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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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85 records · Page 5

Understanding spectral dependance of laser-induced damage precursors in dielectric materials (Full report_23-ERD-006)

The performance of high-energy laser systems is constrained by laser-induced damage in dielectric coatings, particularly those containing hafnium oxide (HfO 2 ). While thresholds at fundamental Nd harmonics are well studied, the spectral dependence of damage initiation—especially under dual-wavelength irradiation—remains poorly characterized. This project provides the first systematic investigation of wavelength-dependent laser damage in hafnia coatings, focusing on nanoscale precursors such as craze lines, nanobubbles, stoichiometric variations, nodules, and controlled crystallization. Coatings were fabricated via ion beam sputtering and electron-beam deposition and characterized using spectrophotometry, ellipsometry, AFM, GI-XRD, RBS, PCI absorption, and fs/ns laser damage testing. Results show that craze lines, benign under infrared light, strongly initiate damage under UV due to wavelength-selective field intensification. Substituting xenon for argon suppresses nanobubbles and improves UV thresholds by up to 32%. Oxygen modulation reveals that fully oxidized films maximize UV resistance, though at the cost of porosity and stress in multilayers. HfO 2 –SiO 2 composites resist crystallization and defects while achieving ppm-level absorption and elevated thresholds, whereas full crystallization of HfO 2 enhances LIDT by reducing defects and improving thermal transport. Collectively, these findings link photon energy, defect states, and bandgap collapse, providing a predictive framework for wavelength-dependent laser damage. The outcomes directly inform the design of durable, multi-wavelength coatings for facilities such as NIF, MEC, HAPLS, and DPAL, advancing the readiness of next-generation optics.

36 MATERIALS SCIENCE↗

Transverse Kinematic Imbalance in MicroBooNE's New nue CC0pi Measurements

Neutrino-nucleus cross section measurements require accurate modelling of neutrino interactions. Neutrino beams are not monoenergetic, and the energy of each interaction must instead be modelled using nuclear interaction assumptions. This introduces significant systematic uncertainty into cross section measurements. Effects such as Fermi motion, nuclear correlations, and final-state interactions (FSI) smear the underlying quasi-elastic scattering signal, making it difficult to disentangle genuine quasi-elastic kinematics from nuclear effects across the full range of interaction channels (QE, MEC, RES, DIS) probed in these measurements. Transverse Kinematic Imbalance (TKI) variables, such as $\delta p_T$ and $\delta \alpha_T$, probe this same phase space by exploiting the fact that the incoming neutrino has zero transverse momentum ($\vec{p}_T^{\,\nu} = 0$). Any measured transverse imbalance in the final state therefore arises from nuclear effects rather than from uncertainty in the incident neutrino energy, allowing cross section measurements to select a phase space that is rich in quasi-elastic-like events with minimal contamination from FSI and other nuclear effects, independent of energy reconstruction. Recent unfolded MicroBooNE cross section measurements of electron-neutrino charged-current interactions with zero pions and at least one proton ($\nu_e$ CC0$\pi$, 1eNp0$\pi$) show that several leading nuclear interaction generators (including GENIE variants, NuWro, GiBUU, and NEUT) reproduce the differential cross section in electron energy reasonably well, but consistently struggle to describe the differential cross section in the cosine of the leading proton's angle, yielding lower $p$-values across all seven generators tested. This tension points to a more fundamental, kinematics-driven disagreement between data and generators that is not visible in energy-only cross section observables. This is precisely the regime TKI variables are designed to probe. Following previous TKI cross section measurements with muon-neutrino data in MicroBooNE, this poster presents the case for extending the TKI framework to electron-neutrino cross section measurements as a next step to isolate and characterize the source of the observed generator tension in proton kinematics.

Burridge, Jessica [U. Manchester (main)] (ORCID:00↗

Studies of Localization Effects on Transverse Kinematic Imbalance in the GENIE Generator

The forthcoming Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE and other Fermilab-based experiments as a central value model for neutrino-nucleus cross sections, exhibits known discrepancies in comparison to MicroBooNE cross section data, especially when considering neutrino scattering events' transverse kinematic imbalance (TKI). For quasielastic-like measurements, the data show a larger transverse missing momentum tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous attempts at a solution include variations of final-state interaction (FSI) strengths, incorrectly decreasing both the peak and tail, thus leaving the discrepancy unresolved. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. In this work, GENIE FSI routines have been modified to directly utilize intranuclear particle positions, thereby introducing a newly localized momentum treatment in correlation with the nominal density in both the hA and hN intranuclear cascade models for their 2018 and 2025 variants. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear nucleons' ("scattering center") momentum and its radial dependence validate the localization implementation. However, while such consistent localization produces modest changes in the proton momentum spectrum at low-to-medium momenta, only small changes are observed in the TKI distributions. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved by such a solution.

Bulla, Braden [Ctr. Coll., Danville; Fermilab]↗

Localized Interactions in Neutrino Simulations

The Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE, exhibits a known discrepancy with MicroBooNE measurements of transverse kinematic imbalance (TKI): the data display a larger high-TKI tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous variations of final-state interaction (FSI) strength affected both the peak and the tail and therefore did not resolve the discrepancy. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. The GENIE FSI routines were modified to use the particle position when generating nucleons, thereby introducing a local-density treatment in the hA and hN intranuclear models for their 2018 and 2025 implementations. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear scattering-center momentum and its radial dependence confirm that the localization was implemented as intended. Localization produces modest changes in the proton momentum spectrum, primarily at low momentum, but only a small change in the TKI distribution between approximately \SI{0.25}{\giga\electronvolt} and \SI{0.40}{\giga\electronvolt}. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved.

Bulla, Braden [Unlisted, US, IL]↗

Identification of Exported Plasmodium falciparum Proteins That Bind to the Erythrocyte Cytoskeleton

Plasmodium proteins are exported to the erythrocyte cytoplasm to create an environment that supports parasite replication. Although hundreds of proteins are predicted to be exported through Plasmodium export element (PEXEL)-dependent and -independent mechanisms, the functions of exported proteins are largely uncharacterized. In this study, we used a biochemical screening approach to identify putative exported P. falciparum proteins that bound to inside-out vesicles prepared from erythrocytes. Out of 69 P. falciparum PEXEL-motif proteins tested, 18 bound to inside-out vesicles (IOVs) in two or more independent assays. Using co-affinity purifications followed by mass spectrometry, pairwise co-purification experiments, and the split-luciferase assay, we identified 31 putative protein–protein interactions between erythrocyte cytoskeletal proteins and predicted exported P. falciparum proteins. We further showed that PF3D7_1401600 binds to the spectrin-binding domain of erythrocyte ankyrin via its MESA erythrocyte cytoskeleton binding (MEC) motif and to the N-terminal domains of ankyrin and 4.1R through a fragment that required an intact Plasmodium helical interspersed sub-telomeric (PHIST) domain. Introduction of PF3D7_1401600 into erythrocyte ghosts increased retention in the microsphiltration assay, consistent with previous data that reported a reduction of rigidity in red blood cells infected with PF3D7_1401600-deficient parasites.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement of $d^2 \sigma/d|\vec{q}|d E_{avail}$ and 2p2h contribution using charged current $\nu_\mu$ interactions in the NOvA Near Detector

This Thesis presents the analysis methods and measurement of the $d^2 \sigma/d|\vec{q}|d E_{avail}$-CC inclusive cross section that describes neutrino scattering in a predominantly hydrocarbon medium. Studies that are prerequisite for the analysis including, variable determinations, event selections, efficiency, purity determinations, and systematic uncertainty estimations, are summarized. Tests of the analysis are also detailed, and shown to reproduce the input distributions. The double-differential cross-section measurement provides the foundation for determination of the inclusive rate for the excess induced by 2p2h processes together with nuclear medium effects that are not described by the Fermi gas model. The methodology for the extraction of this rate, defined as the excess observed relative to the rate estimated for known single-nucleon interactions, is described in detail. The following new measurements are reported in this Thesis: (1) The $\nu_\mu-$CC inclusive double-differential cross section as a function of three-momentum transfer and available hadronic energy, for an average $E_\nu$ of 1.8 GeV, is obtained. The double-differential cross section value that obtains when the bin widths are taken to be the dimensions of the entire analysis domain, e.g. $0.2 \le |\vec{q}| \le 2.0 GeV/c$ and $0.0 \le E_{avail} \le 2.0$ GeV, is inclusive cross section is $(6.05 \pm 0.75)\times10^{-39}$ cm$^2$/GeV/GeV/$c$/nucleon. An event excess attributed to 2p2h-MEC processes is observed; most of the rate occurs in a contiguous phase space region $0.3 \le |\vec{q}| \le 1.0$ GeV$/c$ $0.0 \le E_{avail} \le 0.35$ GeV. This rate represents $12.0\pm 6.5\%$ of the observed CC inclusive cross section; its cross section ratio relative to CCQE scattering is estimated to be $44.3 \pm 23.9\%$.

Olson, Travis Grant↗

BioHydrogen (BioH2) Consortium to Advance Fermentative H2 Production

The overall objective of this project is to develop a carbon-neutral, microbial dark fermentation technology to convert waste lignocellulosic biomass into H2 with a production cost less than $2/kg-H2 via strain engineering, bioprocess design for scale-up, and integrating fermentation with microbial electrolysis cell (MEC).

bioH2↗

BioHydrogen (BioH2) Consortium to Advance Fermentative H2 Production

The overall objective of this project is to develop a carbon-neutral, microbial dark fermentation technology to convert waste lignocellulosic biomass into H2 with a production cost less than $2/kg-H2 via strain engineering, bioprocess design for scale-up, and integrating fermentation with microbial electrolysis cell (MEC).

bioH2↗

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗

A study of the 2H(e, e ' p)X reaction at large 4-momentum transfers and high missing momenta

The short-range region (r < 1 fm) of the nucleon-nucleon potential may be studied via deuteron electro-disintegration. Such an experiment was done at Hall C of Jefferson Lab at 4-momentum transfers of Q^2 = 4.07 (GeV/c)^2 and reaching missing momenta up to 900 MeV/c. At such settings, complications arising from Meson Exchange Currents (MEC) and Isobar Currents are expected to be signifi cantly minimized, as well as Final State Interactions (FSI) at recoiling angles of ¿_Xq ~ 40 deg. This makes comparisons of experimental and theoretical cross sections less model dependent. A luminosity study was done to determine the reduction of liquid deuterium targets with increasing beam current. A 2.8% in the charge yield was found between 0 to 70 µA. Electron scattering from the walls of the target chamber was determined to be negligible, but caution was taken by considering scattering events away from the walls. A neutron was found to be contained in the missing mass spectrum for each missing momentum setting. Extraction of the deuteron total cross section is still on going.

Love, Shawn [California State Univ. (CalState), Lo↗

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Circular Perspective for Utilization of Industrial Wastewaters via Phytoremediation

Wastewater generated in municipal rendering facilities requires multi-step treatment, but it may also serve as a source of nutrients and water and thus may be valorized before or instead of the necessary wastewater treatment operations. In this work, wastewaters from a composting plant were utilized to support the growth of Miscanthus x giganteus, known as both a remediation plant and an energy biomass source. A pot experiment was established to compare the effects of different wastewater doses (0, 50, 100, and 200 mL per pot per week) on the miscanthus biomass yield, phytoextraction of heavy metals, biomass heat of combustion, and plant condition. The increase in the wastewater dose resulted in increases in both biomass yield (from about 44 to 139%) and biomass heat of combustion (from 7 to 17%) when compared to the control sample, with no adverse effects on plant physiological parameters. The highest concentrations of metals were found in miscanthus grown with the highest dose of wastewaters. It was found that higher wastewater dose correlates to both higher phytoextraction and phytorecovery of metals from plant substrate and wastewaters. The highest metal uptake was identified for Fe (431 mg·pot −1 ), followed by Al, Zn, Mn, Cu, Ni, Cr. The lowest metal uptake was noted for Pb, Co and Cd (0.88, 0.11, and 0.95 mg·pot −1 , respectively). The results indicate that miscanthus can be recommended for industrial wastewater treatment. In addition, due to high absorption efficiency of the substrate components, miscanthus can be used as a remediation tool, e.g., for the ecological stabilization of remediation of metal-polluted soils, especially in municipal facilities like rendering plants. This presents a circular perspective for the valorization of post-fermentation wastewaters with subsequent growth of energy crops, with other potential benefits for the environment, such as soil treatment, absorption of CO 2 , and air purification.

Miscanthus x giganteus↗