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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Computationally Selected Multivalent HIV-1 Subtype C Vaccine Protects Against Heterologous SHIV Challenge

Background: The RV144 trial in Thailand is the only HIV-1 vaccine efficacy trial to date to demonstrate any efficacy. Genetic signatures suggested that antibodies targeting the variable loop 2 (V2) of the HIV-1 envelope played an important protective role. The ALVAC prime and protein boost follow-up trial in southern Africa (HVTN702) failed to show any efficacy. One hypothesis for this is the greater diversity of subtype C viruses in southern Africa relative to CRF01_AE in Thailand. Methods: Here, we determined whether an ALVAC prime with computationally selected gp120 boost immunogens maximizing coverage of diversity of subtype C viruses in the variable V1 and V2 regions (V1V2) improved the protection of non-human primates (NHPs) from a heterologous subtype C SHIV challenge compared to more traditional regimens. Results: An ALVAC prime with Trivalent subtype C gp120 boosts resulted in statistically significant protection from repeated intrarectal SHIV challenges compared to the control. Evaluation of the immunogenicity of each vaccine regimen at the time of challenge demonstrated that different gp120 combination boosts elicited similar high magnitudes of gp120 and breadth of V1V2-binding antibodies, as well as strong Fc-mediated immune responses. Low-to-no neutralization of the challenge virus was detected. A Cox proportional hazard analysis of five pre-selected immune parameters at the time of challenge identified ADCC against the challenge envelope as a correlate of protection. Systems serology analysis revealed that immune responses elicited by the different vaccine regimens were distinct and identified further correlates of resistance to infection. Conclusions: Computationally designed vaccines with maximized subtype C V1V2 coverage mediated protection of NHPs from a heterologous Tier-2 subtype C SHIV challenge.

Immunology↗

DOE OSTI2023

Search for a Grotthuss mechanism through the observation of proton transfer

The transport of protons is critical in a variety of bio- and electro-chemical processes and technologies. The Grotthuss mechanism is considered to be the most efficient proton transport mechanism, generally implying a transfer of protons between ‘chains’ of host molecules via elementary reactions within the hydrogen bonds. Although Grotthuss proposed this concept more than 200 years ago, only indirect experimental evidence of the mechanism has been observed. Here we report the first experimental observation of proton transfer between the molecules in pure and 85% aqueous phosphoric acid. Employing dielectric spectroscopy, quasielastic neutron, and light scattering, and ab initio molecular dynamic simulations we determined that protons move by surprisingly short jumps of only ~0.5–0.7 Å, much smaller than the typical ion jump length in ionic liquids. Our analysis confirms the existence of correlations in these proton jumps. However, these correlations actually reduce the conductivity, in contrast to a desirable enhancement, as is usually assumed by a Grotthuss mechanism. Furthermore, our analysis suggests that the expected Grotthuss-like enhancement of conductivity cannot be realized in bulk liquids where ionic correlations always decrease conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Thermal hydraulic analysis of the AFIP-7 irradiation test in the Advanced test Reactor – Model correlation and performance evaluation

We report as a system level code, RELAP5 is widely used in the nuclear field for the reactor hydraulic analysis. In the component/experimental level, it is frequently employed as well. This paper demonstrates that the RELAP5 flow simulation of the AFIP-7 irradiation experiment which has a complicated 3D geometry/flow path deviates by ~28% from the flow evaluation through a computational fluid dynamics (CFD) simulation, which has been validated against a flow test performed at Oregon State University. Thermal safety compliance analysis of an experiment planned to be irradiated in the Advanced Test Reactor is usually performed using the finite element analysis code, Abaqus. This research reveals the disadvantages of the Abaqus simulation in the flow instability and departure from nucleate boiling evaluations via a conjugate heat transfer analysis of the AFIP-7 irradiation experiment. As a result, a detailed CFD simulation is suggested for irradiation experiments with complicated flow paths, rather than a simplified RELAP5 simulation or hand calculations. The validated simulation approach will be integrated with the Boehmite correlations to investigate the oxide growth prediction on the fuel cladding in Part II of this research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Dataset_for_Conserved_macromolecular_architecture_of_Poplar_secondary_cell_walls_revealed_by_ssNMR_and_atomistic_modeling

This dataset contains solid-state 13C NMR data and atomistic molecular dynamics simulation files supporting the study of nanoscale secondary cell wall architecture across 13 genetically diverse Populus trichocarpa genotypes grown under uniform greenhouse conditions in 13C-enriched CO2 atmospheres (~89% 13C enrichment).The dataset contains two collections of solid-state 13C NMR data. (1) 200 MHz data (Bruker Avance III HD, 4 mm HX probe, 10 kHz MAS): raw Bruker TopSpin experiment folders and DMFIT-exported ascii spectra for selective and non-selective 1D 13C-13C spin diffusion experiments (3000 ms mixing) used to quantify inter-polymer spatial proximities, and short-mixing (1 ms) reference spectra used for polymeric abundance quantification by spectral deconvolution. (2) 600 MHz data (Bruker Avance III, 1.6 mm PhoenixNMR HXY probe, 30 kHz MAS): raw Bruker TopSpin experiment folders containing 2D CORD, 2D CP-INADEQUATE, and 13C/1H relaxation (T1, T1rho) experiments for all 13 genotypes, with processed Excel workbooks per experiment type. Molecular dynamics simulation code, coordinate files, and analysis scripts (NAMD/CHARMM/Python) for six atomistic cell wall models are included. Summarized ssNMR data are compiled into a single excel file and subjected to statistical analysis. Multivariate analysis code (PCA, Pearson correlation) and summary data are provided as excel worksheets and Jupyter notebooks (Python 3).

09 BIOMASS FUELS↗

DOE OSTI2022

Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysis

Thomson scattering measurements in high energy density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an important and sometimes the dominant source of measurement uncertainty. In this paper, we present a formal method of accounting for the presence of streak camera noise in our measurements. We present a phenomenological description of the noise generation mechanisms and present a statistical model that may be used to construct the covariance matrix associated with a given measurement. This model is benchmarked against simulations of streak camera images. We demonstrate how this covariance may then be used to weight fitting of the data and provide quantitative assessments of the uncertainty in the fitting parameters determined by the best fit to the data and build confidence in the ability to make statistically significant measurements in the low-signal regime, where spatial correlations in the noise become apparent. These methods will have general applicability to other measurements made using optical streak cameras.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Core Mass Estimates in Strong Lensing Galaxy Clusters Using a Single-halo Lens Model

The core mass of galaxy clusters is an important probe of structure formation. Here we evaluate the use of a single-halo model (SHM) as an efficient method to estimate the strong lensing cluster core mass, testing it with ray-traced images from the Outer Rim simulation. Unlike detailed lens models, the SHM represents the cluster mass distribution with a single halo and can be automatically generated from the measured lensing constraints. In this work we find that the projected core mass estimated with this method, $M_{\text{SHM}}$, has a scatter of 8.52% and a bias of 0.90% compared to the "true" mass within the same aperture. Our analysis shows no systematic correlation between the scatter or bias and the lens-source system properties. The bias and scatter can be reduced to 3.26% and 0.34%, respectively, by excluding models that fail a visual inspection test. We find that the SHM success depends on the lensing geometry, with single giant arc configurations accounting for most of the failed cases due to their limiting constraining power. When excluding such cases, we measure a scatter and bias of 3.88% and 0.84%, respectively. Finally, we find that when the source redshift is unknown, the model-predicted redshifts are overestimated, and the $M_{\text{SHM}}$ is underestimated by a few percent, highlighting the importance of securing spectroscopic redshifts of background sources. Our analysis provides a quantitative characterization of $M_{\text{SHM}}$, enabling its efficient use as a tool to estimate the strong lensing cluster core masses in the large samples, expected from current and future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Sixteen multiple-amplifier sensing charge-coupled devices and characterization techniques targeting the next generation of astronomical instruments

We present a candidate sensor for future spectroscopic applications, such as a Stage-5 Spectroscopic Survey Experiment or the Habitable Worlds Observatory. This type of charge-coupled device (CCD) sensor features multiple in-line amplifiers at its output stage allowing multiple measurements of the same charge packet, either in each amplifier or in the different amplifiers. Recently, the operation of an eight-amplifier sensor has been experimentally demonstrated, and we present the operation of a 16-amplifier sensor. This new sensor enables a noise level of ∼1 erms− with a single sample per amplifier. In addition, it is shown that sub-electron noise can be achieved using multiple samples per amplifier. In addition to demonstrating the performance of the 16-amplifier sensor, we aim to create a framework for future analysis and performance optimization of this type of detectors. New models and techniques are presented to characterize specific parameters, which are absent in conventional CCDs and Skipper CCDs: charge transfer between amplifiers and independent and common noise in the amplifiers and their processing.

16 multiple-amplifer sensing CCD (MAS-CCD)↗

DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Examining the Impact of Local Constraint Violations on Energy Computations in DFT

ABSTRACT This work examines the impact of locally imposed constraints in Density Functional Theory (DFT). Using a metric referred to as the extent of violation index (EVI), we quantify how well exchange‐correlation functionals adhere to local constraints. Applying EVIs to a diverse set of molecules for GGA functionals reveals constraint violations, particularly for semi‐empirical functionals. We leverage EVIs to explore potential connections between these violations and errors in chemical properties. While no correlation is observed for atomization energies, a significant statistical correlation emerges between EVIs and total energies. Similarly, the analysis of reaction energies suggests weak positive correlations for specific constraints. However, definitive conclusions about error cancellation mechanisms cannot be made at this time. These observations revealed by EVIs may be useful for consideration when designing future generations of semilocal functionals.

Khanna, Vaibhav [Department of Chemistry Universit↗

DOE OSTI2024

Measurement of ambient radon progeny decay rates and energy spectra in liquid argon using the MicroBooNE detector

We report measurements of radon progeny in liquid argon within the MicroBooNE time projection chamber (LArTPC). The presence of specific radon daughters in MicroBooNE’s 85 metric tons of active liquid argon bulk is probed with newly developed charge-based low-energy reconstruction tools and analysis techniques to detect correlated Bi 214 − Po 214 radioactive decays. Special datasets taken during periods of active radon doping enable new demonstrations of the calorimetric capabilities of single-phase neutrino LArTPCs for β and α particles with electron-equivalent energies ranging from 0.1 to 3.0 MeV. By applying Bi 214 − Po 214 detection algorithms to data recorded over a 46-day period, no statistically significant presence of radioactive Bi 214 is detected, and a limit on the activity is placed at < 0.35 mBq / kg at the 95% confidence level. This bulk Bi 214 radiopurity limit—the first ever reported for a liquid argon detector incorporating liquid-phase purification—is then further discussed in relation to the targeted upper limit of 1 mBq / kg on bulk Rn 222 activity for the DUNE neutrino detector. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Strongly Anharmonic Phonons and Their Role in Superionic Diffusion and Ultralow Thermal Conductivity of Cu 7 PSe 6

We report the quest for advanced superionic materials requires understanding their complex atomic dynamics, but detailed studies of the interplay between lattice vibrations and ionic diffusion remain scarce. Here inelastic and quasielastic neutron scattering measurements in the superionic argyrodite Cu 7 PSe 6 are reported, combined with molecular dynamics (MD) based on ab initio and machine-learned potentials, providing critical insights into the atomistic mechanisms underlying fast ion conduction. The results reveal how long-range Cu diffusion is limited by intercluster hopping, controlled by selective anharmonic phonons of the crystalline framework. Further, the Green–Kubo simulations reproduce the ultralow lattice thermal conductivity and identify contributions from mobile ions, phonons, and their cross-correlations. The mode resolved analysis shows that the thermal conductivity is dominated by low-energy acoustic phonon modes of the overall crystal framework. The analysis of mode-resolved spectral functions further show that vibrational modes with significant Cu contributions are strongly damped, corresponding to the breakdown of associated phonon quasiparticles. These results highlight the importance of strongly anharmonic effects in superionic systems, in which the traditional quasiharmonic phonon picture is insufficient, and pave the way toward combining machine-learning accelerated simulations with neutron scattering experiments to rationalize the complex atomic dynamics underlying ionic and thermal transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Gallium‐Doping Effects on Structure, Lithium‐Conduction, and Thermochemical Stability of Li 7‐3 x Ga x La 3 Zr 2 O 12 Garnet‐Type Electrolytes

Abstract One of the most promising electrolytes for all‐solid‐state lithium batteries is Li 7 La 3 Zr 2 O 12 . Previously, their thermodynamic stability, Li‐ion conductivity, and structural features induced by Ga‐doping have not been empirically determined or correlated. Here, their interplay was examined for Li 7−3 x Ga x La 3 Zr 2 O 12 with target x Ga=0, 0.25, 0.50, 0.75, and 1.00 atoms per formula unit (apfu). Formation enthalpies, obtained with calorimetry and found to be exothermic at all compositions, linearly decreased in stability with increased x Ga. At dilute x Ga substitution, the formation enthalpy curve shifted stepwise endothermically, and the conductivity increased to a maximum, coinciding with 0.529 Ga apfu. This correlated with percolation threshold analysis (0.558 Ga apfu). Further substitution (0.787 Ga apfu) produced a large decrease in the stability and conductivity due to a large increase in point defects and blocked Li‐migration pathways. At x Ga=1.140 apfu, a small exothermic shift was related to defect cluster organization extending the Li hopping distance and decreased Li‐ion conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Cover crops and poultry litter impact on soil structural stability in dryland soybean production in southeastern United States

Abstract This study explored the efficacy of soil aggregate indices in quantifying soil structural development, utilizing 5‐year field experiment data from the Southeastern United States. The experiment utilized a split‐plot design with cover crops (native vegetation as control, cereal rye (Secale cerealeL.), winter wheat (Triticum aestivum), hairy vetch (Vicia villosa), and mustard (Brassica rapa) plus cereal rye as the main factor and fertilizer source (no fertilizer as control, inorganic fertilizer with phosphorus, potassium, and elemental sulfur, and poultry litter) as the secondary factor. Aggregate size fractions were determined using the wet‐sieving method, and aggregate stability index (ASI), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (FD) were calculated to assess soil structural stability. Main effects results indicated that cereal rye (55.11%) and poultry litter (50.97%) exhibited the highest ASI values. The highest MWD, GMD, and FD were observed under mustard plus cereal rye (1.187 mm), cereal rye (0.462 mm), and hairy vetch (2.573), respectively. Principal component analysis revealed that cover crops significantly improved soil aggregate structure and stability, overcoming limitations of sole fertilization practices. Regression analysis suggested that ASI, MWD, and GWD positively correlated with soil organic carbon, whereas FD negatively correlated with MWD, GMD, and ASI. Principal component analysis exhibited that FD decreased with increasing soil organic carbon, ASI, MWD, and GMD, demonstrating that lower FD values indicate enhanced soil aggregation and structure. Assessed indices, FD included, effectively gauged soil structural stability. These metrics should be prioritized in managerial decisions to support soil productivity and health in agricultural systems.

Agriculture↗

DOE OSTI2022

Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City

In addition to global and regional drivers of urbanization, neighborhood development in urban areas across the United States has been shown to be influenced by various local socio-economic factors. These factors, despite varying across socio-economic groups, have large implications regarding a population’s vulnerability to extreme climate events, including heat waves resulting in adverse health impacts. Additionally, the demographics of an urban area can shape its infrastructural characteristics, causing different populations groups to face varying levels of risks and benefits. As a result, the urban morphology and socio-economic characteristics of a city are deeply intertwined; however, their interactions on a finer scale are not yet fully understood. This research aims to better understand the relationships between various socio-economic factors and the built environment of a city, considering variability in building types, and temperature patterns. This research focuses on the city of Las Vegas, NV, and uses spatial data analysis to understand the correlation between of socio-economic characteristics, building morphology, building characteristics, and temperature data to understand the correlation between these various factors. Results of these research shows there is a distinct pattern of clustering of socio-economic characteristics with the city and there is a distinct correlation between age and cost, socio-economic characteristics, and locations of high heat distribution within the city.

Singh, Ridhima↗

DOE OSTI2022

Analysis of the CP structure of the Yukawa coupling between the Higgs boson and τ leptons in proton-proton collisions at $\sqrt{s}$ = 13 TeV

The first measurement of the CP structure of the Yukawa coupling between the Higgs boson and τ leptons is presented. The measurement is based on data collected in proton-proton collisions at s√ = 13 TeV by the CMS detector at the LHC, corresponding to an integrated luminosity of 137 fb -1 . Our analysis uses the angular correlation between the decay planes of τ leptons produced in Higgs boson decays. The effective mixing angle between CP-even and CP-odd τ Yukawa couplings is found to be -1 ± 19°, compared to an expected value of 0 ± 21° at the 68.3% confidence level. The data disfavour the pure CP-odd scenario at 3.0 standard deviations. The results are compatible with predictions for the standard model Higgs boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Landscape composition and configuration have scale-dependent effects on agricultural pest suppression

Increasing landscape heterogeneity (composition and configuration) can enhance natural enemy populations and support pest suppression in agricultural landscapes. Using a network-based data mining approach, we examined independent gradients of landscape composition and configuration at six spatial scales that were associated with pest suppression services measured at 32 sites in Michigan and Wisconsin, USA. We compared the relative effects of landscape composition and configuration across scales with those of local crop type (corn or grassland). We found that multiple gradients of configurational heterogeneity were independent of composition and strongly associated with pest suppression, with different configuration metrics being predictive of pest suppression depending on the spatial scales and regions considered. Landscapes that were more configurationally heterogeneous at smaller spatial scales consistently supported higher pest suppression. In Michigan, pest suppression increased in landscapes with high edge contrast between annual crops and surrounding habitats and high edge density of grassland within 250-500 m radii. In Wisconsin, pest suppression increased with large core area of grassland and high field density within a 250 m radius. The main compositional effect we found was a positive relationship between grassland cover and pest suppression occurring at larger spatial scales (1000-1500 m) and occurring in Wisconsin but not in Michigan. Our findings demonstrate that effects of landscape composition and configuration on pest suppression differ across spatial scales and vary regionally. The network-based data mining techniques used here could be useful for disentangling intercorrelated landscape metrics in a variety of other contexts in landscape ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Ab-initio investigation of the effect of adsorbed salts on segregation of Cr at the Ni (100) surface

The dissolution and depletion of chromium (Cr) in salt facing nickel (Ni) alloy surfaces is one of the predominant degradation mechanisms of structural components in molten salt technology. Here, we use density functional theory to investigate the role of electronic level interactions that may underlie the depletion phenomenon of Cr in a Ni (100) surface exposed to various adsorbed salt species. Our results show that, under vacuum, Ni preferentially segregates to the surface layer. Conversely, in the presence of adsorbed anionic salt species (e.g., chlorine (Cl), fluorine (F) or the impurity oxygen (O)) Cr segregation becomes more favorable. In these cases, Cl has the weakest effect on segregation, while O has the strongest effect. Our analysis reveals the strong correlation between Cr segregation and the amount of valence charge transferred between the Cr atom and surface adsorbate: the greater the charge transfer, the lower the segregation energy. We also show that, when considered, secondary cations screen Cr-anion interactions, which in turn reduce the magnitude of the anions effect on segregation. These results shed light on the role of salt impurities likely play in the overall corrosion phenomena in molten salt environments. This work provides insights into the atomic level interactions fundamental to molten salt corrosion and on the importance of maintaining salt purity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

High-pressure ignition delay time measurements of a four-component gasoline surrogate and its high-level blends with ethanol and methyl acetate

Ignition delay times of a gasoline surrogate (iso-octane/toluene/n-heptane/1-hexene at 55/25/15/5% by liquid volume, developed in McCormick et al. 2017) with high-level bioblendstock-gasoline surrogate blends (50% and 85% biofuel by liquid volume of each ethanol and methyl acetate) were collected behind reflected shock waves. Post-reflected-shock temperatures ranged from 968 to 1361 K at pressures of about 4, 10, 25, and 50 atm. Data were collected for real fuel–air mixtures at fuel lean and stoichiometric conditions (φ = 0.5, 1.0) with focus on the more-practical, fuel-lean conditions. Ignition delay times were measured from OH* chemiluminescence around 307 nm using an endwall diagnostic. The RON and MON of the surrogate were 90.3 and 84.7, respectively. Ethanol was chosen due to its wide use in flex-fuel vehicles and availability, while also providing an increased octane rating. Methyl acetate was chosen for its especially high octane rating to investigate the effect of an extreme case. To validate the gasoline surrogate, the data are compared to real gasoline (RD387) and several gasoline surrogate experiments from the literature. Using the wide range of pressures studied, the gasoline surrogate’s pressure dependence was quantified to account for test-to-test variations using regression analysis. Similarly, a global correlation for gasoline and its surrogates was developed using all available data from the literature. Two modern chemical kinetics models targeting gasoline and its surrogates are compared to the ignition delay time measurements. These new high-pressure, high-bioblendstock concentration tests provide required chemical kinetic data for optimizing fuel and engine design.

42 ENGINEERING↗