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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 91 records · Page 5

Impact of symmetry breaking and spin-orbit coupling on the band gap of halide perovskites

Halide perovskite (HP) materials have recently emerged as a class of semiconductors with immense promise for various optoelectronic applications, ranging from solar cells to light-emitting diodes. One of the unique attributes of HPs is their tunable band gaps with different factors governing their value. Furthermore, the first factor is related to relativistic corrections [“mass-Darwin,” connected to the ns 2 lone pairs, and spin-orbit coupling (SOC)] that induce an orbital shift or degeneracy splitting, resulting in a band-gap reduction. The second factor involves the structural configuration: in HPs the local symmetry of each Wyckoff position tends to be broken, inducing an opening of the band gap. Based on high-throughput density functional theory calculations, this paper systematically studies a possible self-cancelation on the band-gap correction for HPs when the polymorphous configuration—structural effects—and the SOC—electronic effects—are included. Our results indicate that the nature of interplay between SOC and symmetry breaking (SB) is that they are independent decoupling effects to describe the band-gap magnitude in halide perovskites. As a result of that, we observe a transitivity of the band-gap description; i.e., if we know the band gap of halide perovskites without SB and SOC, we can independently add the effects of band-gap reduction due to SOC and band-gap opening due to SB, regardless of the order in which these effects are considered.

14 SOLAR ENERGY↗

EIC Beam Dynamics Challenges

The Electron Ion Collider aims to produce luminosities of 10³⁴ cm⁻²s⁻¹ . The machine will operate over a broad range of collision energies with highly polarized beams. The coexistence of highly radiative electrons and nonradiative ions produce a host of unique effects. Strong hadron cooling will be employed for the final factor of 3 luminosity boost.

43 PARTICLE ACCELERATORS↗

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Fleet Algorithm Design for Pooled Rideshare: Integrating Human Factors, Simulation, and Optimization

This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning strategies were designed and implemented in a simulation environment. Through a series of successive studies, improvements to current rideshare processes were identified, and beneficial outcomes for profitability, accessibility, and traffic were explored. Further, improved metrics to assess rideshare performance were designed and analyzed in the context of improved rideshare offerings. This research contributes to the field of transportation by tackling novel but pragmatic approaches to challenges facing the rideshare industry. Through the course of this dissertation, rideshares impacts on users, operators, and even regulators will be explored in detail. The justification behind the use of a simulation environment, a set of simulated regional models for testing, and the focus on realism and deployability is illustrated. The research identifies holes in potential markets for the use of both private, and public rideshare systems.

Paul, Joseph↗

Development of Methane Emissions Model to Assess Fuel Recovery Potential at Gas Well Sites Using On Site Compression

The U.S. natural gas production and consumption has increased 85.5% since 2005 primarily due to the unconventional production methods of horizontal drilling and hydraulic fracturing. Natural gas used as a fuel has a lower greenhouse gas (GHG) footprint than coal and petroleum due to lower Carbon Dioxide (CO2) emissions when combusted. However, the “greener” benefit to natural gas may be negated by leaks in production and transmission systems. Methane (CH4), the primary hydrocarbon in natural gas, has an estimated Global Warming Potential (GWP) of 28-36 over 100 years, meaning it can absorb 28-36 more energy than CO2 which has a GWP of 1.0. Natural gas well sites are prone to methane emissions, or leaks and irregular gas releases, vented to atmosphere throughout production and transmission. The U.S. Department of Energy (DOE) and the National Energy Technology Laboratory (NETL) has recently granted West Virginia University (WVU) funding under agreement DE-FOA-0002005, to “Advance technologies to mitigate methane emissions and increase the efficiency of the natural gas transportation infrastructure”. As part of this funding WVU was tasked with identifying and quantifying sources of methane emissions at unconventional well sites, processing this data, and developing a system to recapture these emissions. A 0-D Simulink model was developed, utilizing standardized methodologies, data from previously conducted studies, as well as collected data from well sites in the Marcellus shale play region. The model was developed to predict emission rates from various components at natural gas well sites as well as the potential to utilize these emissions as fuel for the natural gas powered compressor engines on-site. This model was utilized to run high, medium, and low cases for four identified emission sources, engine size, pneumatic controller count, liquid level production which dictates tank emissions, and compressor packing vent emissions. Due to discrepancies in transient tank emission data, a high and low emission factor for tanks was used, resulting in two sets of 81 executed cases, and 162 unique cases of total site emissions and potential for fuel consumption. Each of the cases were run over 86,400 seconds at a 1 Hz, representative of a full 24 hour day of operation. The fuel consumption offset an average of 557% of fuel consumption on an energy density basis across all 81 cases with the high tank emission factor with a maximum offset of 2334%. The fuel consumption offset was an average of 82.9% for all 81 cases with the low tank emission factor with a maximum offset of 337%. This study highlights flaws in the use of publicly available methane number calculations to determine natural gas’s suitability as an engine fuel as well as the lack of public data for transient liquid storage tank emissions.

03 NATURAL GAS↗

Electronic Structure and Epitaxy of CdTe Shells on InSb Nanowires

Abstract Indium antimonide (InSb) nanowires are used as building blocks for quantum devices because of their unique properties, that is, strong spin‐orbit interaction and large Landé g‐factor. Integrating InSb nanowires with other materials could potentially unfold novel devices with distinctive functionality. A prominent example is the combination of InSb nanowires with superconductors for the emerging topological particles research. Here, the combination of the II–VI cadmium telluride (CdTe) with the III–V InSb in the form of core–shell (InSb–CdTe) nanowires is investigated and potential applications based on the electronic structure of the InSb–CdTe interface and the epitaxy of CdTe on the InSb nanowires are explored. The electronic structure of the InSb–CdTe interface using density functional theory is determined and a type‐I band alignment is extracted with a small conduction band offset ( ⩽0.3 eV). These results indicate the potential application of these shells for surface passivation or as tunnel barriers in combination with superconductors. In terms of structural quality, it is demonstrated that the lattice‐matched CdTe can be grown epitaxially on the InSb nanowires without interfacial strain or defects. These shells do not introduce disorder to the InSb nanowires as indicated by the comparable field‐effect mobility measured for both uncapped and CdTe‐capped nanowires.

36 MATERIALS SCIENCE↗

Four-derivative corrections to minimal gauged supergravity in five dimensions

We study four-derivative corrections to pure N = 2, D = 5 gauged supergravity. In particular, we find that, up to field redefinitions, there is a single four-derivative superinvariant that one can add to the action, up to factors of the two-derivative action. Consequently, this selects out a unique set of coefficients for the four-derivative corrections. We confirm these coefficients (in the ungauged limit) on the BMPV solution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Agent-based modeling of supply disruptions in the global rare earths market

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military applications and the supply risk associated with China's dominance in their production. We demonstrate the use of Argonne's Global Critical Materials (GCMat) agent-based model to explore the possible consequences to REE market dynamics of different types of regional supply disruptions including a temporary loss of production, shutdown of capacity, and diversion of supply. Results suggest that supply disruptions may foster earlier and more REE mine starts outside of China, although some of these mines may not be able to sustain operations post disruption. Further, price and associated market responses such as production, capacity, and demand tended to extend beyond the disruption period. Such market impacts in the magnet supply chain could affect the costs and availability of a number of emerging clean energy technology applications such as electric vehicles and wind turbines. In the future, GCMat could be used to evaluate the effectiveness of mitigation strategies - including recycling, conservation, product substitution, and diversification of supplies - on reducing the severity of disruptions in REE markets.

36 MATERIALS SCIENCE↗

Impact of salinity origin on microbial communities in saline springs within the Illinois Basin, USA

Abstract Saline springs within the Illinois Basin result from the discharge of deep‐seated evaporated seawater (brine) and likely contain diverse and complex microbial communities that are poorly understood. In this study, seven saline/mineral springs with different geochemical characteristics and salinity origins were investigated using geochemical and molecular microbiological analyses to reveal the composition of microbial communities inhabiting springs and their key controlling factors. The 16S rRNA sequencing results demonstrated that each spring harbours a unique microbial community influenced by its geochemical properties and subsurface conditions. The microbial communities in springs that originated from Cambrian/Ordovician strata, which are deep confined units that have limited recharge from overlying formations, share a greater similarity in community composition and have a higher species richness and more overlapped taxa than those that originated from shallower Pennsylvanian strata, which are subject to extensive regional surface and groundwater recharge. The microbial distribution along the spring flow paths at the surface indicates that 59.8%–94.2% of total sequences in sedimentary samples originated from spring water, highlighting the role of springs in influencing microbiota in the immediate terrestrial environment. The results indicate that the springs introduce microbiota with a high biodiversity into surface terrestrial or aquatic ecosystems, potentially affecting microbial reservoirs in downstream ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Microbial β-glucuronidases drive human periodontal disease etiology

Periodontitis is a chronic inflammatory disease associated with persistent oral microbial dysbiosis. The human β-glucuronidase (GUS) degrades constituents of the periodontium and is used as a biomarker for periodontitis severity. However, the human microbiome also encodes GUS enzymes, and the role of these factors in periodontal disease is poorly understood. Here, we define the 53 unique GUSs in the human oral microbiome and examine diverse GUS orthologs from periodontitis-associated pathogens. Oral bacterial GUS enzymes are more efficient polysaccharide degraders and processers of biomarker substrates than the human enzyme, particularly at pHs associated with disease progression. Using a microbial GUS-selective inhibitor, we show that GUS activity is reduced in clinical samples obtained from individuals with untreated periodontitis and that the degree of inhibition correlates with disease severity. Together, these results establish oral GUS activity as a biomarker that captures both host and microbial contributions to periodontitis, facilitating more efficient clinical monitoring and treatment paradigms for this common inflammatory disease.

59 BASIC BIOLOGICAL SCIENCES↗

Risk Assessment Considerations for Underground Hydrogen Storage in Depleted Gas Reservoirs

Underground hydrogen storage (UHS) in depleted reservoirs presents a promising solution for large-scale energy storage as hydrogen demand grows. As the UHS industry emerges, robust risk assessments are critical to ensuring safe operation of the storage facilities and minimizing the risk of accidents. This work explores risk assessment protocols for underground natural gas storage (UGS) in depleted reservoirs and identifies key considerations for repurposing these facilities for UHS. By examining the differences in physical and chemical properties between hydrogen and natural gas, this work highlights new and modified hazards that merits a reevaluation of traditional natural gas risk assessment practices. This investigation synthesizes insights from previous literature reviews and interviews with UGS industry experts and operators to identify key areas for adapting risk assessment methodologies for hydrogen. The insights gleaned from expert interviews indicate that existing risk assessment standards are non-prescriptive, leading to diverse company-specific risk assessment methodologies requiring substantial additions to become practical. Due to a lack of concrete risk assessment requirements, experience, and relevant data, this uncertainty is expected to be magnified considerably when considering hydrogen. This study identifies several areas for potential modification of existing risk assessment practices that could be considered by those developing standards or performing risk assessments for UHS. Specifically, risk assessments may be improved by including risks unique to hydrogen in existing standards, changing the magnitude of different risk factors in existing risk assessment protocols, and improving methods of data collection and communication across the industry to address large areas of uncertainty.

08 HYDROGEN↗

Developing a Power Plant Suitability Model for the Energy Zones Mapping Tool

This report provides an example of designing, developing, and running a power plant suitability model in the Energy Zones Mapping Tool (EZMT), a public, web-based mapping tool with a large spatial database focused on energy infrastructure, energy resources, and related siting factors. The example focuses on natural gas combined cycle (NGCC) power plants, which have several unique and interesting characteristics. NGCC plants typically provide peaking power to the electrical grid. Such plants can be started or stopped relatively quickly and are often used to supplement base load plants (such as nuclear or coal) during times of peak electrical consumption or to counterbalance lulls in variable power generation (such as wind or solar). Due to these and other factors, NGCC plants have been projected to increase in number under energy planning studies such as Hadley et al. The scope of the Hadley et. al. study is the Eastern Interconnection (EI), the electrical transmission grid serving much of the United States and Canada east of the Rocky Mountains. Results in the study are organized according to 22 Multi-region National—North American Electricity and Environment Model (NEEM) regions within the EI. NGCC plants usually have lower water requirements than other thermoelectric power plants they may replace; therefore, they are expected to have an interesting role in reducing the overall water requirements of energy generation.

20 FOSSIL-FUELED POWER PLANTS↗

Exclusive QCD Factorization and Single Transverse Polarization Phenomena at High-Energy Colliders

This Ph.D. thesis is divided into two distinct parts. The first part focuses on hard exclusive scattering processes in Quantum Chromodynamics (QCD) at high energies, while the second part delves into spin phenomena at the Large Hadron Collider (LHC). Hard exclusive scattering processes play a crucial role in QCD at high energies, providing unique insights into the confined partonic dynamics within hadrons, complementing inclusive processes. Studying these processes within the QCD factorization approach yields the generalized parton distribution (GPD), a nonperturbative parton correlation function that offers a three-dimensional tomographic parton image within a hadron. However, the experimental measurement of these processes poses significant challenges. This thesis will review the factorization formalism for related processes, examine the limitations of some widely used processes, and introduce two novel processes that enhance the sensitivity to GPD, particularly its dependence on the parton momentum fraction x. The second part of the thesis centers on spin phenomena, specifically single spin production, at the LHC. Noting that a single transverse polarization can be generated even in an unpolarized collision, this research proposes two new jet substructure observables: one for boosted top quark jets and another for high-energy gluon jets. The observation of these phenomena paves the way for innovative tools in LHC phenomenology, enabling both precision measurements and the search for new physics.

Yu, Zhite↗

Other Power Reactor Fuels

While oxide fuels have received the bulk of historic interest as power reactor fuels, a range of other uranium compounds and deployment architectures have also been considered and demonstrated to varying degrees. Metal alloys, technical ceramics, and oxycarbide or oxynitride particle fuels are candidates for various power reactor applications. Although in general these families of nuclear fuels have received more limited study than oxides, the benefits of uranium density, favorable thermophysical properties, and other factors have resulted in interest from both the traditional nuclear power industry as well as more recent entrepreneurial efforts. The dominant fuel chemistry issues for these fuel forms differ substantially from those of oxide systems. Synthesis routes, factors that affect fresh fuel properties, and critical aspects of fuel performance are unique to these systems and often dominated by the desired chemical behavior of uranium in each system. This chapter will briefly introduce metallic uranium alloys, specifically uranium-zirconium, non-traditional ceramic fuels such as carbides and nitrides, and oxycarbide/oxynitride particle fuels most familiar as the basis for TRISO fuel designs. A survey of major fuel chemistry issues is provided for each of these families of fuels, with a focus on contemporary challenges and active research avenues.

Nelson, Andrew↗

Predicting transcription factor activity using prior biological information

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

59 BASIC BIOLOGICAL SCIENCES↗

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

On Rank Selection for Nonnegative Matrix Factorization

Rank selection, i.e. the choice of factorization rank, is the first step in constructing Nonnegative Matrix Factorization (NMF) models. It is a long-standing problem which is not unique to NMF, but arises in most models which attempt to decompose data into its underlying components. Since these models are often used in the unsupervised setting, the rank selection problem is further complicated by the lack of ground truth labels. In this paper, we review and empirically evaluate the most commonly used schemes for NMF rank selection.

Eswar, Srinivas [Argonne National Laboratory]↗

Convection in Scaled Turbine Internal Cooling Passages With Additive Manufacturing Roughness

Abstract Additive manufacturing processes, such as direct metal laser sintering (DMLS), enable the creation of novel turbine cooling internal passages and systems. However, the DMLS method produces a significant and unique surface roughness. Previous work in scaled passages analyzed pressure losses and friction factors associated with the rough surfaces, as well as investigated the velocity profiles and turbulent flow characteristics within the passage. In this study, the heat transfer characteristics of scaled additively manufactured surfaces were measured using infrared (IR) thermography. Roughness panels were CNC machined from plates of aluminum 6061 to create near isothermal roughness elements when heated. Fluid resistance differences between the aluminum roughness panels and roughness panels constructed from ABS plastic using the same roughness patterns from McClain et al. (2020, “Flow in a Simulated Turbine Blade Cooling Channel With Spatially Varying Roughness Caused by Additive Manufacturing Orientation,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-16069) were investigated. Finally, the overall thermal performance enhancements and friction losses were assessed through the calculation of surface averaged “global thermal performance” ratios. The global thermal performance characterizations indicate results in-line with those found for traditional commercial roughness and slightly below traditional internal passage convection enhancement methods such as swirl chambers, dimples, and ribs. The passages investigated in this study do not include compressibility effects or the long-wavelength artifacts and channel geometric deviations observed by Wildgoose et al. (2020, “Impact of Additive Manufacturing on Internal Cooling Channels with Varying Diameters and Build Directions,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-15049). However, the results of this study indicate that, based on the roughness augmentation alone, artificial convective cooling enhancers such as turbulators or dimples may still be required for additively manufactured turbine component cooling.

Engineering↗