Search NASA⌕ Search

SEARCH · Search NASA

Results for “green shift”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Investigating Cu-Site Doped Cu–Sb–S Nanoparticles Using Photoelectron and Electron Paramagnetic Resonance Spectroscopy

Tetrahedrite (Cu 12 Sb 4 S 13 ) and famatinite (Cu 3 SbS 4 ) are good candidates for green energy applications because they possess promising thermoelectric and photovoltaic properties as well as contain earth-abundant and nontoxic constituents. Herein, X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), and electron paramagnetic resonance spectroscopy (EPR) methods examined inherent electronic properties and interatomic magnetic interactions of Cu-site doped tetrahedrite and famatinite nanomaterials. An energy-efficient modified polyol method was utilized for the synthesis of tetrahedrite and famatinite nanoparticles doped on the Cu-site with Zn, Fe, Ni, Mn, and Co. This is the first parallel study of tetrahedrite and famatinite nanomaterials with XPS, UPS, and EPR methods alongside a systematic analysis of dopant-dependent effects on the electronic structure and magnetic interactions for each material. XPS showed that the Cu and Sb species in tetrahedrite and famatinite possess different oxidation states, while UPS characterization reveals larger dopant-dependent shifts in the work function for tetrahedrite nanoparticles (4.21 to 4.79 eV) than for famatinite nanoparticles (4.57 to 4.77 eV). Finally, all famatinite nanoparticles display an EPR signal, indicating trace amounts of paramagnetic Cu(II) present below the detection limit of XPS. For tetrahedrite, EPR signatures were observed only for the Zn-doped and Mn-doped nanoparticles, suggesting signal broadening from Cu–Cu spin exchange or spin–lattice relaxation. This study demonstrates the complementary nature of XPS and EPR techniques for studying the oxidation states of metals in solid-state nanomaterials. Comparing the electronic and magnetic properties of tetrahedrite and famatinite while studying the impact of dopant incorporation will guide future endeavors in designing sustainable, high-performance materials for renewable energy applications.

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

A Search for L4 Earth Trojan Asteroids Using a Novel Track-before-detect Multiepoch Pipeline

We report Earth Trojan asteroids are an important but elusive population that co-orbit with Earth at the L4 and L5 Lagrange points. There is only one known, but a large population is theoretically stable and could provide insight into our solar system’s past and present, as well as planetary defense. In this paper, we present the results of an Earth Trojan survey that uses a novel shift-and-stack detection method on 2 nights of data from the Dark Energy Camera. We find no new Earth Trojan asteroids. We calculate an upper limit on the population that is consistent with previous searches despite much less sky coverage. Additionally, we elaborate on previous upper-limit calculations using current asteroid population statistics and an extensive asteroid simulation to provide the most up-to-date population constraints. We find an L4 Earth Trojan population of N ET < 1 for H = 13.93, N ET < 10 for H = 16, and N ET < 938 for H = 22.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Californium-252 production at the High Flux Isotope Reactor - I: Validation study using campaign data

This paper presents a series of 252 Cf production validation and code-to-code comparison studies performed based on data from the production campaigns at the High Flux Isotope Reactor (HFIR). These studies support efforts to convert HFIR from using highly enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. HFIR must maintain its world-class performance and missions following this conversion, and because 252 Cf is a vital neutron-emitting radioisotope used for a variety of high-impact applications (e.g., reactor startup, cancer treatment), the ability to efficiently produce 252 Cf must be preserved. In this work, the HFIRCON, Shift, ORIGEN, and TCOMP codes were deployed, and several sets of data libraries were investigated to better understand the calculation codes and the data biases. As-loaded target composition data, as-run irradiation history data, and post-irradiation measurements from recent multi-cycle irradiation campaigns of the HEU core were used to validate and determine methodology biases. Further, the findings demonstrated a good agreement, with results falling within 3 standard deviations of measurements. This paper lays the ground work for the second paper, which evaluates and compares 252 Cf production and safety metrics with the HEU core and a proposed LEU core.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Suppressing CO formation in low-temperature methanol steam reforming via Ce-modified CuZnGa layered oxide catalysts

Cu-based layered double hydroxides (LDHs) are widely recognized as effective catalysts for low-temperature methanol steam reforming, yet achieving high hydrogen productivity together with near-complete suppression of CO formation remains challenging. Here, we report the synthesis and evaluation of a series of CuZnGa LDH-derived catalysts and Ce-modified analogues prepared via an aqueous miscible organic method, which enables high metal dispersion and precise structural control. The optimized CuZnGa catalyst exhibits a hydrogen production rate of 16.9 µmol H 2 ·g cat −1 ·s −1 at 180 °C with an H 2 /CO ratio exceeding 3500, outperforming many state-of-the-art low-temperature systems. Importantly, the incorporation of small amounts of Ce further suppresses CO formation while maintaining high hydrogen productivity. Combined spectroscopic characterization and density functional theory calculations reveal that Ce is incorporated into the LDH lattice by substituting Ga 3+ sites up to a critical threshold, beyond which highly dispersed CeO x species are formed. These species provide mobile lattice oxygen that participates in a Mars-van Krevelen-type pathway, selectively oxidizing CO and suppressing the reverse water-gas shift reaction. This study establishes a clear relationship between Ce speciation, oxygen mobility, and catalytic selectivity in LDH-derived systems. The resulting catalysts demonstrate the potential of interface-engineered Cu-based materials for efficient low-temperature hydrogen production with minimal CO contamination.

09 BIOMASS FUELS↗
DOE OSTI2021

Kinetics of furfural electrochemical hydrogenation and hydrogenolysis in acidic media on copper

Electrochemical processes can be implemented for the valorization of biomass-derived species such as furfural to generate fine chemicals and fuels. The electrochemical hydrogenation and hydrogenolysis (ECH) of furfural (FF) can produce furfuryl alcohol (FA) and 2-methylfuran (MF) as the major products over Cu catalysts in acidic conditions. The production of these species are in competition and the kinetics of these reactions should be studied so that the product distribution can be better controlled. In this work, the competing kinetics of furfural ECH to furfuryl alcohol and 2-methylfuran were studied on Cu in acidic media by using the applied cathodic potential, temperature, and initial concentration of furfural as probes. Furthermore, an increased temperature of the system was shown to promote the MF production in the range tested (15 °C and 45 °C), however the production of FA was decreased when the temperature was increased from 35 °C to 45 °C, due to significant promotion of side reactions. By varying the concentration of FF used in bulk electrolysis, we saw that the rates of reaction to FA and MF shift from positive order to zero order, suggesting a Langmuir–Hinshelwood or Eley–Rideal mechanism at –0.56 V vs. RHE and 25 °C. An analysis of the reaction mechanisms showed that a non-competitive Langmuir–Hinshelwood mechanism is likely occurring. In addition, we suggest the likely rate limiting steps based on the mechanisms are the first hydrogenation step of FF to C 4 H 3 O–CH 2 O to form FA, and the C–O cleavage of the C 4 H 3 O–CHOH intermediate to form MF.

09 BIOMASS FUELS↗
DOE OSTI2021

Photostability of Ambient-Processed, Conjugated Polymer Electrochromic Devices Encapsulated by Bioderived Barrier Films

Polymer-based electrochromic devices (ECDs) are a promising technology for enabling low-voltage, disposable displays, yet are currently limited by photo-oxidative bleaching of the active materials. Here, renewable barrier films composed of cellulose and chitin are presented as an alternative to poly(ethylene terephthalate) (PET) for encapsulating ECDs. To assess barrier film effectiveness, lateral ECDs composed of poly(3,4-propylenedioxythiophene-(CH 2 OEtHx) 2 ) (P(ProDOT)) active layers were constructed and encapsulated with a multilayer barrier consisting of chitin nanofibers and cellulose nanocrystals spray cast onto a cellulose acetate substrate (oxygen transmission rate (OTR) = 29 cm 3 m –2 day –1 ), a commercially available PET film (OTR = 8.5 cm 3 m –2 day –1 ), and a high-performance PET-Al 2 O 3 multilayer barrier film (OTR < 1 cm 3 m –2 day –1 ). The photodegradation of the P(ProDOT) active layer was determined by measuring the evolution of the colorimetric contrast (ΔE*) and switching speeds as a function of light exposure (100 mW cm –2 , AM 1.5 G light). Photodegradation was found to proceed at a similar rate for all encapsulated devices (roughly 10 times more slowly than unencapsulated devices), highlighting the opportunity for replacing petroleum packaging with bioderived barrier films. Analysis of the switching kinetics, the shifts in optical absorbance, and evidence of chemical degradation indicate that both photochemical breakdown of the electrolyte and cross-linking of the P(ProDOT) active material are key drivers for loss of device performance when oxygen flux to the active material is limited. Furthermore, pathways toward better understanding photodegradation are then proposed with sustainability in mind for future ECD design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Climate, food and humans predict communities of mammals in the United States

Abstract Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty‐five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard‐mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine‐scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Kays, Roland↗
DOE OSTI2020

Distributed Photovoltaic Economic Impact Analysis in Indonesia

Like other countries in the region, the Government of Indonesia aims to increase its use renewable energy in the near term from various technologies, including grid-connected distributed photovoltaics (DPV). While little DPV has been installed to date, the policy landscape has been shifting over the past few years with recent pronouncements from the state-run utility Perusahaan Listrik Negara (PLN) and the Ministry of Energy and Mines (MEMR) that have begun to provide a more supportive policy framework for the deployment of DPV. Nonetheless, many questions remain as to how DPV impacts customers, the utility, and the economy as a whole. This report presents a holistic view of DPV economic impacts in the Java-Bali region of Indonesia by assessing customer economic impacts, utility revenue impacts, and jobs and economic development impacts.

14 SOLAR ENERGY↗
DOE OSTI2021

Mechanism and dynamics of fatty acid photodecarboxylase

Photoenzymes are rare biocatalysts driven by absorption of a photon at each catalytic cycle; they inspire development of artificial photoenzymes with valuable activities. Fatty acid photodecarboxylase (FAP) is a natural photoenzyme that has potential applications in the bio-based production of hydrocarbons, yet its mechanism is far from fully understood. RATIONALE To elucidate the mechanism of FAP, we studied the wild-type (WT) enzyme from Chlorella variabilis (CvFAP) and variants with altered active-site residues using a wealth of techniques, including static and time-resolved crystallography and spectroscopy, as well as biochemical and computational approaches. RESULTS A 1.8-Å-resolution CvFAP x-ray crystal structure revealed a dense hydrogen-bonding network positioning the fatty acid carboxyl group in the vicinity of the flavin adenine dinucleotide (FAD) cofactor. Structures solved from free electron laser and low-dose synchrotron x-ray crystal data further highlighted an unusual bent shape of the oxidized flavin chromophore, and showed that the bending angle (14°) did not change upon photon absorption (step 1) or throughout the photocycle. Calculations showed that bending substantially affected the energy levels of the flavin. Structural and spectroscopic analysis of WT and mutant proteins targeting two conserved active-site residues, R451 and C432, demonstrated that both residues were crucial for proper positioning of the substrate and water molecules and for oxidation of the fatty acid carboxylate by 1 FAD* (~300 ps in WT FAP) to form FAD ∙– (step 2). Time-resolved infrared spectroscopy demonstrated that decarboxylation occured quasi-instantaneously upon this forward electron transfer, consistent with barrierless bond cleavage predicted by quantum chemistry calculations and with snapshots obtained by time-resolved crystallography. Transient absorption spectroscopy in H 2 O and D 2 O buffers indicated that back electron transfer from FAD ∙– was coupled to and limited by transfer of an exchangeable proton or hydrogen atom (step 3). Unexpectedly, concomitant with FAD ∙– reoxidation (to a red-shifted form FAD RS ) in 100 ns, most of the CO 2 product was converted, most likely into bicarbonate (as inferred from FTIR spectra of the cryotrapped FAD RS intermediate). Calculations indicated that this catalytic transformation involved an active-site water molecule. Cryo-Fourier transform infrared spectroscopy studies suggested that bicarbonate formation (step 4) was preceded by deprotonation of an arginine residue (step 3). At room temperature, the remaining CO 2 left the protein in 1.5 μs (step 4'). The observation of residual electron density close to C432 in electron density maps derived from time-resolved and cryocrystallography data suggests that this residue may play a role in stabilizing CO 2 and/or bicarbonate. Three routes for alkane formation were identified by quantum chemistry calculations; the one shown in the figure is favored by the ensemble of experimental data. CONCLUSION Finally, we provide a detailed and comprehensive characterization of light-driven hydrocarbon formation by FAP, which uses a remarkably complex mechanism including unique catalytic steps. We anticipate that our results will help to expand the green chemistry toolkit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5

Abstract. Isolated deep convective cloud life cycle and seasonal changes in storm properties are observed for daytime events during the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Green Ocean Amazon Experiment (GoAmazon2014/5) campaign to understand controls on storm behavior. Storm life cycles are documented using surveillance radar from initiation through maturity and dissipation. Vertical air velocity estimates are obtained from radar wind profiler overpasses, with the storm environment informed by radiosondes. Dry-season storm conditions favored reduced morning shallow cloud coverage and larger low-level convective available potential energy (CAPE) than wet-season counterparts. The typical dry-season storm reached its peak intensity and size earlier in its life cycle compared with wet-season cells. These cells exhibited updrafts in core precipitation regions (Z>35 dBZ) to above the melting level as well as persistent downdrafts aloft within precipitation adjacent to their cores. Moreover, dry-season cells recorded more intense updrafts to earlier life cycle stages as well as a higher incidence of strong updrafts (i.e., >5 m s−1) at low levels. In contrast, wet-season storms were longer-lived and featured a higher incidence of moderate (i.e., 2–5 m s−1) updrafts aloft. These storms also favored a shift in their most intense properties to later life cycle stages. Strong downdrafts were less frequent within wet-season cells aloft, indicating a potential systematic difference in draft behaviors, as linked to graupel loading and other factors between the seasons. Results from a stochastic parcel model suggest that dry-season cells may expect stronger updrafts at low levels because of larger low-level CAPE in the dry season. Wet-season cells anticipate strong updrafts aloft because of larger free-tropospheric relative humidity and reduced entrainment-driven dilution. Enhanced dry-season downdrafts are partially attributed to increased evaporation, dry-air entrainment mixing, and negative buoyancy in regions adjacent to sampled dry-season cores.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Enamel nanocrystal misorientation increased with meat-eating and agriculture

Enamel covers teeth, is the hardest tissue in the vertebrate body and has a complex multiscale structure from nanometres to millimetres. The structure comprises thin, long hydroxyapatite (Ca 5 (PO 4 ) 3 OH) nanocrystals, 50–70 nm wide, many micrometres long, parallel and bundled into approximately 5-µm-wide rods. The rods undulate and cross into a microscale ‘decussation pattern’ that toughens enamel by deflecting cracks. However, the crystallographic orientation of enamel nanocrystals is poorly understood. Here we show that the misorientation angle of adjacent nanocrystals varies markedly across 12 primate teeth spanning 9 species, 17.8 million years of evolution and diverse diets. Using a method called Polarization Enabled Large Input of Crystal Angles at the Nanoscale (PELICAN), we compare nanocrystals in the same (pre)molar locations and show that misorientation increases with food hardness in extant and fossil non-human apes and monkeys. We compare misorientation across three major dietary shifts in human evolution: the transition to meat-eating about 2.0–1.5 million years before present, to agriculture (about 12,000 years before present), and the Industrial Revolution (about 250 years before present). We show that over the past 1.6 million years, in the human lineage misorientation increased with time, especially when meat and stone-ground grains were introduced into human diets, but not with the Industrial Revolution. Thus, besides macro-changes, teeth adapted to dietary change at the nanoscale and crystallographically. This observation suggests that misorientation may contribute to enamel’s resilience; thus, bioinspired materials may consider small misorientation angles for added resilience.

biomaterials↗
DOE OSTI2024

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Chemistry↗
DOE OSTI2025

Radiation Response of Ga 2 O 3 MOSFETs Probed via Focused Particle Beams

Gallium Oxide (Ga 2 O 3 ), particularly in its β-phase, is attracting lots of interest for high-power and high-voltage electronics due to its wide bandgap, high breakdown field, and thermal stability. This study investigates the radiation response of Ga 2 O 3 Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) under Total Ionizing Dose (TID) and Displacement Damage (DD) conditions, which are critical for applications in radiation environments. Utilizing a dual-beam Focused Ion Beam and Scanning Electron Microscope setup, microscale analysis of radiation effects on individual devices is performed. The findings reveal distinct behaviors under TID and DD + TID conditions, with TID leading to threshold voltage shifts due to trapped charges, while DD results in decreased drive current attributed to increased carrier scattering from lattice defects. Notably, it is demonstrated that the TID effect can be mitigated through dynamic threshold voltage adjustments and that the predicted TID from ions calculated by Monte Carlo simulations overestimates actual TID due to unaccounted charge yield effects. In conclusion, this research enhances the understanding of Ga2O3 MOSFETs' performance in harsh radiation environments, providing insights for the design of robust electronic devices for space and nuclear applications.

MOSFET↗
DOE OSTI2021

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗
DOE OSTI2023

Deterministic-Monte Carlo Hybrid Methods for Eigenvalue Sensitivity Coefficient Calculations

The TSUNAMI suite within the SCALE code package includes several methods for generating sensitivity data, including multigroup (MG) and continuous-energy (CE) capabilities. For generating sensitivities with CE data, three methods are available in SCALE 6.3.0: (1) the iterated fission probability (IFP) method with the KENO Monte Carlo transport solver, (2) IFP with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance Characterization (CLUTCH) with the KENO Monte Carlo transport solver. Currently, it is difficult to generate accurate sensitivities with large reflectors when using the CLUTCH method, specifically with fissionable and hydrogenous materials. To address this issue, the work presented herein examines a methodology to calculate the adjoint flux externally with the 3D deterministic SN transport code DENOVO in SCALE; the result is then read directly into the CLUTCH-TSUNAMI sequence. This hybridization method replaces the Monte Carlo F*(r) calculation in CLUTCH while still utilizing the forward calculation. The critical benchmark HEU-MET-FAST-028-001 is used to generate sensitivities based on the inability of CLUTCH to generate accurate sensitivities. Results from the hybrid method appear to generate sensitivity values that are in excellent agreement with direct perturbations. Although further testing is needed, the method provides promising results for the development and utility of a hybrid method for use in TSUNAMI.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Dynamic soil columns simulate Arctic redox biogeochemistry and carbon release during changes in water saturation

Thawing Arctic permafrost can induce hydrologic change and alter redox conditions, shifting the balance of soil organic matter (SOM) decomposition. There remains uncertainty about how soil saturation and redox transitions impact dissolved and gas phase carbon fluxes, and efforts to link hydrobiogeochemical processes to ecosystem-scale models are limited. This study evaluates SOM decomposition of Arctic tundra soils using column experiments, water chemistry measurements, microbial community analysis, and a PFLOTRAN reactive transport model. Soil columns from a thermokarst channel (TC) and an upland tundra (UC) were exposed to cycles of saturation and drainage, which controlled carbon emissions. During saturation, an outflow of dissolved organic carbon from the UC soil correlated with elevated reduced iron and decreased pH; during drainage, UC carbon dioxide fluxes were 70% higher than TC fluxes. Intermittent methane release was observed for TC, consistent with higher methanogen abundance. Slower drainage in the TC soil correlated with more subtle biogeochemical changes. PFLOTRAN simulations captured experimental trends in soil carbon fluxes, oxygen concentrations, and water contents. The model was then used to evaluate additional soil water drainage rates. This study emphasizes the importance of considering hydrologic change when evaluating and simulating SOM decomposition in dynamic Arctic tundra environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗