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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Quantum stress and torsion distributions in the deuteron

Stress distributions in the deuteron are related to form factors of the asymmetric energy-momentum tensor through three-dimensional Fourier transforms. There are eleven such form factors, which we calculate in an impulse approximation. We compare the obtained form factors to prior results for the six form factors that have been previously calculated. We then elaborate on the formalism for relating the form factors to internal distributions of mass, mass flux, momentum, stresses, and forces, and obtain results for all of these distributions. We obtain the principal stresses for the symmetric part of the stress tensor, and show that the antisymmetric part describes the reorientation of fermion spin by torsion stress when the nucleon moves between the S and D waves. Force distributions in the nucleons depend on the so-called nonconserved form factors through the Cauchy momentum equation, and are nonradial owing to the presence of tensor forces and spin-orbit coupling.

QCD phenomenology↗
DOE OSTI2024

String-based parametrization of nucleon GPDs at any skewness: A comparison to lattice QCD

We introduce a string-based parametrization for nucleon quark and gluon generalized parton distributions (GPDs) valid at all skewness values. The conformal moments of the GPDs are expressed as sums of the spin-j nucleon A-form factor and the skewness-dependent spin-j nucleon D-form factor. This representation, which fulfills the polynomiality condition (due to Lorentz invariance) and does not rely on model-specific assumptions, is derived from t-channel string exchanges in anti-de Sitter spaces. The spin-j nucleon D-form factor is closely related to the spin-j nucleon A-form factor. We use the Mellin moments from empirical parton distributions to model the spin-j nucleon A-form factors. Using only five Regge slope parameters, fixed from the electromagnetic and gravitational form factors, our string-based parametrization generates accurate singlet, nonsinglet, isovector, and flavor-separated nucleon quark GPDs, along with symmetric nucleon gluon GPDs from their Mellin-Barnes integral representations. Our isovector nucleon quark GPD is in agreement with existing lattice data. Our string-based parametrization should facilitate the empirical extraction and global analysis of nucleon GPDs in exclusive processes, bypassing the deconvolution challenge.

Electron-ion collisions↗
DOE OSTI2025

Effective Li-Ion Transport Quantification in Composite Cathodes for All-Solid-State Batteries via Multiscale Modeling and Experiments

The tortuosity factor of composite cathodes significantly affects the rate performance of all-solid-state batteries (ASSBs) and has significant differences from systems with liquid electrolytes. Here, in this work, we report a simulation-experiment combined approach that quantifies the effective Li-ion transport in an ASSB composite cathode, which links tortuosity factor on ∼ μm scale to terminal voltage during cycling at the cell level (on ∼ cm scale). Two independent approaches of tortuosity factor quantification are considered: fitting electrochemical cycling data and verifying at different cycling rates and calculating from segmented tomography images, with the tortuosity factor quantified from both methods reaching self-consistency. The simulated terminal voltage using the quantified tortuosity factor has a small relative error of <3% compared to the experimental measurements. We find a significantly reduced value of the Bruggeman exponent of the catholyte phase (1.75), and using shape analysis, we show that rod-shaped catholyte particles play an important role in lowering the tortuosity factor.

Yao, Archie Mingze [Univ. of Michigan, Ann Arbor, ↗
DOE OSTI2026

Analysis of a Heat Balance Experiment in the TREAT Reactor with SPARTA and OpenMC

This article presents the interpretation of a heat balance experiment in TREAT using the SPARTA methodology and an OpenMC model. The study examines the effects of control rods and temperature variations on the effective multiplication factor ($k_{\rm eff}$) and correction factors. Results indicate that both core temperature and rod positions have a linear effect on $k_{\rm eff}$ and correction factors in the upper-west channel. A critical hypothesis of SPARTA was validated: reactivities and correction factors can be obtained by linearly combining individual effects. The previously considered negligible effect of temperature on correction factors was found to be significant, necessitating updates to the SPARTA methodology. By fitting an exponential curve to mean temperature data, SPARTA's accuracy and convergence have been improved. Comparisons between SPARTA and OpenMC showed consistent reactivity removal due to temperature increase. While SPARTA effectively interprets complex transients, simpler methods may suffice when correction factors have minimal influence on reactivity calculations.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Structural analysis of extracellular ATP-independent chaperones of streptococcal species and protein substrate interactions

ABSTRACT During infection, bacterial pathogens rely on secreted virulence factors to manipulate the host cell. However, in gram-positive bacteria, the molecular mechanisms underlying the folding and activity of these virulence factors after membrane translocation are not clear. Here, we solved the protein structures of two secreted parvulin and two secreted cyclophilin-like peptidyl-prolyl isomerase (PPIase) ATP-independent chaperones found in gram-positive streptococcal species. The extracellular parvulin-type PPIase, PrsA inStreptococcus pneumoniaeandStreptococcus mutansmaintain dimeric crystal structures reminiscent of folding catalysts that consist of two domains, a PPIase and foldase domain. Structural comparison of the two cyclophilin-like extracellular chaperones fromS. pneumoniaeandStreptococcus pyogeneswith other cyclophilins demonstrates that this group of cyclophilin-like chaperones has novel structural appendages formed by 9- and 24-residue insertions. Furthermore, we demonstrate that deletion ofprsAandslrAgenes impairs the secretion of the cholesterol-dependent pore-forming toxin, pneumolysin inS. pneumoniae. Using protein pull-down and biophysical assays, we demonstrate a direct interaction between PrsA and SlrA with Ply. Then, we developed chaperone-assisted folding assays that show that theS. pneumoniaePrsA and SlrA extracellular chaperones accelerate pneumolysin folding. In addition, we demonstrate that SlrA and, for the first time,S. pyogenes PpiA exhibit PPIase activity and can bind the immunosuppressive drug, cyclosporine A. Altogether, these findings suggest a mechanistic role for streptococcal PPIase chaperones in the activity and folding of secreted virulence factors such as pneumolysin. IMPORTANCE Streptococcal species are a leading cause of lower respiratory infections that annually affect millions of people worldwide. During infection, streptococcal species secrete a medley of virulence factors that allow the bacteria to colonize and translocate to deeper tissues. In many gram-positive bacteria, virulence factors are secreted from the cytosol across the bacterial membrane in an unfolded state. The bacterial membrane-cell wall interface is exposed to the potentially harsh extracellular environment, making it difficult for native virulence factors to fold before being released into the host. ATP-independent PPIase-type chaperones, PrsA and SlrA, are thought to facilitate folding and stabilization of several unfolded proteins to promote the colonization and spread of streptococci. Here, we present crystal structures of the molecular chaperones of PrsA and SlrA homologs from streptococcal species. We provide evidence that theStreptococcus pyogenesSlrA homolog, PpiA, has PPIase activity and binds to cyclosporine A. In addition, we show thatStreptococcus pneumoniaePrsA and SlrA directly interact and fold the cholesterol-dependent pore-forming toxin and critical virulence determinant, pneumolysin.

Microbiology↗
DOE OSTI2024

Infinite quantum signal processing

Quantum signal processing (QSP) represents a real scalar polynomial of degree d using a product of unitary matrices of size 2 × 2 , parameterized by ( d + 1 ) real numbers called the phase factors. This innovative representation of polynomials has a wide range of applications in quantum computation. When the polynomial of interest is obtained by truncating an infinite polynomial series, a natural question is whether the phase factors have a well defined limit as the degree d → ∞ . While the phase factors are generally not unique, we find that there exists a consistent choice of parameterization so that the limit is well defined in the ℓ 1 space. This generalization of QSP, called the infinite quantum signal processing, can be used to represent a large class of non-polynomial functions. Our analysis reveals a surprising connection between the regularity of the target function and the decay properties of the phase factors. Our analysis also inspires a very simple and efficient algorithm to approximately compute the phase factors in the ℓ 1 space. The algorithm uses only double precision arithmetic operations, and provably converges when the ℓ 1 norm of the Chebyshev coefficients of the target function is upper bounded by a constant that is independent of d . This is also the first numerically stable algorithm for finding phase factors with provable performance guarantees in the limit d → ∞ .

Dong, Yulong [Department of Mathematics, Universit↗
DOE OSTI2025

Structure property correlations in wet-spun textile PAN fibers for cost-effective carbon fibers applicable in H 2 storage tank manufacturing

The economic viability of high-strength carbon fibers is pivotal for their integration into Type IV compressed hydrogen storage tanks. Oak Ridge National Laboratory is advancing this objective by developing cost-effective, textile-grade polyacrylonitrile (PAN) precursor fibers through an optimized wet spinning-process to garner more microstructural control over the precursor fibers. Here, this study examines the microstructural characteristics of PAN fibers, particularly the crystalline orientation factor, and their impact on mechanical properties in both precursor and thermally converted carbon fibers (CFs). Three wet-spun PAN fibers, all having diameters of 12-13 µm but varying orientation factors were assessed. Comprehensive characterization using X-ray scattering and microscopy revealed that fibers with higher orientation factors exhibited enhanced crystallinity and optimized crystallite sizes. Mechanical testing demonstrated that the PAN fiber with the highest orientation factor achieved the greatest tensile strength (98 ksi) and modulus (1.60 Msi). Additionally optical and scanning electron microscopy confirmed smooth and defect-free surfaces across all samples. These findings indicate that manipulating spinning parameters to maximize orientation factor is more impactful in achieving high strength and modulus over factors attributed to crystallinity and crystallite sizes. Here, highest performing CFs, thermally processed in lab from textile-grade precursor averaged 558 ksi, a 10% increase over previous results.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Marginal Soils Index Analysis & Geospatial Data

This data package contains output files associated with Mongird et al. (in prep) organized into four dataset directories. Each dataset is described in more detail below. 1. Marginal Soils Index Analysis Description: This folder contains a csv file with land needs and availability by state, power generating technology type, and scenario in 2050 when suitable siting areas are additionally constrained to areas with increasing levels of soil marginality. Files: msi_constrained_siting_availability_2050.csv Variables: Scenario - Projected 2050 scenario name State - US state abbreviation Technology - Generating technology type solar = solar photovoltaic gas_cc_re = natural gas combined cycle (recirculating cooling) wind = onshore wind gas_cc_ccs_re = natural gas combined cycle with carbon capture sequestration (recirculating cooling) gas_cc_dry = natural gas combined cycle with (dry cooling) gas_cc_pond = natural gas combined cycle with (pond cooling) coal_conv_ccs_re = conventional coal with carbon capture sequestration (recirculating cooling) Req_Capacity_MW - The amount of rated capacity required in 2050 of the given technology type in the given state and under the given scenario from the capacity expansion plan Req_Capacity_Factor - The assumed capacity factor (fraction between 0 and 1) for the given technology type in the given state and under the given scenario by the capacity expansion plan Req_Land_km2 - The amount of land required (in km-squared) to host the required generating capacity that is capable of meeting the specified capacity factor for the given technology type in the given state and under the given scenario Req_Energy_TWh - Product of Req_Capacity_MW, Req_Capacity_Factor, and 8760/1e6 for the given technology type in the given state and under the given scenario MSI_Case - The level of MSI that siting the given technology is additionally constrained to, where >0 means siting is additionally constrained to suitable land areas that have an MSI value greater than 0 >=1 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 1 >=2 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 2 >=3 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 3 Soil Attribute Rasters Description: This folder contains geospatial raster files for individual soil parameters upscaled to the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of non-missing 30m resolution values. All raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. Files: avg_cond_raster_ .tif - Average conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm max_cond_raster_ .tif - Maximum conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm min_ph_raster_ .tif- Min pH values across all soil horizons within a depth of 40 inches. avg_ph_raster_ .tif - Average pH value across all soil horizons within a depth of 40 inches. max_ph_raster_ .tif- Max pH value across all soil horizons within a depth of 40 inches. erosion_factor_raster_ .tif - Product of k-factor and percent slope flood_freq_raster_ .tif - Number of months of the year during which the area is commonly, frequently, or very frequently flooded. max_sar_raster_ .tif - Maximum sodium adsorption ratio across all horizons within a depth of 40 inches rock_frac_raster_ .tif - Fraction of the upper 6 inches of soil composed of rock fragments larger than 3 inches. temp_regime_raster_ .tif - Soil temperature regime with the following key: 0 = pergelic 1 = gelic 2 = cryic 3 = frigid 4 = isofrigid 5 = mesic 6 = isomesic 7 = thermic 8 = isothermic 9 = hyperthermic 10 =isohyperthermic Marginal Soils Index Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index at the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of 30m resolution. Both raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. A value of 0 indicates that there were no soil attributes present that indicate marginal soil. NA values indicate that data was unavailable or bodies of water. Files: marginal_soils_index_30m_raster.tif marginal_soils_index_1km_raster.tif Marginal Soils Index Resource Potential Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index + Resource Potential (MSI+RP) score at 1km resolution for geothermal, solar, and wind technologies. Raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. NA values indicate that the location is not suitable for siting the given technology due to policy, environmental, socioeconomic, topological, and other constraints regardless of soil marginality level. Areas with values greater than or equal to zero represent the product of the normalized MSI value and the normalized resource potential value. Files: geothermal_msi_ep_score_raster.tif solar_msi_ep_score_raster.tif wind_msi_ep_score_raster.tif Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Agriculture↗
DOE OSTI2026

Marginal Soils Index Analysis & Geospatial Data

This data package contains output files associated with the Mongird et al. paper entitled "Can US power grid expansion avoid prime agricultural lands?" and is organized into four dataset directories. Each dataset is described in more detail below. 1. Marginal Soils Index Analysis Description: This folder contains a csv file with land needs and availability by state, power generating technology type, and scenario in 2050 when suitable siting areas are additionally constrained to areas with increasing levels of soil marginality. Files: msi_constrained_siting_availability_2050.csv Variables: Scenario - Projected 2050 scenario name State - US state abbreviation Technology - Generating technology type solar = solar photovoltaic gas_cc_re = natural gas combined cycle (recirculating cooling) wind = onshore wind gas_cc_ccs_re = natural gas combined cycle with carbon capture sequestration (recirculating cooling) gas_cc_dry = natural gas combined cycle with (dry cooling) gas_cc_pond = natural gas combined cycle with (pond cooling) coal_conv_ccs_re = conventional coal with carbon capture sequestration (recirculating cooling) Req_Capacity_MW - The amount of rated capacity required in 2050 of the given technology type in the given state and under the given scenario from the capacity expansion plan Req_Capacity_Factor - The assumed capacity factor (fraction between 0 and 1) for the given technology type in the given state and under the given scenario by the capacity expansion plan Req_Land_km2 - The amount of land required (in km-squared) to host the required generating capacity that is capable of meeting the specified capacity factor for the given technology type in the given state and under the given scenario Req_Energy_TWh - Product of Req_Capacity_MW, Req_Capacity_Factor, and 8760/1e6 for the given technology type in the given state and under the given scenario MSI_Case - The level of MSI that siting the given technology is additionally constrained to, where >0 means siting is additionally constrained to suitable land areas that have an MSI value greater than 0 >=1 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 1 >=2 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 2 >=3 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 3 Soil Attribute Rasters Description: This folder contains geospatial raster files for individual soil parameters upscaled to the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of non-missing 30m resolution values. All raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. Files: avg_cond_raster_ .tif - Average conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm max_cond_raster_ .tif - Maximum conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm min_ph_raster_ .tif- Min pH values across all soil horizons within a depth of 40 inches. avg_ph_raster_ .tif - Average pH value across all soil horizons within a depth of 40 inches. max_ph_raster_ .tif- Max pH value across all soil horizons within a depth of 40 inches. erosion_factor_raster_ .tif - Product of k-factor and percent slope flood_freq_raster_ .tif - Number of months of the year during which the area is commonly, frequently, or very frequently flooded. max_sar_raster_ .tif - Maximum sodium adsorption ratio across all horizons within a depth of 40 inches rock_frac_raster_ .tif - Fraction of the upper 6 inches of soil composed of rock fragments larger than 3 inches. temp_regime_raster_ .tif - Soil temperature regime with the following key: 0 = pergelic 1 = gelic 2 = cryic 3 = frigid 4 = isofrigid 5 = mesic 6 = isomesic 7 = thermic 8 = isothermic 9 = hyperthermic 10 =isohyperthermic Marginal Soils Index Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index at the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of 30m resolution. Both raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. A value of 0 indicates that there were no soil attributes present that indicate marginal soil. NA values indicate that data was unavailable or bodies of water. Files: marginal_soils_index_30m_raster.tif marginal_soils_index_1km_raster.tif Marginal Soils Index Resource Potential Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index + Resource Potential (MSIxRP) score at 1km resolution for geothermal, solar, and wind technologies. Raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. NA values indicate that the location is not suitable for siting the given technology due to policy, environmental, socioeconomic, topological, and other constraints regardless of soil marginality level. Areas with values greater than or equal to zero represent the product of the normalized MSI value and the normalized resource potential value. Files: geothermal_msi_rp_score_raster.tif solar_msi_rp_score_raster.tif wind_msi_rp_score_raster.tif Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Agriculture↗
DOE OSTI2026

Are Deep Energy Retrofits in Commercial Buildings Including Window Upgrades?

U.S. Commercial buildings account for about 20% of total U.S. energy consumption. Because the thermal performance of windows significantly affects building energy efficiency and HVAC system performance, best practice guidance often includes window and envelope improvements in conjunction with HVAC upgrades to optimize energy use and improve occupant comfort. It is an open question, however, regarding how often these best practices are implemented in the field. This paper aims to address that gap by conducting a literature review and a series of interviews with commercial building auditing and management professionals to explore the factors that drive window retrofits in commercial buildings. The paper explores a range of case studies from deep energy retrofits across the globe, comparing projects with and without window retrofits. The primary goals of this review are to: (1) provide data from real-world case studies illustrating the role of windows in deep energy renovations and HVAC upgrades, (2) conduct retrofit cost analyses for windows and high-performance HVAC systems and (3) offer insights into how window upgrade decisions are made and when they are implemented as part of deep energy retrofits. Most of the retrofit studies focused exclusively on high performance HVAC upgrades without considering how window upgrades might further enhance the overall energy efficiency of commercial buildings. Interviews with building industry experts shed light on the key factors influencing deep energy retrofit decisions and what factors tip the scales in favor of including window measures with more comprehensive retrofit projects.

Cort, Katherine↗
DOE OSTI2025

Quantum entropy as a harbinger of factorizability

Deeply inelastic scattering (DIS) is a powerful probe for investigating the QCD structure of hadronic matter and testing the standard model (SM). DIS can be described through QCD factorization theorems which separate contributions to the scattering interaction arising from disparate scales — e.g ., with nonperturbative matrix elements associated with long distances and a perturbative hard scattering kernel applying to short-distance parton-level interactions. The fundamental underpinnings of factorization may be recast in the quantum-theoretic terms of entanglement, (de)coherence, and system localization in a fashion which sheds complementary light on the dynamics at work in DIS from QCD bound states. In this Letter, we propose and quantitatively test such a quantum-information theoretic approach for dissecting factorization in DIS and its domain of validity; we employ metrics associated with quantum entanglement such as a differential quantum entropy and associated Kullback-Leibler (KL) divergences in numerical tests. We deploy these methods on an archetypal quark-spectator model of the proton, for which we monitor quantum decoherence in DIS as underlying model parameters are varied. On this basis, we demonstrate quantitatively how factorization-breaking effects may be imprinted on quantum entropies in a kinematic regime where leading-twist factorization increasingly receives large corrections from finite- Q 2 effects; our findings suggest potential applications of quantum simulation to QCD systems and their interactions.

Deep inelastic scattering↗
DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Climatic controls on erosional efficiency vary with lithology across the Himalaya

Although climate can strongly influence erosional efficiency (i.e., erosion rate for a given topography), demonstrating its impact in tectonically active areas has been challenging due to other confounding controlling factors, such as lithology. Here, we show that 10 Be-derived erosion rates and efficiencies in the Himalayan orogen exhibit distinct relationships with climatic factors depending on lithology. We compile 173 10 Be-derived, basin-averaged erosion rates across the orogen, including 12 newly measured rates from the Dibang and Lohit valleys in the easternmost Himalaya, regions characterized by high precipitation magnitudes and variability. We group basins based on lithologies separated by orogen-scale thrust faults and quantify erosional efficiency coefficients based on the relationships between erosion rates and topographic metrics. Our results show that erosion rates and erosional efficiency from sedimentary and metasedimentary rocks along the Himalayan range front display a positive, nonlinear correlation with climatic factors, such as the number of extreme rainfall events and mean annual precipitation rates. In contrast, erosion rates from crystalline lithologies in the hanging wall of the Main Central thrust show a strong correlation with fluvial topography, whereas erosional efficiency shows no statistically significant correlation with climatic factors. Rapid erosion rates and high erosional efficiencies in the eastern Himalayan range front are likely driven by extreme precipitation on tectonically active, steep slopes composed of mechanically weak metasedimentary rocks. Our findings highlight the importance of the interplay between controlling factors, which include tectonics, lithology, and climate, that drive surface erosion and influence the topographic evolution of orogenic systems.

Channel steepness↗
DOE OSTI2025

Machine learning inversion from small-angle scattering for charged polymers

We develop Monte Carlo simulations for uniformly charged polymers and a machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments. The polymer is modeled as a chain of fixed-length bonds, where the connected bonds are subject to bending energy, and there is also a screened Coulomb potential for charge interaction between all joints. The bending energy is determined by the intrinsic bending stiffness, and the charge interaction depends on the interaction strength and screening length. All three contribute to the stiffness of the polymer chain and lead to longer and larger polymer conformations. The screening length also introduces a second length scale for the polymer besides the bending persistence length. To obtain the inverse mapping from the structure factor to these polymer conformation and energy-related parameters, we generate a large data set of structure factors by running simulations for a wide range of polymer energy parameters. We use principal component analysis to investigate the intra-polymer structure factors and determine the feasibility of the inversion using the nearest neighbor distance. We employ Gaussian process regression to achieve the inverse mapping and extract the characteristic parameters of polymers from the structure factor with low relative error.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigating the Impact of Temporal and Directional Traffic Distribution on Crash Frequencies

Safety Performance Functions (SPFs) are mathematical models that establish relationships between the frequency of various crash types and site-specific characteristics, serving as essential tools for traffic safety analysis and roadway design. Traditional SPFs, however, often overlook the temporal fluctuations in traffic flow (such as peak-hour surges) and directional imbalances between opposing traffic streams. These traffic patterns can exacerbate congestion, disrupt driver behavior, and create unexpected conflict points, potentially leading to increased crash frequencies and more severe accidents. In light of this gap, this study aims to explore the potential of incorporating K-factors (representing peak-hour traffic proportions) and D-factors (reflecting the imbalance of directional traffic) into the development of SPFs to assess whether these factors can effectively represent the impact of temporal and spatial traffic distribution on roadway safety. Using crash data from Pennsylvania urban-suburban collector roadways, it is found that the D-factor plays a significant role in predicting the frequency of total crashes, fatal + injury crashes, and angle crashes, with positive coefficient signs indicating that higher directional imbalances correspond to increased crash risks. Similarly, the K-factor emerges as a critical predictor for fatal + injury crashes and rear-end crashes, with negative coefficients suggesting that a more pronounced traffic peak is associated with a reduction in expected crash frequencies. These results highlight the importance of accounting for uneven traffic distribution in both time and direction when developing SPFs, offering deeper insights into crash patterns and supporting more effective safety interventions and roadway designs.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Top-Performing Photovoltaic Cells Compared to the Shockley–Queisser Limit

Top-performing single-junction and two-terminal tandem devices that include at least one polycrystalline cell are compared with each other and their ideal limits. The parameters of open-circuit voltage, short-circuit current, and fill-factor are individually compared to the Shockley–Queisser limit to investigate where different technologies have room to improve. Technologies, such as silicon and cadmium telluride have the most room for improvement in open-circuit voltage currently utilizing 87% and 81% of their maxima, respectively. Detailed diode and fill-factor loss analysis is presented for single-junction devices to give further insight on how they compare and where efficiency is lost. Single-crystal technologies demonstrate a fill-factor closer to the Shockley–Queisser limit than polycrystalline devices. The high diode quality factor of polycrystalline devices is the leading cause of the decreased fill-factor. Similar analysis on tandem cells with at least one thin-film cell shows that although their efficiency exceeds that of the single-junction cells, the fraction of their ideal efficiency is smaller. Here, by comparing parameters to the Shockley–Queisser limit, it becomes clearer where certain technologies have the potential for improvement.

High efficiency↗
DOE OSTI2024

Exploiting bacterial effector proteins to uncover evolutionarily conserved antiviral host machinery

Arboviruses are a diverse group of insect-transmitted pathogens that pose global public health challenges. Identifying evolutionarily conserved host factors that combat arbovirus replication in disparate eukaryotic hosts is important as they may tip the balance between productive and abortive viral replication, and thus determine virus host range. Here, we exploit naturally abortive arbovirus infections that we identified in lepidopteran cells and use bacterial effector proteins to uncover host factors restricting arbovirus replication. Bacterial effectors are proteins secreted by pathogenic bacteria into eukaryotic hosts cells that can inhibit antimicrobial defenses. Since bacteria and viruses can encounter common host defenses, we hypothesized that some bacterial effectors may inhibit host factors that restrict arbovirus replication in lepidopteran cells. Thus, we used bacterial effectors as molecular tools to identify host factors that restrict four distinct arboviruses in lepidopteran cells. By screening 210 effectors encoded by seven different bacterial pathogens, we identify several effectors that individually rescue the replication of all four arboviruses. We show that these effectors encode diverse enzymatic activities that are required to break arbovirus restriction. We further characterize Shigella flexneri-encoded IpaH4 as an E3 ubiquitin ligase that directly ubiquitinates two evolutionarily conserved proteins, SHOC2 and PSMC1, promoting their degradation in insect and human cells. We show that depletion of either SHOC2 or PSMC1 in insect or human cells promotes arbovirus replication, indicating that these are ancient virus restriction factors conserved across invertebrate and vertebrate hosts. Collectively, our study reveals a novel pathogen-guided approach to identify conserved antimicrobial machinery, new effector functions, and conserved roles for SHOC2 and PSMC1 in virus restriction.

59 BASIC BIOLOGICAL SCIENCES↗