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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards revealing intrinsic vortex-core states in Fe-based superconductors through statistical discovery

Abstract In type-II superconductors, electronic states within magnetic vortices hold crucial information about the paring mechanism and can reveal non-trivial topology. While scanning tunneling microscopy/spectroscopy (STM/S) is a powerful tool for imaging superconducting vortices, it is challenging to isolate the intrinsic electronic properties from extrinsic effects like subsurface defects and disorders. Here we combine STM/STS with basic machine learning to develop a method for screening out the vortices pinned by embedded disorder in iron-based superconductors. Through a principal component analysis of large STS data within vortices, we find that the vortex-core states in Ba(Fe 0.96 Ni 0.04 ) 2 As 2 start to split into two categories at certain magnetic field strengths, reflecting vortices with and without pinning by subsurface defects or disorders. Our machine-learning analysis provides an unbiased approach to reveal intrinsic vortex-core states in novel superconductors and shed light on ongoing puzzles in the possible emergence of a Majorana zero mode.

Guo, Yueming↗
DOE OSTI2023

Understanding the compound flood risk along the coast of the contiguous United States

Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Updated distribution maps of predominant Culex mosquitoes across the Americas

Abstract Background Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s. Since these estimates were made, there have been many more documented observations of mosquitoes and new methods have been developed for species distribution modeling. Moreover, mosquito distributions are affected by environmental conditions, which have changed since the 1980s. This calls for updated estimates of these distributions to understand the risk of emerging and re-emerging mosquito-borne diseases. Methods We used contemporary mosquito data, environmental drivers, and a machine learning ecological niche model to create updated estimates of the geographical range of seven predominant Culex species across North America and South America: Culex erraticus , Culex nigripalpus , Culex pipiens , Culex quinquefasciatus , Culex restuans , Culex salinarius , and Culex tarsalis . Results We found that Culex mosquito species differ in their geographical range. Each Culex species is sensitive to both natural and human-influenced environmental factors, especially climate and land cover type. Some prefer urban environments instead of rural ones, and some are limited to tropical or humid areas. Many are found throughout the Central Plains of the USA. Conclusions Our updated contemporary Culex distribution maps may be used to assess mosquito-borne disease risk. It is critical to understand the current geographical distributions of these important disease vectors and the key environmental predictors structuring their distributions not only to assess current risk, but also to understand how they will respond to climate change. Since the environmental predictors structuring the geographical distribution of mosquito species varied, we hypothesize that each species may have a different response to climate change. Graphical abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using ground state and excited state density functional theory to decipher 3d dopant defects in GaN

Abstract Using ground state density functional theory (DFT) and implementing an occupation-constrained DFT (occ-DFT) for self-consistent excited state calculations, we decipher the electronic structure of the Mn dopant and other 3 d defects in GaN across the band gap. Our analysis, validated with broad agreement with defect levels (ground-state calculations) and photoluminescence data (excited-state calculations), mandates reinterpretation and reassignment of 3 d defect data in GaN. The Mn Ga defect is determined to span stable charge states from (1−) in n -type GaN through (2+) in p -type GaN. The Mn(2+) is predicted to be a d 2 ground state spin triplet defect with a singlet excited state, isoelectronic with the defect associated with the 1.19 eV photoluminescence in n -type GaN. The combined analysis of defect levels and excited states invites reassessment of all d 2 -capable dopants in GaN. We demonstrate that the 1.19 eV defect, a candidate defect for optically controlled quantum applications, cannot be the Cr(1+) assumed in literature and instead must be the V(0). The combined ground-state/excited-state DFT analysis is shown to be able to chemically fingerprint defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Model-independent constraints on Ωm and H ( z ) from the link between geometry and growth

ABSTRACT We constrain the expansion history of the Universe and the cosmological matter density fraction in a model-independent way by exclusively making use of the relationship between background and perturbations under a minimal set of assumptions. We do so by employing a Gaussian process to model the expansion history of the Universe from present time to the recombination era. The expansion history and the cosmological matter density are then constrained using recent measurements from cosmic chronometers, Type-Ia supernovae, baryon acoustic oscillations, and redshift-space distortion data. Our results show that the evolution in the reconstructed expansion history is compatible with the Planck 2018 prediction at all redshifts. The current data considered in this study can constrain a Gaussian process on H(z) to an average $9.4 {{\ \rm per\ cent}}$ precision across redshift. We find Ωm = 0.224 ± 0.066, lower but statistically compatible with the Planck 2018 cosmology. Finally, the combination of future DESI measurements with the CMB measurement considered in this work holds the promise of $8 {{\ \rm per\ cent}}$ average constraints on a model-independent expansion history as well as a five-fold tighter Ωm constraint using the methodology developed in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BuildStockQuery [SWR-23-58]

BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. BuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.

Adhikari, Rajendra↗
DOE OSTI2024

Hawai‘i Supernova Flows: a peculiar velocity survey using over a Thousand Supernovae in the near-infrared

ABSTRACT We introduce the Hawai‘i Supernova Flows project and present summary statistics of the first 1217 astronomical transients observed, 668 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to obtain systematics-limited distances to SNe Ia while consuming minimal dedicated observational resources. To date, we have performed almost 5000 near-infrared (NIR) observations of astronomical transients and have obtained spectra for over 200 host galaxies lacking published spectroscopic redshifts. In this survey paper, we describe the methodology used to select targets, collect/reduce data, calculate distances, and perform quality cuts. We compare our methods to those used in similar studies, finding general agreement or mild improvement. Our summary statistics include various parametrizations of dispersion in the Hubble diagrams produced using fits to several commonly used SN Ia models. We find the lowest dispersions using the SNooPy package’s EBV_model2, with a root mean square deviation of 0.165 mag and a normalized median absolute deviation of 0.123 mag. The full utility of the Hawai‘i Supernova Flows data set far exceeds the analyses presented in this paper. Our photometry will provide a valuable test bed for models of SN Ia incorporating NIR data. Differential cosmological studies comparing optical samples and combined optical and NIR samples will have increased leverage for constraining chromatic effects like dust extinction. We invite the community to explore our data by making the light curves, fits, and host galaxy redshifts publicly accessible.

Do, Aaron (ORCID:0000000334297845)↗
DOE OSTI2025

Addressing the Split Incentive Challenge for Enhanced Solar Adoption in Multifamily Rental Properties [Abstract]

The split incentive problem is particularly pronounced in rental markets, where landlords prioritize investments that directly increase property value or rental income. Since energy savings from solar photovoltaic (PV) systems primarily benefit tenants, landlords may perceive little return on investment unless mechanisms exist to recapture some of the financial gains. The primary objective of this project is to develop a publicly available, web-based tool to analyze the U.S. Department of Energy’s ResStock database, which models the U.S. residential building stock. The tool allows users to filter buildings by location, type, HVAC system, square footage, and other characteristics, and outputs typical electric load profiles. By leveraging location-specific electric load data, Fram Energy aims to advance business strategies that address the split incentive barrier and promote the adoption of solar PV installations in rental properties. In addition, a machine learning model will be developed to weigh the marginal contribution of building features across the dataset in predicting electricity demand, supporting guided decision making in forecasting electric load profiles. Lastly, based on each building’s location, load profile, and utility’s electricity rate, an optimized solar photovoltaic array and battery energy storage system will be sized to provide energy arbitrage opportunities.

14 SOLAR ENERGY↗
DOE OSTI2021

Discreteness and integrality in Conformal Field Theory

Various observables in compact CFTs are required to obey positivity, discreteness, and integrality. Positivity forms the crux of the conformal bootstrap, but understanding of the abstract implications of discreteness and integrality for the space of CFTs is lacking. We systematically study these constraints in two-dimensional, non-holomorphic CFTs, making use of two main mathematical results. First, we prove a theorem constraining the behavior near the cusp of integral, vector-valued modular functions. Second, we explicitly construct non-factorizable, non-holomorphic cuspidal functions satisfying discreteness and integrality, and prove the non-existence of such functions once positivity is added. Application of these results yields several bootstrap-type bounds on OPE data of both rational and irrational CFTs, including some powerful bounds for theories with conformal manifolds, as well as insights into questions of spectral determinacy. We prove that in rational CFT, the spectrum of operator twists t ≥ c/12 is uniquely determined by its complement. Likewise, we argue that in generic CFTs, the spectrum of operator dimensions Δ > c–1/12 is uniquely determined by its complement, absent fine-tuning in a sense we articulate. Finally, we discuss implications for black hole physics and the (non-)uniqueness of a possible ensemble interpretation of AdS 3 gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Photosynthetic modulation during the diurnal cycle in a unicellular diazotrophic cyanobacterium grown under nitrogen-replete and nitrogen-fixing conditions

Abstract Cyanobacteria are the only oxygenic photosynthetic organisms that can fix nitrogen. In diazotrophic cyanobacteria, the regulation of photosynthesis during the diurnal cycle is hypothesized to be linked with nitrogen fixation and involve the D1 protein isoform PsbA4. The amount of bioavailable nitrogen has a major impact on productivity in aqueous environments. In contrast to low- or nitrogen-fixing (−N) conditions, little data on photosynthetic regulation under nitrogen-replete (+ N) conditions are available. We compared the regulation of photosynthesis under −N and + N conditions during the diurnal cycle in wild type and a psbA4 deletion strain of the unicellular diazotrophic cyanobacterium Cyanothece sp. ATCC 51142. We observed common changes to light harvesting and photosynthetic electron transport during the dark in + N and −N conditions and found that these modifications occur in both diazotrophic and non-diazotrophic cyanobacteria. Nitrogen availability increased PSII titer when cells transitioned from dark to light and promoted growth. Under −N conditions, deletion of PsbA4 modified charge recombination in dark and regulation of PSII titer during dark to light transition. We conclude that darkness impacts the acceptor-side modifications to PSII and photosynthetic electron transport in cyanobacteria independently of the nitrogen-fixing status and the presence of PsbA4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

Abstract This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid‐Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross‐validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.

Pang, Hao↗
DOE OSTI2026

Fortran mimetic abstraction language (Formal) v0.1.

The Fortran mimetic abstraction language ("Formal") is a domain-specific language (DSL) embedded in Fortran 202Y [1]. Formal provides novel software abstractions for simulating phenomena governed by the partial differential equations (PDEs) of vector and tensor calculus. Such equations model an extremely broad set of physical phenomena, ranging from atmospheric winds to light propagation. Formal's data structures and algorithms mimic in form and behavior continuous functions and operators. Formal supports these mathematical constructs using mimetic discretizations that define a discrete calculus satisfying various tensor calculus theorems, thereby ensuring high-fidelity representations of the physics being modeled. [2] Formal 0.1.0 also lays a foundation for the future use of Fortran 202Y type-safe templates to facilitate the formal verification of tensor contractions in computational physics and artificial intelligence [3]. [1] "Fortran 202Y" is Fortran standard committee's informal designation for the next Fortran revision, which will likely be "Fortran 2028". [2] Corbino, J. and Castillo, J. (2020) Journal of Computational and Applied Mathematics, https://doi.org/10.1016/j.cam.2019.06.042. [3] Haveraaen, M., Järvi, J., & Rouson, D. (2019). Reflecting on Generics for Fortran. https://j3-fortran.org/doc/year/19/19-188.pdf.

Rouson, Damian [Lawrence Berkeley National Laborat↗
DOE OSTI2023

African smoke particles act as cloud condensation nuclei in the wintertime tropical North Atlantic boundary layer over Barbados

Abstract. The number concentration and properties of aerosol particles serving as cloud condensation nuclei (CCN) are important for understanding cloud properties, including in the tropical Atlantic marine boundary layer (MBL), where marine cumulus clouds reflect incoming solar radiation and obscure the low-albedo ocean surface. Studies linking aerosol source, composition, and water uptake properties in this region have been conducted primarily during the summertime dust transport season, despite the region receiving a variety of aerosol particle types throughout the year. In this study, we compare size-resolved aerosol chemical composition data to the hygroscopicity parameter κ derived from size-resolved CCN measurements made during the Elucidating the Role of Clouds–Circulation Coupling in Climate (EUREC4A) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns from January to February 2020. We observed unexpected periods of wintertime long-range transport of African smoke and dust to Barbados. During these periods, the accumulation-mode aerosol particle and CCN number concentrations as well as the proportions of dust and smoke particles increased, whereas the average κ slightly decreased (κ=0.46±0.10) from marine background conditions (κ=0.52±0.09) when the submicron particles were mostly composed of marine organics and sulfate. Size-resolved chemical analysis shows that smoke particles were the major contributor to the accumulation mode during long-range transport events, indicating that smoke is mainly responsible for the observed increase in CCN number concentrations. Earlier studies conducted at Barbados have mostly focused on the role of dust on CCN, but our results show that aerosol hygroscopicity and CCN number concentrations during wintertime long-range transport events over the tropical North Atlantic are also affected by African smoke. Our findings highlight the importance of African smoke for atmospheric processes and cloud formation over the Caribbean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Dark Energy Survey Supernova Program results: type Ia supernova brightness correlates with host galaxy dust

ABSTRACT Cosmological analyses with type Ia supernovae (SNe Ia) often assume a single empirical relation between colour and luminosity (β) and do not account for varying host-galaxy dust properties. However, from studies of dust in large samples of galaxies, it is known that dust attenuation can vary significantly. Here, we take advantage of state-of-the-art modelling of galaxy properties to characterize dust parameters (dust attenuation AV, and a parameter describing the dust law slope RV) for 1100 Dark Energy Survey (DES) SN host galaxies. Utilizing optical and infrared data of the hosts alone, we find three key aspects of host dust that impact SN cosmology: (1) there exists a large range (∼1–6) of host RV; (2) high-stellar mass hosts have RV on average ∼0.7 lower than that of low-mass hosts; (3) for a subsample of 81 spectroscopically classified SNe there is a significant (>3σ) correlation between the Hubble diagram residuals of red SNe Ia and the host RV that when corrected for reduces scatter by $\sim 13{{\ \rm per\ cent}}$ and the significance of the ‘mass step’ to ∼1σ. These represent independent confirmations of recent predictions based on dust that attempted to explain the puzzling ‘mass step’ and intrinsic scatter (σint) in SN Ia analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2022

Late-onset Circumstellar Medium Interactions are Rare: An Unbiased GALEX View of Type Ia Supernovae

Abstract Using ultraviolet (UV) light curves, we constrain the circumstellar environments of 1080 Type Ia supernovae (SNe Ia) within z < 0.5 from archival Galaxy Evolution Explorer (GALEX) observations. All SNe Ia are required to have pre- and post-explosion GALEX observations to ensure adequate subtraction of the host-galaxy flux. Using the late-time GALEX observations, we look for the UV excess expected from any interaction between the SN ejecta and circumstellar material (CSM). Four SNe Ia are detected near maximum light, and we compare the GALEX photometry to archival data. However, we find that none of our targets show convincing evidence of CSM interaction. A recent Hubble Space Telescope (HST) survey estimates that ∼6% of SNe Ia may interact with distant CSM, but statistical inferences are complicated by the small sample size and selection effects. By injecting model light curves into our data and then recovering them, we constrain a broad range of CSM interactions based on the CSM interaction start time and the maximum luminosity. Combining our GALEX nondetections with the HST results, we constrain occurrence of late-onset CSM interaction among SNe Ia with moderate CSM interaction, similar to that observed in PTF11kx, to f CSM ≲ 5.1% between 0 and 500 days after discovery and ≲2.7% between 500 and 1000 days after discovery at 90% confidence. For weaker CSM interactions similar to SN 2015cp, we obtain limits of ≲16% and ≲4.8%, respectively, for the same time ranges.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Molecular subtyping reveals immune alterations in IDH wild‐type lower‐grade diffuse glioma

Abstract Isocitrate dehydrogenase ( IDH ) wild‐type diffuse lower‐grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression‐based molecular classification of IDH wild‐type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild‐type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy‐three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild‐type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up‐regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A / CDKN2B , DMRTA1 , C9orf53 , and MTAP . Furthermore, we developed and validated a five‐gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild‐type diffuse LGGs and deepen our molecular understandi‐g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Wu, Fan↗