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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

MESOSCALE THERMAL TRANSPORT MEASUREMENTS OF MULTI-PHASE AND POROUS NUCLEAR FUELS USING A SQUARE-WAVE PULSE THERMOREFLECTANCE TECHNIQUE

The safe and efficient operation of nuclear reactors require accurate knowledge of peak temperatures in the fuel assemblies. The temperature profiles are governed by the thermal transport properties of the fuel, namely the thermal conductivities (k) and thermal diffusivities (D). These values can be very difficult to measure as they are known to vary considerably from the measured bulk values of the fresh fuel, and quickly degrade with increasing burnup [1 -3] . Laser-based techniques have been effectively used for non-destructive and non-contact thermal transport measurements of a wide variety of materials, including nuclear materials [4-6] that would otherwise prove too hazardous or difficult to measure otherwise. In this study, a new thermoreflectance technique known as square-pulse transient thermoreflectance (SPTR) is described and used to determine the mesoscale thermal diffusivity of both uranium sesquisilicide (U3Si2) and uranium nitride (UN) phases in a composite fuel with micron level spatial resolution [7]. This technique employs a rapid train of square-wave pulses from an excitation laser to create a periodic heat flux on a gold coated sample surface. Surface adsorption results in transient film temperatures and hence rapid fluctuations in thermoreflectance that can be measured via a detection laser coupled with a digital oscilloscope. The lasers are coaxially focused on the sample surface, allowing for a sample measurement area of a single convolved laser spot size (~2 µm). A sensitivity analysis was conducted to identify key measurement parameters of this technique using reference materials with a range of thermal conductivities comparable to those of both ceramic, composite, and metal nuclear fuel types (1.4 – 27.2 W/m-K). The reference materials were measured using the new technique as well as a spatial-domain thermoreflectance technique (SDTR) previously reported for a comparison [8]. Additionally, measurements of several U3Si2 and UN phase regions of a polished UN/U3Si2 (70/30 vol.%) sample were taken, and the resulting calculated D values are reported, with both techniques showing excellent agreement between samples. This technique was used to scan a multiphase region at 5 micron increments to generate a local diffusivity map, demonstrating the utility of the techniques for measuring thermal transport properties in specimens with precipitates and secondary phases. Furthermore, the technique is currently being applied to measure thermal properties of Fast Flux Test Reactor (FFTR) irradiated metal fuel specimens whose porous microstructure make it very difficult to measure using other techniques. Comparison of the local scale measurements are compared with the pre-irradiated fuel samples to show the degradation of thermal transport in fuels due to pores from fission gas bubbles and other irradiation induced defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Evidence of Buried Junctions in CdSeTe Absorbers

The introduction of selenium band gap gradients has been shown to be a promising path for improving CdTe devices. Controlling maximum selenium concentration during deposition should allow for better device performance. In this work cross-section electron beam induced current (EBIC) maps were measured for CdSeTe/CdTe devices with as-grown selenium concentration between 0 and 20 percent. Measured EBIC profiles show high collection in the middle of the absorber layer, which differs from past EBIC studies of CdSe/CdTe devices. Increasing as-deposited selenium concentrations resulted in increased collection at this mid-absorber location. Combined with a 2-dimensional numerical model, these results suggest a buried homo-junction in the absorber layer of the device. This buried junction may be associated with a number of composition dependent parameters including electron affinity and p-dopability. Understanding this collection profile and its implications for device performance may be key in optimizing CdSeTe/CdTe devices.

CdSeTe↗
DOE OSTI2021

Systems Biology to Improve Camelina Seed and Oil Quality Traits (Final Report)

Camelina has great potential to become a sustainable high energy-yielding source of biofuel in the US. This project aims to address two critical needs for realizing this potential: to increase seed size and oil content for improved seedling establishment and oil yield, and to optimize oil quality for satisfactory fuel properties. Specifically, quantitative trait loci (QTL) and molecular markers associated with these important traits will be identified using high-density genome maps and repeated field trials in Montana and Washington states. Modern genomics and biotechnological approaches will be employed to uncover novel molecular mechanisms (including genes and gene networks regulated by microRNAs and transcription factors) regulating fatty acid modification, oil accumulation and seed size in Camelina.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The User Guide for the ComPro Database

An extensive database of glass composition and durability data has been compiled at Savannah River National Laboratory to support the development of nuclear waste glasses. This database is referred to as the Glass Composition-Properties Database (ComPro). The ComPro Database, Revision 3, contains 14,134 total rows of data and 125 columns of composition, durability, as defined by the Product Consistency Test, and other fabrication and characterization information, if available, for each glass. Of the 14,134 total rows, 8,484 rows have been classified as “Model” data and 5,650 rows have been classified as “Non-Model” data. An integral supplement to the ComPro database is the User Guide. The User Guide was developed as a tool to aid the End User in a more effective use of the ComPro database. The User Guide provides a road-map of the specific datasets that comprise the ComPro database (both “Model” and “Non-Model” data) as well as a technical basis for the terminology and definitions the End User will encounter. In this report, a general description of the format and information contained in the User Guide is provided. In addition, specific terminology used in the User Guide is also discussed.

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

Reactivity of Shale to Supercritical CO 2 : Insights from Microstructural Characterization and Mineral Phase Evolution in Caney Shales for CCUS Applications

Understanding mineral–fluid interactions in shale under supercritical CO 2 (scCO 2 ) conditions is relevant for assessing long-term geochemical containment. This study characterizes mineralogical transformations and elemental redistribution in five Caney Shale samples serving as proxies for reservoir (R1, R2, R3) and caprock (D1, D2) facies, subjected to 30-day static exposure to pure scCO 2 at 60 °C and 17.23 MPa (2500 psi), with no brine or impurities introduced. SEM-EDS analyses were conducted before and after exposure, with mineral phases classified into silicates, carbonates, sulfides, and organic matter. Initial compositions were dominated by quartz (38–47 wt.%), illite (16–23 wt.%), carbonates (12–18 wt.%), and organic matter (8–11 wt.%). Post-exposure, carbonate loss ranged from 15 to 40% in reservoir samples and up to 20% in caprock samples. Illite and K-feldspar showed depletion of Fe 2+ , Mg 2+ , and K + at grain edges and cleavages, while pyrite underwent oxidation with Fe redistribution. Organic matter exhibited scCO 2 -induced surface alteration and apparent sorption effects, most pronounced in R2 and R3. Elemental mapping revealed Ca 2+ , Mg 2+ , Fe 2+ , and Si 4+ mobilization near reactive interfaces, though no secondary mineral precipitates formed. Reservoir samples developed localized porosity, whereas caprock samples retained more structural clay integrity. The results advance understanding of mineral reactivity and elemental fluxes in shale-based CO 2 sequestration.

geochemical CO2 sequestration↗
DOE OSTI2020

High-yield growth kinetics and spatial mapping of single-walled carbon nanotube forests at wafer scale

Emerging commercial applications of vertically aligned, single-walled carbon nanotube (SWCNT) “forests” require synthesis that minimizes nanotube diameter while maximizing number density across substrate areas exceeding centimeter scale. To address this need, we synthesized SWCNT forests on full silicon wafers with notable reproducibility and uniformity, and co-optimized growth for small diameters and high densities across large areas to access new territory in this 3D parameter space. We mapped the spatial uniformity of key structural features using Raman microscopy, synchrotron X-ray scattering, and Rutherford backscattering spectrometry. Low C 2 H 2 flux over sub-nm Fe/Mo catalysts produced small-diameter SWCNTs (2.1 nm) at high number densities (2.26 × 10 12 cm -2 ) on wafers up to 6 in. Although removing Mo resulted in larger SWCNT diameters and lower densities (<0.7 × 10 12 cm -2 ), mass conversion rates from C 2 H 2 to SWCNT product were high and remarkably invariant for catalyst compositions and densities (i.e., 47.7% or 1.30 × 10 6 % g-catalyst -1 on 4-in. wafers). These carbon conversion efficiencies far exceed typical benchtop reactors and are on par with the best reported literature values. Our detailed elucidation of correlations among structural characteristics within this resource-efficient process is expected to guide future scale-up efforts of SWCNT forest growth beyond wafer scale.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computationally Predicted High-Throughput Free-Energy Phase Diagrams for the Discovery of Solid-State Hydrogen Storage Reactions

The design of multinary solid-state material systems that undergo reversible phase changes via changes in temperature and pressure provides a potential means of safely storing hydrogen. However, fully mapping the stabilities of known or newly targeted compounds relative to competing phases at reaction conditions has previously required many stringent experiments or computationally demanding calculations of each compound’s change in Gibbs energy with respect to temperature, G(T). Here, we have extended the approach of constructing chemical potential phase diagrams based on ΔG f (T) to enable the analysis of phase stability at non-zero temperatures. We first performed density functional theory calculations to compute the formation enthalpies of binary, ternary, and quaternary compounds within several compositional spaces of current interest for solid-state hydrogen storage. Temperature effects on solid compound stability were then accounted for using our recently introduced machine learned descriptor for the temperature-dependent contribution G δ (T) to the Gibbs energy G(T). From these Gibbs energies, we evaluated each compound’s stability relative to competing compounds over a wide range of conditions and show using chemical potential and composition phase diagrams that the predicted stable phases and H2 release reactions are consistent with experimental observations. This demonstrates that our approach rapidly computes the thermochemistry of hydrogen release reactions for compounds at sufficiently high accuracy relative to experiment to provide a powerful framework for analyzing hydrogen storage materials. This framework based on G(T) enables the accelerated discovery of active materials for a variety of technologies that rely on solid-state reactions involving these materials.

08 HYDROGEN↗
DOE OSTI2025

Rapid Oxidation of Uranium Steel Alloys: Combustion Synthesis

This project explored the use of combustion synthesis as a rapid, high-temperature method for oxidizing uranium-bearing steel alloys. Traditional laboratory-scale synthesis methods often fail to replicate the thermal and kinetic conditions experienced by real-world particulates, particularly those formed under rapid quenching or high-temperature scenarios. Combustion synthesis offers a promising alternative by enabling fast, localized heating and flexible precursor selection. A series of targeted experiments were conducted using a U 2 NiCrFe 4 alloy as the precursor. The alloy was oxidized using combustion synthesis reactions fueled by uranyl nitrate and glycine, achieving peak temperatures exceeding 1,200 °C. Postreaction analysis using scanning electron microscopy (SEM), elemental mapping, and Raman spectroscopy revealed the formation of iron-based oxides, with limited but detectable evidence of uranium oxide phases such as UO 2 . The results indicate that under the rapid reaction and cooling conditions of combustion synthesis, iron oxides form preferentially, but uranium oxide formation is kinetically limited. These findings validate combustion synthesis as a viable method for simulating the oxidation behavior of uranium steels in extreme environments and lay the groundwork for future studies aimed at enhancing uranium oxide formation through higher temperatures or modified precursor compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Protein coating composition targets nanoparticles to leaf stomata and trichomes

Plant nanobiotechnology has the potential to revolutionize agriculture. However, the lack of effective methods to deliver nanoparticles (NPs) to the precise locations in plants where they are needed impedes these technological innovations. Here, model gold nanoparticles (AuNP) were coated with citrate, bovine serum albumin (BSA) as a protein control, or LM6-M, an antibody with an affinity for functional groups unique to stomata on leaf surfaces to deliver the AuNPs to stomata. One-month-old Vicia faba leaves were exposed via drop deposition to aqueous suspensions of LM6-M-coated AuNPs and allowed to air dry. After rinsing, Au distribution on the leaf surface was investigated by enhanced dark-field microscopy and X-ray fluorescence mapping. While citrate-coated AuNPs randomly covered the plant leaves, LM6M-AuNPs strongly adhered to the stomata and remained on the leaf surface after rinsing, and BSA-AuNPs specifically targeted trichome hairs. To the authors’ knowledge, this is the first report of active targeting of live leaf structures using NPs coated with molecular recognition molecules. Finally, this proof-of-concept study provides a strategy for future targeted nanopesticide delivery research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Solidification Effects in Additively Manufactured Si and SiGe Compositions

SiGe alloys have a proven track record as robust high-temperature thermoelectric materials, powering NASA missions like SNAP-10A, LES-9, and Voyager 1 and 2. Enhancing thermoelectric efficiency hinges on minimizing thermal conductivity while preserving electrical conductivity. Rapid solidification via LPBF can generate microstructural features such as subgrain cellular boundaries and twinning, which may help reduce thermal conductivity while preserving semiconducting behavior. Here, this study investigates the potential of laser powder bed fusion (LPBF) additive manufacturing to fabricate nanostructured Si and SiGe thermoelectric materials. High cooling rates (10 5 to 10 7 K/s) rates inherent to the LPBF process are conducive to forming such nanostructures. Moreover, this fabrication technique could also be suitable for fabricating complex geometries needed to achieve improved device level performance. Process mapping of commercial Si powder with irregular morphology was first performed to understand the LPBF processing behavior of this semiconductor material. Subsequent studies included in-house synthesized B-doped (p-type) Si7 8 Ge 22 spherical powder that was produced via ultrasonic atomization. Scan strategies involved multiple laser exposures to mitigate solidification cracking: a high density of >98% was achieved, but solidification cracking could not be fully eliminated. Subsequently, a high electrical resistivity (i.e., low conductivity) was observed, but the measured Seebeck coefficient, ∼230 μV/K @ 500 °C, proved that good semiconductor material was being fabricated. A subgrain cellular structure (5–10 μm) was observed as defined by Ge segregation to the intercellular boundaries. The remelting strategies helped lower the cooling rates in processing SiGe, but this still resulted in high residual stresses, which induced a remarkably high density of twins (78–95%) to accommodate the deformation. This unique grain structure offers an avenue for phonon scattering and potential improvements in thermoelectric performance.

figure of merit↗
DOE OSTI2026

Passivation‐Induced Species Dynamics and Microstructural Evolution in Solid‐State Lithium–Sulfur Cathodes

Solid-state lithium–sulfur (SSLS) batteries offer high theoretical energy density, yet their practical viability is hindered by poor sulfur utilization and limited rechargeability. At the core of this challenge lies the passivating nature of Li 2 S, which restricts ionic and electronic transport, suppresses interfacial activity, and severely impedes the reversibility of electrochemical reactions. In this study, we elucidate the mechanistic origins of these limitations by resolving how charge and discharge species form, grow, and spatially evolve within the cathode microstructure under varied current densities and electrode compositions. By resolving the species distribution at the particle scale and coupling it with Raman spectroscopy and X-ray diffraction, we demonstrate how Li 2 S formation induces localized surface passivation that progressively limits electrochemical accessibility within the cathode microstructure. Sulfur utilization is found to be strongly governed by the interplay between sulfur loading, residual porosity, and interfacial architecture. High sulfur contents result in buried, electrochemically isolated domains due to poor solid electrolyte (SE) percolation, while low sulfur contents trigger SE degradation via parasitic reactions. The resulting sulfur-porosity maps delineate the mechanistic boundaries between reversible and transport-limited regimes, offering actionable design guidance for SSLS cathodes with enhanced sulfur utilization.

electrode microstructure↗
DOE OSTI2021

Core–Shell Gold Nanoparticle-Star Copolymer Composites with Gradient Transfer and Transport Properties: Toward Electro-Optical Sensors and Catalysis

A series of hybrid core–shell nanomaterials was prepared by solvent phase transfer methods with gold (Au) nanoparticles (NPs) as a core and star copolymers (h-PEI-b-PCL-Cbz) as a shell—consisting of hyperbranched polyethyleneimine (h-PEI) with different poly(ε-caprolactone) (PCL) chain lengths and a carbazole-contained terminating agent (Cbz). By varying the PCL chain length, these core–shell nanomaterials exhibited gradient energy transfer properties, surface hydrophobicity, electropolymerizability, and ionic probe transport and diffusion properties. The systematic copolymer formation was verified with quadruple-detector size exclusion chromatography (SEC) and 1H nuclear magnetic resonance (NMR). High-resolution atomic force microscopy-infrared spectroscopy (AFM-IR) chemical mapping verified nanoparticle-substrate adhesion and film formation. The design of these hybrid NPs and elucidation of gradient properties will be useful for future applications of the core–shell systems in electro-optical sensing and catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Floating zone crystal growth, structure, and properties of a cubic Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 garnet-type lithium-ion conductor

As a promising candidate for solid-state electrolytes in Li-ion batteries, the garnet-type Li-ion conductor series Li 5+x La 3 Nb 2-x Zr x O 12 (LLNZO) (0 ≤ x ≤ 2) exhibits high ionic conductivity at room temperature. However, no previous single-crystal growth or characterization has been reported for LLNZO compositions 0 ≤ x ≤ 1. To obtain a complete understanding of the trend in the structure–property relationship in this class of materials, we used the floating zone (FZ) method to grow a single crystal of Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 that was 4 mm in diameter and 10 mm in length. Using Laue neutron single-crystal diffraction, two distinct Li sites were observed: tetrahedral 24d and octahedral 96h sites. The maximum entropy method (MEM) based on neutron single-crystal diffraction data was used to map Li nuclear density and estimate that the bottleneck of Li transport exists between neighboring tetrahedral and octahedral sites, and that Li is delocalized between split octahedral sites. Room-temperature Li-ion conductivity in Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 measured with electrochemical impedance spectroscopy (EIS) was 1.37 × 10 -4 S cm -1 . The Li migration activation energy was estimated to be 0.50 eV from EIS and 0.47 eV from dielectric relaxation measurements. The Li-ion jump attempt rate was estimated to be 1.47 × 10 12 Hz while the time scale of successful migration is 10 -7 to 10 -6 s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multimodal Mass Spectrometry Imaging (MSI) of Archean and Jurassic Geologic Samples

Current geochemical analytical techniques such as gas chromatography-mass spectrometry (GC-MS and $G\acute{C}GC-MS$) can effectively determine the composition and structure of the organic biosignatures within a sample but cannot resolve the spatial distribution of organic biosignatures within rocks or sediments. The spatial distribution can be used to determine the character of the organic biosignatures [1], which can be indigenous (deposited with host rocks), non-indigenous (incorporated after deposition via fluid migration), or contaminant. Determining the character of organic biosignatures is critical for ancient samples [2] and will be critical if organics are observed in samples returned from Mars [3].Fs-LDPI-MS has the ability to map organic compounds across the surface of samples at 2 - 10 μm lateral resolution. Furthermore, fs-LDPI-MS can be used to carry out multiple analyses in the same location for micron-scale analysis of previously buried material [4]. We used fs-LDPI-MS to examine a ~164 million year old organic-rich mudstone from SW England (14.2 wt. % total organic carbon) [5] and determined the spatial distribution of likely indigenous components buried below potentially contaminated surface layers.We then used ToF-SIMS to re-analyze the mudstone to directly compare ToF-SIMS to fs-LDPI-MS datasets, and to analyze a series of ~2.7 billion year old geologic samples from Timmins, ON, CA [6]. Ref. [6] previously analyzed the Archean samples and observed a series of archaeal biomarkers, as well as hopanes and steranes. Using ToF-SIMS analysis, we were able to detect hopanes and steranes in the mudstone samples, but not in the Archean samples indicating that the hopanes and steranes are most likely contaminants in the Archean samples. We also did not observe the archaeal biomarkers; however, this may be from the lack of molecular ion preservation during ToF-SIMS.

Pasterski, Michael↗
DOE OSTI2024

Idaho National Laboratory Integrated Multisite SSHAC Level 3: Probabilistic Volcanic Hazards Assessment

The Idaho National Laboratory (INL) resides on the eastern Snake River Plain (ESRP), part of the Snake River Plain (SRP) with a complex origin and geologic history of volcanism. Much of the Quaternary (last 2.58 million years) volcanism within 400 km of INL is genetically associated with a major thermal anomaly referred to as the Yellowstone hotspot, which is currently located more than 180 km northeast of INL. Near INL, local volcanic sources include silicic domes near its southern border, and numerous dike-fed basaltic vents of the ESRP, some of which are near or within the INL boundaries. Quantitative probabilistic assessments of screened-in volcanic hazardous phenomena for nine different facility complexes at the INL are presented for a Senior Seismic Hazard Analysis Committee (SSHAC) Level 3 (SL3) study. The comprehensive, integrated multisite SSHAC study consists of a single regional Probabilistic Volcanic Hazards Assessment (PVHA) that pertains to all nine INL facility complexes, with site-specific information developed at each respective area of interest (AOI), referred to as the "INL facility AOI" (Figure ES-1). Hazard products are generated for specified INL facility AOIs for use by multiple stakeholders from different agencies in risk-informed decision-making regarding site selection, operations, and design of nuclear facilities at INL, consistent with U.S. Department of Energy (DOE) and U.S. Nuclear Regulatory Commission (NRC) regulatory guidance. The study also serves as the basis for future periodic safety assessments required for existing DOE facilities, such as 10-year evaluations of natural-phenomena hazards. Elements of the INL PVHA including initial characterization, screening, quantitative assessments of eruption and hazard potential, and consideration of facility needs are conducted using the three phases of the SSHAC process: evaluation, integration, and documentation. As per regulatory guidance, the SSHAC framework provided the necessary processes and procedures for the PVHA Technical Integration (TI) team, at three workshops, five formal working meetings and many TI team remote meetings, to conduct initial characterization, screen the volcanic hazards, create PVHA model inputs, exercise those models in the PVHA, consider facility-specific volcanic hazard needs, and perform final hazard calculations. The Participatory Peer Review Panel (PPRP) provided independent oversight and performed process and technical reviews of the PVHA throughout its duration. The study included an extensive New Data Collection and Analyses (NDCA) program developed by the PVHA TI team to reduce uncertainties in hazard-significant elements in the PVHA model. NDCA activities generated 20 reports providing important contributory datasets and results to the project database for characterizing the ESRP. For example, a report compiling the dimensions of ESRP shield volcanoes and lava fields was used to construct volcanic footprints (areas of impact), was compared with data from INL subsurface cores, and was used to validate the results of lava-flow inundation modeling on the contemporary terrain. Another example is the acquisition of aeromagnetic data over INL and its surrounding area, with maps of buried magmatic features (e.g., subsurface volcanoes and swarms of feeder dikes) that informed the PVHA conceptual model of volcanism. The SSHAC evaluation process was used to conduct all elements of the PVHA including initial characterization and screening. Existing data and NDCA activities provided the foundation to develop the tectonomagmatic conceptual model of volcanism for the region of geographical interest in the SRP and Yellowstone hotspot volcanic system, and for considering volcanoes in the western US. Considering Quaternary volcanic sources active during this period, the screening approach identified and evaluated magma compositions, types of eruptive and intrusive phenomena, types of hazardous phenomena, and proximity of sources to INL. The PVHA TI team evaluated 18 types of magmatic sources in terms of 20 potentially hazardous phenomena, resulting in 360 screening decisions. The screening process resulted in 140 screened-in hazardous volcanic phenomena for Quaternary volcanic sources 1) proximal to INL facility complexes in the ESRP (64 basaltic and 54 silicic), 2) regional sources associated with the Yellowstone caldera system and Blackfoot Reservoir volcanic field (7), and 3) more distal sources from thirteen Cascade volcanoes and two volcanoes at Long Valley caldera (CA).

58 GEOSCIENCES↗
DOE OSTI2022

Photometric variability in star-forming galaxies as evidence for low-mass AGN and a precursor to quenching

We measure the optical variability in ~16 500 low-redshift (z ~ 0.1) galaxies to map the relations between active galactic nucleus (AGN) activity and galaxy stellar mass, specific star formation rate, half-light radius, and bulge-to-total ratio. To do this, we use a reduced χ 2 variability measure on >10 epoch light curves from the Zwicky Transient Facility and combine with spectroscopic data and derive galaxy parameters from the Sloan Digital Sky Survey. We find that below the stellar mass of 10 11 M ⊙ , galaxies classed as star-forming via the Baldwin–Phillips–Terlevich diagram have higher mean variabilities than AGN or composite galaxies. Revealingly, the highest mean variabilities occur in star-forming galaxies in a narrow range of specific star formation rate: -11 < log(sSFR/yr -1 ) < -10. In very actively star-forming galaxies [log(sSFR/yr -1 ) > -10], the reduced variability implies a lack of instantaneous correlation with star formation rate. Our results may indicate that a high level of variability, and thus black hole growth, acts as a precursor for reduced star formation, bulge growth, and revealed AGN-like emission lines. These results add to the mounting evidence that optical variability can act as a viable tracer for low-mass AGNs and that such AGNs can strongly affect their host galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Controlled catalyst-transfer polymerization in graphene nanoribbon synthesis

Exercising direct control over the unusual electronic structures arising from quantum confinement effects in graphene nanoribbons (GNRs) is intimately linked to geometric boundary conditions imposed by the structure of the ribbon. Besides composition and position of substitutional dopant atoms, the symmetry of the unit cell, width, length, and termination of a GNR govern its electronic structure. Here, we present a rational design that integrates each of these interdependent variables within a modular bottom-up synthesis. Our hybrid chemical approach relies on a catalyst-transfer polymerization that establishes excellent control over length, width, and end groups. Complemented by a surface-assisted cyclodehydrogenation step, uniquely enabled by matrix-assisted direct (MAD) transfer protocols, geometry and functional handles encoded in a polymer template are faithfully mapped onto the structure of the corresponding GNR. Bond-resolved scanning tunneling microscopy (BRSTM) and spectroscopy (STS) validate the robust correlation between polymer template design and GNR electronic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗