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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The electroweak phase transition: a collider target

Determining the thermal history of electroweak symmetry breaking (EWSB) is an important challenge for particle physics and cosmology. Lattice simulations indicate that EWSB in the Standard Model (SM) occurs through a crossover transition, while the presence of new physics beyond the SM could alter this thermal history. The occurrence of a first order EWSB transition would be particularly interesting, providing the needed pre-conditions for generation of the cosmic matter-antimatter asymmetry and sources for potentially observable gravitational radiation. I provide simple, generic arguments that if such an alternate thermal history exists, the new particles involved cannot be too heavy with respect to the SM electroweak temperature, nor can they interact too feebly with the SM Higgs boson. These arguments do not rely on the decoupling limit. I derive corresponding quantitative expectations for masses and interaction strengths which imply that their effects could in principle be observed (or ruled out) by prospective next generation high energy colliders. The simple, generic arguments provide a quantitative, parametric understanding of results obtained in a wide range of explicit model studies; relate them explicitly to the electroweak temperature; and delineate broad contours of collider phenomenology pertaining to a non-standard history of EWSB.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Spatial variation in soil microbial processes as a result of woody encroachment depends on shrub size in tallgrass prairie

Aims: As woody plants encroach into grassland ecosystems, we expect that altered plant-soil interactions will lead to changes in the microbial processes that affect carbon storage and nutrient cycling. Specifically, this research aimed to address how (1) soil chemistry, (2) microbial nutrient demand, and (3) the rate and source of potential soil C mineralization vary spatially under individual woody shrubs of varying size within a mesic grassland. Methods: Here, we collected soil samples from the center, the midpoint between the center and edge, the edge, and the shrub-grass ecotone of multiple Cornus drummondii shrubs across a shrub-size gradient in infrequently burned tallgrass prairie. Results: We found total soil carbon and total soil nitrogen increased with shrub size in every location but the edge. Microbial demand for nitrogen also increased as shrubs increased in size. Across all shrub sizes and sampling locations, potential soil carbon mineralization rates were higher when microbes broke down proportionally more shrub-derived (C 3 ) organic matter than grass-derived (C 4 ) organic matter. Conclusions: Our results suggest that the spatio-temporal context of woody encroachment is critical for understanding its impact on belowground microbial processes. In this ecosystem, a longer period of occupancy by woody plants increases potentially mineralizable carbon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Balancing Impedance and Controllability in Response Reconstruction with $\mathrm{TS-IMMAT}$

In a prior work the authors proposed a variant on the Impedance Matched Multi-Axis Test (IMMAT) in which a fixture is defined, called the Transmission Simulator (TS), and the desired environment is matched at a set of sensors on the TS. If the motion of the TS is matched then the response of the rest of the component will also match, provided that the attached component has the same dynamics as it did when the environment was measured. Hence, one would like the TS to be flexible so that it reproduces the boundary conditions that the component of interest experiences during flight, but the more flexible the TS, the more shakers might be needed to control its response. This work presents a derivation that gives expressions for these two potential error sources in TS-IMMAT. Then, various case studies are presented, both on simulated and real hardware, to understand the importance of each error term in practical testing. The theory explains the phenomena that were observed when using measurements from a component that flew on a sounding rocket. The environmental response was measured and then various fixtures were attached, each comprising more of the next assembly, or the hardware to which the component was attached in flight. MIMO testing was repeated with each fixture and the results were compared to seek to understand the role of the impedance match in this type of testing. Here the results show that the number of modes that are active in the transmission simulator is also very important, and so the best solution balances these two considerations. An improved method of simulating the MIMO test is then proposed, so simulations can be used to predict what fixture, or transmission simulator, will give the best results in a TS-IMMAT test.

42 ENGINEERING↗
DOE OSTI2021

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO 2 ) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO 2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO 2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO 2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

On the viability of stimulated hydrogen generation from iron-rich formations

Hydrogen-based technologies present a promising solution for the global energy transition. In addition to electrolytic production, subsurface geological formations provide a potential natural source of hydrogen. Iron-rich ultramafic rocks, in particular, are favorable for hydrogen generation through natural processes such as serpentinization. Naturally occurring reactions and migration can be enhanced through various types of stimulation, including thermal, hydraulic, and chemical treatment. Through numerical simulations, we analyzed the complex interplay of factors influencing the production and migration within the subsurface, emphasizing the importance of different stimulation techniques, catalysts, and conditions. Our findings indicate that key parameters, such as damage zone permeability and width, significantly impact producible hydrogen mass. Our results indicate that a combination of large damage zone widths, high permeability, and a stimulated reaction rate of 1 × 10 -9 can yield economically viable production rates of up to 1 kg s -1 at the wellhead. Moreover, the availability of ferrous iron, rather than the serpentinization rate itself, has been identified as the primary limiting factor in achieving economically sustainable hydrogen production. In conclusion, while an unstimulated rock volume of 0.165 km 3 yields only 45t of hydrogen in two years, various stimulation techniques can increase production to 18500t.

08 - HYDROGEN↗
DOE OSTI2026

The evolution of coal porosity during pyrolysis

Gasification of coal, municipal waste, or other organic materials is a potential hydrogen source that entails complex thermal decomposition and transport processes. This study provides a multiscale analysis of these processes for sub-bituminous (Usibelli, Healy, Alaska) and lignite (Center, North Dakota) coals and provides data useful for process design. The chemistry, mineralogy, and pore structures of pyrolyzed coal and their evolution with thermal decomposition are discussed. Samples pyrolyzed at 200–1000 °C were analyzed by small-angle neutron scattering; ultra-small, small-, and wide-angle X-ray scattering; and other complementary techniques. Scanning electron microscopy showed new pores in the high-temperature-pyrolyzed material. Upon heating, the coals became progressively denser, and the concentration of hydrogen decreased. Changes in pore volume fell into three temperature ranges: an initial, low-temperature range that, for the Usibelli coal, involved an increase in overall porosity; a mid-temperature range associated with pore volume loss; and a high-temperature range associated with significant porosity increase and char formation. This transformation was paralleled by changes in fractal dimension and correlation length. The higher the pyrolysis temperature the greater the small-pore-volume fraction and overall surface area became. Pyrolysis increased the lateral size of coal crystallites, decreased the amorphous fraction, and increased the aromatics fraction and overall coal rank. Comparisons of neutron and X-ray scattering data and subsequent water uptake studies showed that pre-dried coals can re-hydrate relatively rapidly upon exposure to air, which can significantly affect the porosity calculated from small-angle-scattering data. Fits to the cumulative porosity curves provide a method for modeling the physical and chemical transformation of hydrogen-containing feedstock during gasification.

Anovitz, Lawrence {Larry} [ORNL] (ORCID:0000000226↗
DOE OSTI2020

Machine learning for international freight transportation management: A comprehensive review

Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.

Data sources↗
DOE OSTI2023

Active Thermochemical Tables: Enthalpies of Formation of Bromo- and Iodo-Methanes, Ethenes and Ethynes

Here, the thermochemistry of halocarbon species containing iodine and bromine is examined through an extensive interplay between new Feller–Peterson–Dixon (FPD) style composite methods and a detailed analysis of all available experimental and theoretical determinations using the thermochemical network that underlies the Active Thermochemical Tables (ATcT). From the computational viewpoint, a slower convergence of the components of composite thermochemistry methods is observed relative to species that solely contain first row elements, leading to a higher computational expense for achieving comparable levels of accuracy. Potential systematic sources of computational uncertainty are investigated, and, not surprisingly, spin-orbit coupling is found to be a critical component, particularly for iodine containing molecular species. The ATcT analysis of available experimental and theoretical determinations indicates that prior theoretical determinations have significantly larger uncertainties than originally reported, particularly in cases where molecular spin-orbit effects were ignored. Accurate and reliable heats of formation are reported for 38 halogen containing systems, based on combining the current computations with previous experimental and theoretical work via the ATcT approach.

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

Effect of Solvents on Lignin–Surface Interactions via Molecular Dynamics Simulations

Lignin, an essential building block of lignocellulosic biomass, is a potential abundant source of aromatic monomers for the polymer and chemical industry. Reductive catalytic fractionation (RCF) is one promising process that can produce high yields of phenolic monomers and oligomers from lignin under different catalytic conditions. An important choice in optimizing RCF is the selection of solvent; however, detailed insights into solvent effects on lignin behaviors and interactions remain limited. Here, in this work, we perform all-atom molecular dynamics simulations to study the solvation of lignin, solvent-mediated conformational changes, and the interaction of solvated lignin oligomers with model surfaces. We focus on the behavior of an oligomeric lignin model compound in methanol, ethanol, a binary mixture of ethanol and water, and water at both the RCF reaction temperature (473 K) and room temperature. Analysis of structural features of lignin suggests that these three organic solvent systems favorably solvate lignin, resulting in a more extended conformation suitable for catalytic conversion to valuable chemicals. We further introduce model palladium (Pd) and carbon (C) surfaces to understand how solvent choice impacts adsorption onto a representative catalytic surface and support, and to quantify the competition among the reactant and solvent molecules for the surface. Unbiased simulations suggest strong adsorption of lignin on both Pd and C surfaces at 473 K, with notable solvent-mediated differences in adsorption energies. Additionally, our findings indicate that lignin adsorption is promoted by the entropy change resulting from the displacement of solvent molecules from the surface. This study provides a molecular perspective of adsorption of lignin onto varying surfaces, which is a step towards understanding and optimizing the catalytic conversion of lignin into valuable chemicals.

adsorption↗
DOE OSTI2021

Observation of Single-Electron Transport and Charging on Individual Point Defects in Atomically Thin WSe 2

Defects significantly impact the properties of 2D semiconductors, providing in-gap quantum states that can serve as a natural platform for single-electron operations, localization sites for excitons to serve as single-photon sources, and potentially quantum spin memories. To date, however, a microscopic observation of such a single-electron transport (SET) behavior has been rarely reported on single defects of 2D semiconductors. In this study, we report a SET and charge-state transition on individual point-defect states buried in the bilayer WSe 2 using scanning tunneling microscopy. SET characteristics of their states is evidenced by both the Coulomb staircase and the saturation behavior of the transport current, consistent with the SET model. Furthermore, we demonstrate that, through the local field of a scanning tunneling microscope tip, it is possible to successively charge the defects by single electrons, suggested by both the ring structures and charging peaks in dI/dV measurements. Our results provide new insights into the quantum nature of these defect-bound states, as well as the possibility of using their single-electron behavior and response for applications in quantum information and local-field sensing.

2D semiconductor↗
DOE OSTI2023

Quantum Simulation of Polarized Light-Induced Electron Transfer with a Trapped-Ion Qutrit System

Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. Here this study describes a quantum simulation method that explores the influence of light polarization on electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce quantum dynamics that mimic the electron-transfer dynamics in molecules. We use three-level systems (qutrits), rather than traditional two-level systems (qubits), to enhance the simulation efficiency and realize high-fidelity simulations of electron-transfer dynamics. We treat the quantum interference between the electron coupling pathways from a donor with two degenerate excited states to an acceptor and analyze the transfer efficiency. We also examine the potential error sources that enter the quantum simulations. The trapped-ion systems have favorable scalings with system size compared to those of classical computers, promising access to richer electron-transfer simulations.

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

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. As a result, this approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Bacteria↗
DOE OSTI2024

Adsorption of Neodymium, Dysprosium, and Ytterbium to Goethite under Varying Aqueous Chemistry Conditions

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (<5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (>5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple-layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. An SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. Furthermore, this predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗
DOE OSTI2023

Sterol methyltransferases in uncultured bacteria complicate eukaryotic biomarker interpretations

Abstract Sterane molecular fossils are broadly interpreted as eukaryotic biomarkers, although diverse bacteria also produce sterols. Steranes with side-chain methylations can act as more specific biomarkers if their sterol precursors are limited to particular eukaryotes and are absent in bacteria. One such sterane, 24-isopropylcholestane, has been attributed to demosponges and potentially represents the earliest evidence for animals on Earth, but enzymes that methylate sterols to give the 24-isopropyl side-chain remain undiscovered. Here, we show that sterol methyltransferases from both sponges and yet-uncultured bacteria function in vitro and identify three methyltransferases from symbiotic bacteria each capable of sequential methylations resulting in the 24-isopropyl sterol side-chain. We demonstrate that bacteria have the genomic capacity to synthesize side-chain alkylated sterols, and that bacterial symbionts may contribute to 24-isopropyl sterol biosynthesis in demosponges. Together, our results suggest bacteria should not be dismissed as potential contributing sources of side-chain alkylated sterane biomarkers in the rock record.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A novel d-xylose isomerase from the gut of the wood feeding beetle Odontotaenius disjunctus efficiently expressed in Saccharomyces cerevisiae

Carbohydrate rich substrates such as lignocellulosic hydrolysates remain one of the primary sources of potentially renewable fuel and bulk chemicals. The pentose sugar d-xylose is often present in significant amounts along with hexoses. Saccharomyces cerevisiae can acquire the ability to metabolize d-xylose through expression of heterologous d-xylose isomerase (XI). This enzyme is notoriously difficult to express in S. cerevisiae and only fourteen XIs have been reported to be active so far. We cloned a new d-xylose isomerase derived from microorganisms in the gut of the wood-feeding beetle Odontotaenius disjunctus. Although somewhat homologous to the XI from Piromyces sp. E2, the new gene was identified as bacterial in origin and the host as a Parabacteroides sp. Expression of the new XI in S. cerevisiae resulted in faster aerobic growth than the XI from Piromyces on d-xylose media. The d-xylose isomerization rate conferred by the new XI was also 72% higher, while absolute xylitol production was identical in both strains. Interestingly, increasing concentrations of xylitol (up to 8 g L –1 ) appeared not to inhibit d-xylose consumption. The newly described XI displayed 2.6 times higher specific activity, 37% lower KM for d-xylose, and exhibited higher activity over a broader temperature range, retaining 51% of maximal activity at 30 °C compared with only 29% activity for the Piromyces XI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The effect of differential mineral shrinkage on crack formation and network geometry

Rock, concrete, and other engineered materials are often composed of several minerals that change volumetrically in response to variations in the moisture content of the local environment. Such differential shrinkage is caused by varying shrinkage rates between mineral compositions during dehydration. Using both 3D X-ray imaging of geo-architected samples and peridynamic (PD) numerical simulations, we show that the spatial distribution of the clay affects the crack network geometry with distributed clay particles yielding the most complex crack networks and percent damage (99.56%), along with a 60% reduction in material strength. We also demonstrate that crack formation, growth, coalescence, and distribution during dehydration, are controlled by the differential shrinkage rates between a highly shrinkable clay and a homogeneous mortar matrix. Sensitivity tests performed with the PD models show a clay shrinkage parameter of 0.4 yields considerable damage, and reductions in the parameter can result in a significant reduction in fracturing and an increase in material strength. Additionally, isolated clay inclusions induced localized fracturing predominantly due to debonding between the clay and matrix. These insights indicate differential shrinkage is a source of potential failure in natural and engineered barriers used to sequester anthropogenic waste.

58 GEOSCIENCES↗