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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Savannah River Site High Level Radioactive Waste Tank Sample Thermolytic Hydrogen Generation - 20346

To support the revision of flammability calculations and controls for the Savannah River Site (SRS) High-Level Radioactive Waste (HLW) tanks, Savannah River National Laboratory (SRNL) conducted laboratory measurements with the goal of quantifying hydrogen produced in HLW by non-radiolytic chemical reactions (i.e., thermolysis). Testing was performed with HLW tank supernate samples that represented a cross section of types of waste at SRS, including tanks that store typical evaporator concentrate, dissolved salt-cake, dilute recycle stream from the Defense Waste Processing Facility (DWPF), evaporator concentrate of the recycle stream from DWPF, fresh waste from the canyon separations facility, and waste that has been through salt processing cesium removal. Non-radioactive simulant testing included the classes of organic compounds historically introduced into the HLW tanks that were recently shown to be the most active toward the thermolytic generation of hydrogen. The reaction rate equations developed for thermolytic hydrogen generation from each class of organic compound showed direct proportionality to organic compound concentration and hydroxide concentration. Simulant testing identified that highly concentrated waste with high hydroxide concentration had the highest rates of thermolytic hydrogen generation. Using the radioactive tank sample thermolysis measurements at high temperatures and the mechanistic salt dependence of the simulant models, a global model was developed for tank waste thermolytic hydrogen generation as a function of total organic carbon content of SRS HLW. Through the primary functionality of the global model (organic carbon and free hydroxide concentration), the relative reactivity of the organic carbon in the waste was quantified. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Likelihood-Based Particle Identification in the Short-Baseline Near Detector

Accurate particle identification is crucial in any high-energy physics experiment, allowing scientists to understand the unique interactions and mechanisms at play in a detector. In this project, I develop and study a new particle identification (PID) algorithm for the Short-Baseline Near Detector, a likelihood-based approach, different from out current $\chi^2$ method. A likelihood estimation offers a more physically motivated strategy for PID. The distribution random energy losses of charged particles traveling through a medium are described by the Vavilov probability density function. By using this model, we can account for random energy losses and construct likelihood functions specific to each particle type, potentially enabling a more accurate method for PID.

Vanderwaal, Sophia [U. Alabama, Huntsville] (ORCID↗
DOE OSTI2025

Thermal Hydraulics Analysis of a Divertor Monoblock Using SALAMANDER

Divertors are critical components in magnetic confinement fusion devices. One of the Divertor's crictial roles is absorbing the highest heat flux from the plasma. The Divertor accomplishes this through the use of divertor monoblocks and cooling channels. This work presents a thermal hydraulic analysis of a divertor monoblock using the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering and Research (SALAMANDER). SALAMANDER is an open source tool developed at Idaho National Laboratory for conducting multiphysics and multscale analysis of Plasma Facing Components (PFCs). For the monoblock, solid heat conduction is modeled in the block with a constant heat flux of 1E7 W/m^2 applied to the top of the block to represent peak heat flux from the plasma. The cooling channel (which is pressurized water at a Reynolds number of ~1,000,000) is modeled using a k-epsilon turbulence model with standard wall functions. The heat transfer between the solid and fluid domain is modeled using the Dittus-Boelter correlation for the convective heat transfer coefficient. This work aims to show the importance of a multiphysics modeling approach when performing simulations on PFCs.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture

Abstract Background and Aims Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies. Methods We utilize the functional–structural plant model ‘OpenSimRoot’ to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources. Key Results Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these. Conclusions While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Evidence for a genetic basis in functional trait tradeoffs with microbial growth rate but not growth yield

Tradeoffs in microbial functional traits have been a focus of recently described ecological frameworks and of mathematical models of microbial community functioning. Tradeoffs in key traits such as growth rate, growth yield, resource acquisition, and stress tolerance may have either a genetic basis or a physiological basis, and the type of tradeoff can inform how traits are modeled and measured. Here we provide evidence that growth rate/decomposition and growth rate/stress tolerance tradeoffs have a primarily genetic basis in a phylogenetically diverse suite of ten leaf litter-inhabiting fungi. In contrast, growth yield tradeoffs with functional traits are more likely to have a physiological basis. Consideration of the type of tradeoff, genetic or physiological, should help to inform efforts to model microbial contributions to ecosystem processes, especially when considering different scales. Consideration of physiological tradeoffs may be important for understanding short-term variability (e.g., pulse events) and fine spatial scales, whereas genetic tradeoffs are likely to be useful for understanding regional- to continental-scale and medium- to long-term contributions of microbes to ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Non-Destructive, Three-Dimensional Imaging of Processes in the Rhizosphere Utilizing High Energy Photons

Soil structure, which can be described as the aggregation and distribution of pore spaces, regulates carbon, nutrient, and water cycling across the Earth system. Yet the inability to make quantitative, dynamic, in situ measurements of soil structure and rhizosphere carbon flow has prevented meaningful incorporation of soil structural processes into Earth System Models (ESMs). The key limitations are: (i) Lack of scale integration between micron-scale soil structure and ecosystem-scale models, (ii) Poor functional linkage between soil structural properties and biogeochemical processes, and (iii) Absence of dynamic 3D measurements of rhizosphere structural changes and carbon transformations. To address these challenges, we developed a new integrated positron emission tomography (PET) - microcomputed tomography (CT) imaging platform that enables the first 4D (spatial 3D and time), non-invasive, quantitative imaging of carbon allocation and rhizosphere structural dynamics in living plants and intact soils. The system combines: • Rhizo-PET (R-PET): a high-resolution positron emission tomography scanner optimized for 11 CO 2 tracing in plant roots. • a-Se micro-CT: a high-contrast, high-spatial resolution CT system based on amorphous selenium (a-Se) direct conversion technology, enabling micron-scale visualization of soil structure and root–soil interfaces. Together, these advances allow us to quantify how carbon exudates move, transform, and stabilize within the rhizosphere, directly informing missing processes in BER-relevant carbon cycle models.

42 ENGINEERING↗
DOE OSTI2021

CPT2 downregulation triggers stemness and oxaliplatin resistance in colorectal cancer via activating the ROS/Wnt/β-catenin-induced glycolytic metabolism

Highlights: • CPT2 was downregulated in CRC. • CPT2 suppressed the proliferation and glycolytic metabolism in CRC cells. • CPT2 inhibited cancer stem cell properties and oxaliplatin resistance in CRC. • CPT2 attenuated CRC tumor growth and enhanced oxaliplatin sensitivity in vivo. • CPT2 functioned via suppressing ROS/Wnt/β-catenin pathway in CRC. Carnitine palmitoyltransferase 2 (CPT2) has been demonstrated to act as a tumor promotor or suppressor in different types of cancers. However, little is known about the effect of CPT2 on colorectal cancer (CRC). In the present study, we analyzed CPT2 expression in CRC tissues and cells. CPT2 was overexpressed in CRC cell lines (SW480 and RKO), and its effects and molecular mechanism on the proliferation, glycolysis, stemness, and oxaliplatin sensitivity were investigated. The xenograft experiment was used to confirm the influence of CPT2 on CRC tumorigenesis in vivo. We found that CPT2 expression was significantly downregulated in CRC patients, and its lower expression was associated with the poor prognosis, large tumor size, advanced TNM stage, and poor histological grade differentiation of patients. Upregulation of CPT2 significantly inhibited the proliferation, glycolytic metabolism, cancer stem cell properties, and oxaliplatin resistance in CRC cells. Also, the increase of CPT2 inhibited tumorigenesis, stemness and glycolysis, while enhanced oxaliplatin sensitivity in mouse models. Mechanistically, CPT2 functioned via suppressing the activation of Wnt/β-catenin pathway through repressing ROS production. In conclusion, our results demonstrated that CPT2 was decreased in CRC, and CPT2 downregulation could trigger stemness and oxaliplatin resistance in CRC via activating the ROS/Wnt/β-catenin-induced glycolytic metabolism. This study indicates that CPT2 is a potential therapeutic target for CRC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Probing thermodynamics of radiogenic helium and defects in $δ$-plutonium alloys and interactions with adsorbed environmental gases

Differential scanning calorimetry coupled with simultaneous evolved gas analysis (DSC-EGA) on aged δ-Pu samples shows that most radiogenic helium remains trapped within the Pu matrix at temperatures very close to, or slightly above, the melting temperature. Our results indicate that helium release from 50-year-old δ-Pu occurs as a burst just below the melting temperature (>0.994 T m ), with subsequent pressure oscillations as temperature increases. Subordinate quantities of H 2 were also released along with helium. Here, the helium emission tails off and ceases above ~720 – 750°C. In a δ-Pu alloy aged 6 years, the initial helium burst occurs slightly above melting (~1.015 – 1.042 T m ), with a discrete, larger helium spike occurring between 670 and 686°C. The proximity of helium release to the liquidus transition presented challenges in the deconvolution of overlapping process enthalpies, the liquidus endotherm, and the exotherm resulting from bubble collapse, annealing and gas expulsion. Helium’s strong affinity for vacancy binding in a 2He-vac configuration is predicted by Density Functional Theory (DFT) modeling. The measured stored energy associated with the He release events in a 50-year-old δ alloy is on the order of ~ 10–11 J/g, which is significantly higher than stored energies measured in the sub-solidus regimes (~2 J/g) that are related to the solid-state annealing of processing- and radiation-induced defects. This implies that aged δ Pu alloys have a remarkable resilience to accommodate the lattice strain produced by the internal pressure of the helium bubbles and provides further insight into the thermodynamic behavior of aged δ Pu.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Doped Mott insulators in the triangular-lattice Hubbard model

Here we investigate the evolution of the Mott insulators in the triangular lattice Hubbard Model, as a function of hole doping δ in both the strong and intermediate coupling limits. Using the advanced density matrix renormalization group (DMRG) method, at light hole doping δ ≲ 10%, we find a significant difference between strong and intermediate couplings. Notably, at intermediate coupling an unusual metallic state emerges, with short ranged spin correlations but long ranged spin-chirality order. Moreover, no clear Fermi surface or wave vector is observed, this chiral metal also exhibits staggered loop current, which breaks the translational symmetry. These features disappear on increasing interaction strength or on further doping. At strong coupling, the 120 degree magnetic order of the insulating magnet persists for light doping, and produces hole pockets with a well-defined Fermi surface. On further doping, δ ≈ 10%~20% SDW order and coherent hole Fermi pockets are found at both strong and intermediate couplings. At even higher doping δ ≳ 20%, the SDW order is suppressed and the spin-singlet Cooper pair correlations are simultaneously enhanced. We also briefly comment on the strong particle-hole asymmetry of the model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Energy-peak based method to measure top quark mass via B -hadron decay lengths

We develop a method for the determination of the top quark mass using the distribution of the decay length of the B -hadrons originating from its decay. This technique is based on our earlier observation regarding the location of the peak of the b quark energy distribution. Such “energy-peak” methods enjoy a greater degree of model-independence with respect to the kinematics of top quark production compared to earlier proposals. The CMS experiment has implemented the energy-peak method using associated b -jet energy as an approximation for b quark energy. The new method uses B -hadron decay lengths, which are related to b quark energies by convolution. The advantage of the new decay length method is that it can be applied in a way that evades jet-energy scale (JES) uncertainties. Indeed, CMS has measured the top quark mass using B -hadron decay lengths, but they did not incorporate the energy-peak method. Therefore, mismodeling of top quark transverse momentum remains a large uncertainty in their result. We demonstrate that, using energy-peak methods, this systematic uncertainty can become negligible. We show that with the current LHC data set, a sub-GeV statistical uncertainty on the top quark mass can be attained with this method. To achieve a comparable systematic uncertainty as is true for many methods based on exclusive or semi-inclusive observables using hadrons, we find that the quark-hadron transition needs to be described significantly better than is the case with current fragmentation functions and hadronization models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The impact of $γN$ and $γ^∗N$ interactions on our understanding of nucleon excitations

We review recent progress in our understanding of the nucleon excitation spectrum. Thanks to dedicated efforts at facilities such as ELSA, MAMI and Jefferson Lab, several new nucleon resonances have been discovered, and evidence for previously elusive states has been significantly improved. Numerous decay channels have been observed for the first time, and resonance properties are being extracted from these data by several groups through coupled-channel analyses of varying complexity. Electroproduction experiments have provided further insights into the internal structure of light baryon resonances – for example, the long-debated Roper resonance N (1440) is observed as a three-quark state with a significant meson-cloud component. While the non-relativistic quark model remains a valuable tool for organizing the spectrum of nucleon and Δ resonances, a variety of theoretical frameworks have emerged to offer deeper understanding, including phenomenological quark models, holographic QCD, functional methods, effective field theories, and lattice QCD. We examine the interplay between these approaches, highlight their respective strengths and explore how they complement each other in shaping our knowledge of light baryon resonances. We address several open questions in baryon spectroscopy, including the nature of the enigmatic Λ (1405), ongoing searches for exotic states such as hybrid baryons and pentaquarks, and the dichotomy between microscopic descriptions of baryons in terms of quarks and gluons versus effective hadronic descriptions based on meson-baryon dynamics.

Baryon resonances↗
DOE OSTI2022

Modeling the hydrodynamic impact on the tool influence function during hemispherical subaperture optical polishing

To fabricate high-precision and accurate optics relative to the optical design surface, a high level of deterministic control of material removal (i.e., the tool influence function, TIF) during subaperture tool polishing is required. In this study, a detailed analysis of the pressure distribution, which is a key component of the TIF, has been performed using finite element analysis to couple together solid mechanics and fluid dynamics. Modeling experimental parameters of recently published work reveals that, when considering tool deformation, which in turn influences the fluid film thickness between the tool and workpiece, the effective pressure profile has a flat-top distribution. This flat-top pressure profile differs from the parabolic pressure distributions predicted by Hertzian mechanics. Furthermore, the shear contribution is shown here to be a key contributor to material removal, inducing the removal at the periphery of the contact edge and even outside the generally accepted contact area. Finally, the simulated fluid velocities provide evidence of mixed-mode contact polishing, supporting recent experimental findings that also suggest that onset of hydroplaning contributions lead to material removal drop-off.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Weak Form Scientific Machine Learning: Test Function Construction for System Identification

Weak form Scientific Machine Learning (WSciML) is a recently developed framework for data-driven modeling and scientific discovery. It leverages the weak form of equation error residuals to provide enhanced noise robustness in system identification via convolving model equations with test functions, reformulating the problem to avoid direct differentiation of data. The performance, however, relies on wisely choosing a set of compactly supported test functions. In this work, we mathematically motivate a novel data-driven method for constructing Single-scale-Local reference functions for creating the set of test functions. Our approach numerically approximates the integration error introduced by the quadrature and identifies the support size for which the error is minimal, without requiring access to the model parameter values. Through numerical experiments across various models, noise levels, and temporal resolutions, we demonstrate that the selected supports consistently align with regions of minimal parameter estimation error. We also compare the proposed method against the strategy for constructing Multi-scale-Global (and orthogonal) test functions introduced in our prior work, demonstrating the improved computational efficiency.

FOS: Computer and information sciences↗
DOE OSTI2020

Land Use in Computable General Equilibrium Models

Constant Elasticity of Transformation (CET) functions are widely used to allocate land across uses in Computable General Equilibrium (CGE) models. These models fail to maintain area of land in balance. Several ways have been used or offered to fix this problem. This paper first examines the extent to which the CET approach may generate imbalances in area of land and identifies determinants of such imbalances. It then evaluates the merits, properties, and welfare impacts of the available approaches that restore area of land in balance. We show that heterogeneity in land prices (land rents) is the main source of imbalance in area of land, not the curvature of the CET function. Furthermore, we show that the available approaches that restore area of land in balance either introduce ad hoc adjustments in land allocation or undermine the conventional welfare assessments of the CET results and ignore the opportunity costs of land transformation. The CGE models which applied stochastic productivity distribution functions to allocate land among uses maintain area of land in balance, but they suffer from important limitations and ignore costs of land transformation.

Taheripour, Farzad↗
DOE OSTI2020

Combining Computational Modeling with Reaction Kinetics Experiments for Elucidating the In Situ Nature of the Active Site in Catalysis

Microkinetic modeling based on density functional theory (DFT) derived energetics is important for addressing fundamental questions in catalysis. The quantitative fidelity of microkinetic models (MKMs), however, is often insufficient to conclusively infer the mechanistic details of a specific catalytic system. Here, this can be attributed to a number of factors such as an incorrect model of the active site for which DFT calculations are performed, deficiencies in the hypothesized reaction mechanism, inadequate consideration of the surface environment under reaction conditions, and intrinsic errors in the DFT exchange-correlation functional. Despite these limitations, we aim at developing a rigorous understanding of the reaction mechanism and of the nature of the active site for heterogeneous catalytic chemistries under reaction conditions. By achieving parity between experimental and modeling outcomes through robust parameter estimation and by ensuring coverage-consistency between DFT calculations and MKM predictions, it is possible to systematically refine the mechanistic model and, thereby, our understanding of the catalytic active site in situ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Using projection operators with maximum overlap methods to simplify challenging self-consistent field optimization

Maximum overlap methods are effective tools for optimizing challenging ground- and excited-state wave functions using self-consistent field models such as Hartree-Fock and Kohn-Sham density functional theory. Nevertheless, such models have shown significant sensitivity to the user-defined initial guess of the target wave function. Here in this work, a projection operator framework is defined and used to provide a metric for non-aufbau orbital selection in maximum-overlap-methods. The resulting algorithms, termed the Projection-based Maximum Overlap Method (PMOM) and Projection-based Initial Maximum Overlap Method (PIMOM), are shown to perform exceptionally well when using simple user-defined target solutions based on occupied/virtual molecular orbital permutations. This work also presents a new metric that provides a simple and conceptually convenient measure of agreement between the desired target and the current or final SCF results during a calculation employing a maximum-overlap method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hepatocellular Metabolic Profile: Understanding Post-Thawing Metabolic Shift in Primary Hepatocytes In Vitro

Primary human hepatocytes (PHHs) are widely used as in vitro models for liver function and drug metabolism studies, yet their metabolic stability post-thawing remains an open question. To better characterize early metabolic changes, we conducted a time-course experiment using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze metabolic shifts in PHHs cultured in suspension. Unexposed and exposed (acetaminophen-treated) samples were evaluated, and TITAN analysis was applied to determine the time point of maximal metabolic change at both individual metabolite and global metabolic profile levels. Our results indicate that the majority of metabolic shifts occur within the first five hours post-thawing. In the early culture time points, substantial metabolic overlap was observed between unexposed and exposed cells, suggesting a conserved biological response likely related to cellular recovery. However, at later time points, metabolite profiles diverged, with acetaminophen treatment-specific metabolic changes emerging, potentially reflecting differences in homeostatic restoration versus hepatotoxic responses. Our study highlights the importance of considering early post-thawing metabolic dynamics in experimental design and offers insights for optimizing hepatocyte culture protocols to better replicate in vivo physiological conditions.

59 BASIC BIOLOGICAL SCIENCES↗