ce(NO 3 ) 6 ] to stabilize the hexavalent oxidation state. The absorbance spectrum of the 10 M HNO 3 is drastically different from the spectra of the other samples; the 10 M spectrum indicates coordination of nitrate ligands to the Np(VI)O 2 2+ ion to form a complex with high symmetry. Additionally, absorbance spectra were recorded over the temperature range of 15 to 40 °C, and systematic increases and decreases in certain spectral features of the ultraviolet–visible (UV–vis)–near-infrared (NIR) spectra are present in the spectra. The difference in spectral features suggests that Np(VI) nitrate speciation depends on temperature. Dilution studies of this sample were monitored with UV–vis–NIR and Raman spectroscopies. Spectral data indicate the presence of multiple complexes with different symmetries, including a high-symmetry complex with an inversion center. As samples are diluted and aquo ligands replace nitrate ligands bound to the Np(VI) neptunyl cation, changes in spectroscopic signals indicate a decrease in the high-symmetry nitrate complex and an increase in the lower-symmetry aquo complex. Additionally, the Raman band associated with the Np(VI)O 2 2+ symmetric stretch broadens with dilution and is fitted with two peaks. These peaks are assigned to Np(VI) aquo and nitrato complexes, indicating that this vibrational mode is sensitive to the coordination environment of the Np(VI) neptunyl cation and that contributions from these two Np(VI) complexes can be distinguished. This unique experimental data could be used to advance computational models describing the electronic transitions of complex actinyl ions.

Absorption↗
DOE OSTI2024

Quantum annealing-aided design of an ultrathin-metamaterial optical diode

Abstract Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. Here, we leverage a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths. Consequently, we successfully identify optimal structures at three specific wavelengths (600, 800, and 1000 nm). In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal–dielectric pixel arrays. Thereby, it yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. In addition, we experimentally verify the optical isolation function of the optical diode.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nitrate-To-Ammonia Electroconversion at Neutral pH on Polycrystalline Vanadium Sulfide Derived from Vanadium Disulfide

The electrochemical nitrate reduction reaction (NO3RR) offers a pathway to produce NH3 for fuel and fertilizer from waste NO3-. In this work, a polycrystalline vanadium sulfide (VSx), which is derived from solvothermally grown and annealed VS2, is shown to exhibit excellent NO3RR activity (2.3 +- 0.6 mg.cm-2 geo..h-1 @ -0.92 VRHE) and Faradaic efficiency to NH4+ (69 +- 6% at -0.69 VRHE) in buffered neutral pH electrolyte containing 0.1 M NO3-. A variety of characterization techniques are leveraged to support the VSx assignment, including X-ray photoelectron spectroscopy, near-edge X-ray absorption fine structure spectroscopy, selected area electron diffraction, and X-ray diffraction measurements. The VS2 annealing step reduces the oxide character and generates VSx, which, based on the improved NO3RR activity, results in the creation of active sites for NO3- binding. To help shed light on NO3RR on VSx, VS2 is used as a model system, and a grand-canonical density functional theory (GC-DFT) investigation of VS2 shows strong evidence that S vacancies are active sites for NO3RR, where NO3- outcompetes H+ for adsorption at the S-vacancy sites. Moreover, GC-DFT results highlight a thermodynamically favorable reaction to generate NH4+ in an aqueous electrolyte at relevant cathodic potentials. As an annealed material, VSx may contain undersaturated V sites, which show an electronic structure similar to the theoretically calculated S-vacancy site of VS2, and these sites may contribute to the observed increase in NO3RR activity and selectivity for NH4+ on VSx versus unannealed VS2. Finally, kinetic isotope effect measurements suggest that the kinetic rate-limiting step of the NO3RR on VSx is not proton-coupled, indicating it may be the first electron transfer to adsorbed NO3*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

New constraints on sodium production in globular clusters from the Na 23 ( He 3 , d ) Mg 24 reaction

The star-to-star anticorrelation of sodium and oxygen is a defining feature of globular clusters, but, to date, the astrophysical site responsible for this unique chemical signature remains unknown. Sodium enrichment within these clusters depends sensitively on reaction rate of the sodium destroying reactions 23 Na(p, γ) and 23 Na(p,α). In this paper, we report the results of a 23 Na( 3 He,d) 24 Mg transfer reaction carried out at Triangle Universities Nuclear Laboratory using a 21 MeV 3 He beam. Astrophysically relevant states in 24 Mg between 11 < E x < 12 MeV were studied using high-resolution magnetic spectroscopy, thereby allowing the extraction of excitation energies and spectroscopic factors. Bayesian methods are combined with the distorted wave Born approximation to assign statistically meaningful uncertainties to the extracted spectroscopic factors. For the first time, these uncertainties are propagated through to the estimation of proton partial widths. Our experimental data are used to calculate the reaction rate. The impact of the new rates are investigated using asymptotic giant branch star models. Furthermore, it is found that while the astrophysical conditions still dominate the total uncertainty, intramodel variations on sodium production from the 23 Na(p, γ) and 23 Na(p,α) reaction channels are a lingering source of uncertainty.

20 ≤ A ≤ 38↗
DOE OSTI2025

Traffic Shaping to Traffic Engineering in Time-Sensitive OT Network

Modern industrial automation systems increasingly depend on network infrastructures for time-critical communication, driving the need for solutions that guarantee timely and reliable data delivery. IEEE 802.1 Time-Sensitive Networking (TSN) holds significant promise for converging Information Technology (IT) and Operational Technology (OT) networks, enabling interoperability and supporting the coexistence of mixed-critical traffic crucial for Industry 4.0 and IIoT. To achieve deterministic communication, TSN employs various traffic shapers such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), and Credit-Based Shaper (CBS). However, the effective deployment of TSN in industrial automation faces several challenges. These include the non-trivial mapping of diverse industrial traffic types to specific shapers, the complexity of optimizing shaper configurations. We present a model for effective traffic engineering within TSN enabled OT Network. Our experiments also demonstrate how shaping of certain traffic types get affected in absence of precise time synchronization and propose possible solutions based on experiment results. Based on our experimental results we provide recommendations on how traffic type assignments should be done and which traffic shaping mechanisms should be used for a particular traffic type.

Sarker, Taposh Kumer [University of Texas at El Pa↗
DOE OSTI2024

Seeing the forest for the trees: implementing dynamic representation of forest management and forest carbon in a long-term global multisector model

Abstract Studies have found that understanding forest management is critical in understanding the interaction between the carbon cycle and the integrated human-Earth system. This makes effectively representing forest management decisions such as planting and harvesting important. Here, we implement a novel dynamic forest harvest model in a global state of the art multi-sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement an approach that explicitly tracks forest age and generates rotation ages for forest harvest that are responsive to changes in wood prices, changes in forest age and regional preferences for forest rotation. Furthermore, the forest sector in GCAM competes for investment with other land use types in the future years based on expected profit. Our baseline scenario results indicate that with the new forest harvest model, the current global wood product demand in GCAM can be met with minimal loss of old growth forest through the age-based harvest decisions. We find that economic pressure for deforestation and consequent loss of forest carbon is a bigger driver of global forest change than wood harvests, especially in developing regions. Under alternative scenarios where an economic value is placed on carbon across the terrestrial and energy systems, while there is an increase in forest plantations, there can be corresponding decreases in forest cover in some regions as forest land competes with land for bio-energy crops. When the carbon in forests is assigned a price, we find that the average rotation age for wood harvests can be reduced across regions to harvest forests in a more carbon efficient manner.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Safety Functions and Features, Events and Processes for the E-Area Performance Assessment

The DOE Technical Standard, “Disposal Authorization Statement and Tank Closure Documentation,” (DOE 2017) recommends the use of safety functions and features, events and processes (FEPs) to support development of conceptual models and identification of scenarios to be considered in a performance assessment (PA). The FEP process provides a means to describe how a PA considers and addresses the factors that could influence the performance of key barriers. Understanding the roles of barriers in terms of limiting migration helps to focus on how changes in the system could lead to a situation where those roles cannot be fulfilled and there is the potential for compromised performance. The FEPs screening and review process was used to identify FEPs that are relevant for the EArea Low-Level Waste Facility (LLWF) and specifically those FEPs that could have a detrimental impact on the effectiveness of a given safety function. For this PA, a default list of FEPs developed at the International Atomic Energy Agency (IAEA 2004) and an approach implemented for PAs at the Hanford and Idaho sites (Mehta et al. 2016, DOE-ID 2019) are used to identify processes and events that could influence the effectiveness of a given safety function for the E-Area LLWF (e.g., subsidence can impact the safety function of the cover system and lead to increased infiltration). The Hanford and Idaho PAs represent two of the most recent applications of this approach. The PA evaluates the potential impacts of changes in performance of different features of the system and demonstrates that the safety functions represent multiple and redundant barriers. Barrier analyses, assuming a safety function is not present, also test the robustness of the system in the event of the loss of one or more safety functions. Such evaluations also support a qualitative illustration of the concept of defense in depth. The safety concept for closure of the E-Area LLWF (generically referred to as “E-Area”) encompasses a variety of different features (i.e., administrative controls, natural site features, and engineered barriers) that reduce the potential impacts on human health and the environment from the residual waste that will remain after closure. These features can be represented as a collection of safety functions acting independently and as a system to provide for overall safety. In some applications, there have been attempts to assign numerical expectations to specific safety functions, but that is not the intent in this case. The concept of safety functions is used more qualitatively in two ways for this PA: 1. To illustrate the robustness of the E-Area design, operational practices and closure approach by documenting features that are and are not credited in different modeling cases. 2. To identify the roles of the different features and potential processes and events that could compromise the performance of safety features and need to be considered when developing the modeling approach. This report addresses both safety functions and FEPs for the E-Area PA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Gut microbiome partially mediates and coordinates the effects of genetics on anxiety-like behavior in Collaborative Cross mice

Abstract Growing evidence suggests that the gut microbiome (GM) plays a critical role in health and disease. However, the contribution of GM to psychiatric disorders, especially anxiety, remains unclear. We used the Collaborative Cross (CC) mouse population-based model to identify anxiety associated host genetic and GM factors. Anxiety-like behavior of 445 mice across 30 CC strains was measured using the light/dark box assay and documented by video. A custom tracking system was developed to quantify seven anxiety-related phenotypes based on video. Mice were assigned to a low or high anxiety group by consensus clustering using seven anxiety-related phenotypes. Genome-wide association analysis (GWAS) identified 141 genes (264 SNPs) significantly enriched for anxiety and depression related functions. In the same CC cohort, we measured GM composition and identified five families that differ between high and low anxiety mice. Anxiety level was predicted with 79% accuracy and an AUC of 0.81. Mediation analyses revealed that the genetic contribution to anxiety was partially mediated by the GM. Our findings indicate that GM partially mediates and coordinates the effects of genetics on anxiety.

59 BASIC BIOLOGICAL SCIENCES↗