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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

FY23 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY23. As a continuation of the modeling effort from FY22, this year’s work focuses on improving the RELAP5-3D model developed previously for two-phase flow simulations. The RELAP5-3D model is updated to more accurately capture the heat loss experienced by the facility. The updated model is compared against experimental data for benchmarking purposes of the RELAP5-3D input model. By correctly accounting for heat loss, the updated RELAP5-3D model can now predict the two-phase baseline case more accurately. The onset and the duration of instability are captured well by the model. Furthermore, analyses are performed to better understand the instability mechanism experienced by the flow where the expansion of the boiling boundary in the chimney is studied in details and the fundamental frequencies of the oscillations are obtained. The updated RELAP5-3D model is further compared against four fault conditions, namely the reduction of riser header inlet flow area, depletion of system inventory, blocked riser channels, and static boiling scenario. For each fault condition, minor modifications and tuning are performed to improve the predictions of the model. The purpose of the analyses is to investigate the capability of RELAP5-3D in predicting complex two-phase flows in possible accident scenarios in actual Reactor Cavity Cooling System (RCCS). Overall, the model is able to capture the behaviors and trends of these fault conditions relatively well. Some discrepancies remain between the experimental data and the predictions, many of which are likely due to the differences in the predicted and experimental vapor generation rate. Future work will focus on the continued development of the current RELAP5-3D input model of the NSTF to both improve the accuracy of the model’s predictive capability and continue supporting the experimental program needs. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Why cutting respiratory CO 2 loss from crops is possible, practicable, and prudential

Abstract Plants release back to the atmosphere about half of the CO 2 they capture by photosynthesis. Decreasing the rate of crop respiration could therefore potentially increase yields, store more carbon in the soil and draw down atmospheric CO 2 . However, decreasing respiration rate has had very little research effort compared to increasing photosynthesis, the historically dominant metabolic paradigm for crop improvement. Conceptual and technical advances, particularly in protein turnover and directed enzyme evolution, have now opened ways to trim the large fraction of respiration that fuels proteome maintenance by lowering the breakdown and resynthesis rates of enzymes and other proteins. In addition to being theoretically possible and practicable, exploring the reduction of respiration is prudential, given that it (i) has barely yet been tried and (ii) could help meet the challenges of sustaining crop productivity and managing atmospheric carbon.

Joshi, Jaya↗
DOE OSTI2024

Performance and Durability of Heavy-Duty Fuel Cell Systems with an Advanced Ordered Intermetallic ORR Alloy Catalyst and Novel Support

Ordered PtCo intermetallic (OIM) catalyst (L1 0 -PtCo/C) is a promising candidate as the oxygen reduction reaction (ORR) catalyst in hybrid fuel cell systems (FCS) for class-8 heavy duty (HD) trucks. Compared to a baseline annealed Pt on high surface area carbon (a-Pt/HSC) catalyst, its mass activity (MA) is 71% higher initially and 144% higher after 90,000 potential cycles in an accelerated stress test (AST). Analysis of the AST data indicates that the ORR kinetic constants do not change with aging and the degradation in the OIM catalyst activity is linearly proportional to the loss in the electrochemically active surface area (ECSA). Several operational strategies are investigated to mitigate catalyst degradation and achieve 25,000-h electrode lifetime and 2.5 kW g −1 Pt utilization on a HD truck duty cycle including load sharing with the hybrid battery, regulating the radiator fan power to maintain the coolant temperature close to 60 °C, clipping the maximum cell voltage below 850 mV, limiting the ECSA loss to 55%, and oversizing the active area of the membrane electrode assemblies by 20%. Drive cycle simulations indicate that the lifetime average voltage degradation rate is about 1.8 μV h −1 and the integrated stack and FCS drive cycle efficiencies decrease by 3.5 to 3.9%.

25 ENERGY STORAGE↗
DOE OSTI2022

Decline in Seasonal Snow during a Projected 20-Year Dry Spell

Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence, and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections, we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a “stress test” for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find that 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in the area burned, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems, we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47–58% of historical values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Electrochemical Oxidation in Garnet-Type Solid Electrolyte by Formation of Point Defects

All-solid-state batteries hold greater promise for improving safety and energy density over conventional battery technology employing organic liquid electrolytes. One of the required features of a Li + conducting solid electrolyte is electrochemical stability, attained thermodynamically or kinetically, within the targeted operating voltage and temperature ranges. Therefore, understanding of the oxidative or reductive degradation mechanism is important to allow the design of stable solid electrolyte materials. This work contributes to building an understanding of the oxidative degradation mechanism in lithium solid electrolytes at cell operating conditions. Here, we have focused on resolving the oxidative decomposition mechanism of Al-doped lithium garnet Li 6.28 Al 0.24 La 3 Zr 2 O 12 (LLZO) as a state-of-the-art inorganic ceramic electrolyte. By combining experimental and computational analyses, we show that oxidation of LLZO occurs by simultaneous loss of oxygen and lithium from the structure, resulting in substoichiometric LLZO, at a moderate temperature (80 °C) and a high electrode potential (4.3 V vs Li/Li + ). Based on X-ray absorption and diffraction analyses, we find that the zirconium coordination shells in LLZO contract while the crystal structure experiences positive chemical strain upon electrochemical oxidation. The results from ex situ structural characterization of both the local structure and crystal symmetry are supported by a substoichiometric LLZO with lithium and oxygen vacancies, modeled by density functional theory (DFT) calculations. These chemical and structural changes in LLZO suppress effective lithium-ion conductivity by an order of magnitude. Formation of lithium and oxygen vacancies in LLZO upon electrochemical oxidation is different from prior thermodynamic predictions of phase decomposition of LLZO. The difference here is that the experiments were conducted at near-room temperature, which can hinder the kinetics of phase separation, and thus, the resultant LLZO solid electrolyte is still single-phase but substoichiometric in Li and O. In conclusion, these findings contribute an important degradation mechanism of the electrolyte, relevant for practical operational conditions of solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Facet-Dependent Ni Segregation in a Micron-Sized Single-Crystal Li 1.2 Ni 0.2 Mn 0.6 O 2 Cathode

Elemental surface segregation in cathode materials is critical for determining the phase and interfacial reaction between electrode and electrolyte, which consequently affects the electrochemical properties. Single-crystal cathode of Li 1.2 Ni 0.2 Mn 0.6 O 2 and Li 1.2 Ni 0.2 Mn 0.6 O 1.95 F 0.05 with an octahedral morphology of (102) and (003) dominated facets have been manifested to show enhanced electrochemical properties. However, the surface structural features of such single crystals have not been investigated. Herein, using scanning transmission electron microscopy, energy dispersive X-ray spectroscopy, and electron energy loss spectroscopy, we probe the elemental surface segregation characteristics in these single-crystal cathode. We reveal that Ni surface segregation shows dependence on the crystal facet such that it occurs on crystal facets with a mix of cations and anions, but not on the facets with only cations or anions. Furthermore, facet-dependent surface reconstructions are observed, featuring a spinel-like structure at the Ni-rich facet but rock-salt structure at the facet without Ni segregation. The commonly known Mn reduction appears at the single crystal surfaces, more pronounced at the facet without Ni segregation. We further reveal that fluorination leads to the stabilization of surface oxygens. In conclusion, this study provides detailed structural and chemical information about the facet-dependent Ni surface segregation and the resulted phase formation in the rather less explored micron-sized octahedral Li 1.2 Ni 0.2 Mn 0.6 O 2 and Li 1.2 Ni 0.2 Mn 0.6 O 1.95 F 0.05 single crystals, which is key to further exploration of electrochemical properties of cathode in the form of micro-sized single crystal.

25 ENERGY STORAGE↗
DOE OSTI2025

An end-to-end deep learning method for solving nonlocal Allen–Cahn and Cahn–Hilliard phase-field models

Here, we propose an efficient end-to-end deep learning method for solving nonlocal Allen–Cahn (AC) and Cahn–Hilliard (CH) phase-field models. One motivation for this effort emanates from the fact that discretized partial differential equation-based AC or CH phase-field models result in diffuse interfaces between phases, with the only recourse for remediation is to severely refine the spatial grids in the vicinity of the true moving sharp interface whose width is determined by a grid-independent parameter that is substantially larger than the local grid size. In this work, we introduce non-mass conserving nonlocal AC or CH phase-field models with regular, logarithmic, or obstacle double-well potentials. Because of non-locality, some of these models feature totally sharp interfaces separating phases. The discretization of such models can lead to a transition between phases whose width is only a single grid cell wide. Another motivation is to use deep learning approaches to ameliorate the otherwise high cost of solving discretized nonlocal phase-field models. To this end, loss functions of the customized neural networks are defined using the residual of the fully discrete approximations of the AC or CH models, which results from applying a Fourier collocation method and a temporal semi-implicit approximation. To address the long-range interactions in the models, we tailor the architecture of the neural network by incorporating a nonlocal kernel as an input channel to the neural network model. We then provide the results of extensive computational experiments to illustrate the accuracy, predictive capabilities, and cost reductions of the proposed method.

42 ENGINEERING↗
DOE OSTI2021

Self-Anchored Platinum-Decorated Antimony-Doped-Tin Oxide as a Durable Oxygen Reduction Electrocatalyst

The lifetime of commercial Proton Exchange Membrane Fuel Cells (PEMFCs) is circumscribed by the insufficient durability of commercial catalysts. The use of metal oxide supports in place of carbon significantly increases electrocatalyst durability. Herein, following density functional theory (DFT) predictions of improved Platinum (Pt) stability on antimony doped tin oxide (ATO) supports, we synthesized ATO whose morphology and crystal structure was engineered using a Pt anchoring technique. X-ray photoelectron spectroscopy (XPS) indicated that the Pt anchor sites aided in the reduction of Pt precursors to Pt on the ATO surface. X-ray absorption near-edge spectroscopy (XANES) revealed the existence of strong-metal-support interactions (SMSI) between Pt and ATO. The combination of SMSI and high control over Pt dispersion enabled the Pt/Pt-aerogel-ATO (Pt supported on aerogel ATO with Pt anchor sites) electrocatalyst to achieve 2x the area specific activity of Pt/C in ex-situ testing. In a H 2 /air PEMFC Pt/Pt-aerogel-ATO cathodes enabled 20% higher peak power density and <1/6 the loss of active surface area as compared to Pt/C. Notably, in a PEMFC under rigorous potential cycling, the Pt/Pt-aerogel-ATO retained its initial peak power density as opposed to a 58% loss for Pt/C. Further, cost models indicate that Pt/Pt-aerogel-ATO is 26% less expensive than Pt/C over its useful lifetime.

25 ENERGY STORAGE↗
DOE OSTI2025

Constructing Highly Durable Fuel Cell Catalysts Through Integrating Graphitic Shell‐Protected Composite Carbon Support with Gaseous Co Deposition‐Driven PtCo Intermetallics

Metal dissolution, nanoparticle agglomeration, and carbon support corrosion cause significant performance degradation of current PtCo catalysts under acidic and oxidative oxygen reduction reaction. Here, in this study, an integrated strategy is presented to design high-performance Pt 3 Co intermetallic catalysts by regulating gaseous Co deposition-driven diffusion into Pt nanoparticles supported on a composite carbon. The composite carbon is derived from ZIF-8/polyaniline, consisting of a high-surface-area (HSC) core and a protective graphitic shell (GS), which is employed to design 40 wt.% Pt/HSC@GS catalyst. The corresponding membrane electrode assemblies (MEAs) can maintain 1.09 A cm −2 at 0.7 V (20. 7% loss) after 10 000 cycles (1.0–1.5 V for carbon stability) and 1.15 A cm −2 (16.1% loss) after 150 000 cycles (0.60–0.95 V for catalyst stability). A ordered Pt 3 Co intermetallic is synthesized via a gaseous Co-deposition process, which yields a homogeneous Co-rich layer onto the Pt nanoparticles on the composite support, thereby facilitating Co diffusion into Pt crystal during subsequent ordering annealing to form the ordered intermetallic structure. This gaseous deposition leads to a thin carbon layer on PtCo nanoparticles, inhibiting particle growth during the annealing and mitigating Co dissolution under dynamic electrochemical conditions. The PtCo catalyst achieves impressive MEA performance and long-term durability (1.45 A cm −2 at 0.7 V after 120 000 cycles) under heavy-duty conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Engineering metal-oxide interface by depositing ZrO 2 overcoating on Ni/Al 2 O 3 for dry reforming of methane

Zirconium oxide (ZrO 2 ) was deposited onto Ni/Al 2 O 3 catalyst as overcoating by atomic layer deposition (ALD) for dry reforming of methane (DRM). High-temperature heating during H-2-reduction could transform the ALD-prepared ZrO 2 thin film to tetragonal phase and crack the encapsulating layer on Ni sites, which constructed a beneficial Ni-ZrO x interface. Here, interfacial surface oxygen vacancies on ZrO 2 overcoating were induced by the partial reduction of ZrO 2 surface during high-temperature H 2 reduction, with the assistance of Ni. During DRM, the interfacial oxygen vacancies enhanced CO 2 activation by dissociating CO 2 and releasing active O, thereby limiting carbon formation. For DRM at 700 °C and 800 °C, Ni/Al 2 O 3 with 5 cycles of ZrO 2 ALD overcoating enhanced both activity and stability significantly. For a 100-h DRM test at 600 °C, no deactivation was observed for the Ni/Al 2 O 3 catalyst with 10 cycles of ZrO 2 ALD overcoating, as compared to 59% relative activity loss of Ni/Al 2 O 3 .

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

sMicroRNA-28-5p acts as a metastasis suppressor in gastric cancer by targeting Nrf2

The transcription factor nuclear factor (erythroid-2)-related factor 2 (Nrf2) can principally serve a mode of protection for both the normal cells and cancer cells from cellular stress, and elevates cancer cell survival. microRNA-28 (miR-28) has been involved in the regulation of Nrf2 expression in breast epithelial cells. However, no comprehensive analysis has been conducted regarding the function of miR-28-5p regulating Nrf2 in gastric cancer (GC). In this study, we aimed to evaluate their interaction and biological roles in the migration and invasion of GC cells. The expression of Nrf2 in the cancer tissues harvested from 42 patients with GC was examined by an array of molecular techniques comprising of Immunohistochemical staining, RT-qPCR and Western blot analysis. Kaplan-Meier method was adopted for analysis of the correlation of Nrf2 with the prognosis of GC patients. Interaction between miR-28-5p and Nrf2 was determined using the bioinformatics analysis and dual luciferase reporter gene assay. Gain- and loss-of-function studies of miR-28-5p and Nrf2 were conducted to elucidate their effects on GC cell migration, invasion and metastasis, as well as expression pattern of several epithelial-mesenchymal transition (EMT)-related proteins. Results indicated that the expression pattern of Nrf2 was significantly upregulated in GC tissues and indicative of poor prognosis of GC patients. miR-28-5p was verified to target Nrf2 and downregulate its expression. GC cells with overexpression of miR-28-5p or Nrf2 knockdown exhibited a marked reduction in the migrated and invasive abilities, along with the N-cadherin expression yet an increase of E-cadherin expression. Furthermore, miR-28-5p exerted an inhibitory function on the metastatic and tumorigenicity of GC cells. In conclusion, miR-28-5p is a comprehensive tumor suppressor that inhibits GC cell migration and invasion through repressing the Nrf2 expression. Therefore, miR-28-5p may serve as a potential biomarker for the prognosis of GC and a novel therapeutic target in advanced GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Optimal Design and Operation of Intensified Absorbers with 3D-Printed Packing for Solvent-Based CO 2 Capture

Many potential solvent-based carbon capture processes suffer from a high heat of absorption of CO 2 that adversely affects the thermodynamic driving force. While interstage coolers are often used for removing a portion of the generated heat by removing the solvent or a portion of the solvent from a stage and cooling and returning it back to the absorber, they can be placed only at discrete locations in the tower. This work investigates intensified absorbers with 3D-printed packing that includes an internal cooler and therefore can be potentially used for maximizing the operational efficiency of the absorbers for CO 2 capture. The intensified absorber is modeled by using a generic, first-principles, equation-oriented absorber column model. Since the placement of these intensified packings would cause a loss of area/volume used for mass transfer, optimization of the proposed intensified absorber is performed by optimally selecting the locations at which to place these devices and designing them such that the trade-off due to the addition of the heat removal area and the resulting loss in the mass transfer area is accounted for. Results show that optimally placed and designed intensified packings can lead to a significant increase in the capture efficiency of the process in comparison to a similar column with no internal cooling. It is also observed that by optimally placing and designing intensified packings, the lean solvent flow rate to the absorber can be decreased, and the CO 2 lean loading can be increased while still maintaining the same capture efficiency. These process changes can lead to a substantial reduction in the cost of capture.

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

Efficient Training of Deep Neural Operator Networks via Randomized Sampling

Neural operators (NOs) employ deep neural networks to learn the mappings between infinitedimensional function spaces. Deep operator network (DeepONet), a popular NO architecture, has demonstrated success in the real-time prediction of complex dynamics across various scientific and engineering applications. In this work, we introduce a random sampling technique to be adopted during the training of DeepONet, aimed at improving the generalization ability of the model, while significantly reducing the computational time. The proposed approach targets the trunk network of the DeepONet model that outputs the basis functions corresponding to the spatiotemporal locations of the bounded domain on which the physical system is defined. While constructing the loss function, DeepONet training traditionally considers a uniform grid of spatiotemporal points at which all the output functions are evaluated for each iteration. This approach leads to a larger batch size, resulting in poor generalization and increased memory demands, due to the limitations of the stochastic gradient descent (SGD) optimizer. The proposed random sampling over the inputs of the trunk net mitigates these challenges, improving generalization and reducing the memory requirements during training, resulting in significant computational gains. We validate our hypothesis through three benchmark examples, demonstrating substantial reductions in training time while achieving comparable or lower overall test errors relative to the traditional training approach. Our results indicate that incorporating randomization in the trunk network inputs during training enhances the efficiency and robustness of DeepONet, offering a promising avenue for improving the framework’s performance in modeling complex physical systems.

Karumuri, Sharmila [Department of Civil & Systems ↗
DOE OSTI2020

Structural evolution at the oxidative and reductive limits in the first electrochemical cycle of Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2

High-energy-density lithium-rich materials are of significant interest for advanced lithium-ion batteries, provided that several roadblocks, such as voltage fade and poor energy efficiency are removed. However, this remains challenging as their functioning mechanisms during first cycle are not fully understood. Here we enlarge the cycling potential window for Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 electrode, identifying novel structural evolution mechanism involving a structurally-densified single-phase A’ formed under harsh oxidizing conditions throughout the crystallites and not only at the surface, in contrast to previous beliefs. We also recover a majority of first-cycle capacity loss by applying a constant-voltage step on discharge. Using highly reducing conditions we obtain additional capacity via a new low-potential P” phase, which is involved into triggering oxygen redox on charge. Altogether, these results provide deeper insights into the structural-composition evolution of Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 and will help to find measures to cure voltage fade and improve energy efficiency in this class of material.

25 ENERGY STORAGE↗
DOE OSTI2023

Compressing the Cosmological Information in One-dimensional Correlations of the Lyman-$\alpha$ Forest

Observations of the Lyman-α forest from spectroscopic surveys such as the Baryon Oscillation Spectroscopic Survey or its extension, eBOSS, or the ongoing Dark Energy Spectroscopic Instrument (DESI) survey offer a unique window to study the growth of structure on megaparsec scales. Interpretation of these measurements is a complicated task, requiring hydrodynamical simulations to model and marginalize over the thermal and ionization state of the intergalactic medium. This complexity has limited the use of Lyα clustering measurements in joint cosmological analyses. In this work we show that the cosmological information content of the one-dimensional power spectrum (P 1D ) of the Lyman-α forest can be compressed into a simple two-parameter likelihood without any significant loss of constraining power. We simulate P 1D measurements from DESI using hydrodynamical simulations and show that the compressed likelihood is model independent and lossless, recovering unbiased results even in the presence of massive neutrinos or running of the primordial power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Compartment-specific energy requirements of photosynthetic carbon metabolism in Camelina sativa leaves

Abstract Main conclusion The oxidative pentose phosphate pathway provides cytosolic NADPH yet reduces carbon and energy use efficiency. Repressing this pathway and introducing cytosolic NADPH-dependent malate dehydrogenase may increase crop yields by ≈5%. Abstract Detailed knowledge about plant energy metabolism may aid crop improvements. Using published estimates of flux through central carbon metabolism, we phenotype energy metabolism in illuminated Camelina sativa leaves (grown at 22 °C, 500 µmol photons m −2 s −1 ) and report several findings. First, the oxidative pentose phosphate pathway (OPPP) transfers 3.3% of the NADPH consumed in the Calvin–Benson cycle to the cytosol. NADPH supply proceeds at about 10% of the rate of net carbon assimilation. However, concomitantly respired CO 2 accounts for 4.8% of total rubisco activity. Hence, 4.8% of the flux through the Calvin–Benson cycle and photorespiration is spent on supplying cytosolic NADPH, a significant investment. Associated energy requirements exceed the energy output of the OPPP. Thus, autotrophic carbon metabolism is not simply optimised for flux into carbon sinks but sacrifices carbon and energy use efficiency to support cytosolic energy metabolism. To reduce these costs, we suggest bioengineering plants with a repressed cytosolic OPPP, and an inserted cytosolic NADPH-dependent malate dehydrogenase tuned to compensate for the loss in OPPP activity (if required). Second, sucrose cycling is a minor investment in overall leaf energy metabolism but a significant investment in cytosolic energy metabolism. Third, leaf energy balancing strictly requires oxidative phosphorylation, cofactor export from chloroplasts, and peroxisomal NADH import. Fourth, mitochondria are energetically self-sufficient. Fifth, carbon metabolism has an ATP/NADPH demand ratio of 1.52 which is met if ≤ 21.7% of whole electron flux is cyclic. Sixth, electron transport has a photon use efficiency of ≥ 62%. Last, we discuss interactions between the OPPP and the cytosolic oxidation–reduction cycle in supplying leaf cytosolic NADPH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Investigating the Role of Accident Tolerant Cladding on Source Term Reduction for High-Burnup PWRs Using MELCOR

The use of accident tolerant fuel (ATF) cladding can increase coping times during and beyond design basis accidents. While such gains may be incremental, they provide a margin that can potentially be recovered to enable high-burnup (HBU) operation. Realizing such a margin requires demonstrating that the combination of HBU and ATF has not led to an overall increase in source term. This study investigates the influence of cladding technology (Zr-based, Cr-coated Zr, and FeCrAl) and fuel cycle length (18 and 24 months) on radiological dose at the boundary of the exclusion zone for a four-loop pressurized water reactor to investigate whether ATF claddings can provide such benefits. We analyze a recovered large break loss-of-coolant accident scenario to investigate the impact of transient timescale on the benefits of such coping time increases. The simulations have been performed using the MELCOR and MELCOR Accident Consequence Code System codes. For the cases analyzed, increased fuel cycle length did not necessarily increase radionuclide release and hydrogen generation, as these were found to be sensitive to the core power distribution. Similarly, off-site dose consequence is dominated by short-lived radionuclides that tend to saturate earlier in the burnup, so higher burnup operation did not necessarily increase the source term for the phenomena and transients analyzed here. Delays in recovery of the lowpressure safety injection system increase hydrogen production and radionuclide release, especially between 780 s and 1620 s, due to the nonlinear oxidation and core degradation behavior. Results show that Cr-coated Zr enhances safety by delaying heatup and gap release. Here, when uncertainty propagation on oxidation properties is considered, FeCrAl exhibits the lowest overall radionuclide release and off-site dose throughout the spectrum. However, while the considered “base model” performance is superior under delayed injection scenarios, upper-bound cases display hydrogen generation risk comparable to the Zr-based cladding.

Accident Tolerant Fuel↗
DOE OSTI2020

In silico assessment of the potential of basalt amendments to reduce N 2 O emissions from bioenergy crops

Abstract The potential of large‐scale deployment of basalt to reduce N 2 O emissions from cultivated soils may contribute to climate stabilization beyond the CO 2 ‐removal effect from enhanced weathering. We used 3 years of field observations from maize ( Zea mays ) and miscanthus ( Miscanthus × giganteus ) to improve the nitrogen (N) module of the DayCent model and evaluate the potential of basalt amendments to reduce N losses and increase yields from two bioenergy crops. We found 20%–60% improvement in our N 2 O flux estimates over previous model descriptions. Model results predict that the application of basalt would reduce N 2 O emissions by 16% in maize and 9% in miscanthus. Lower N 2 O emissions responded to increases in the N 2 :N 2 O ratio of denitrification with basalt‐induced increases in soil pH, with minor contributions from the impact of P additions (a minor component of some basalts) on N immobilization. The larger reduction of N 2 O emissions in maize than in miscanthus was likely explained by a synergistic effect between soil pH and N content, leading to a higher sensitivity of the N 2 :N 2 O ratio to changes in pH in heavily fertilized maize. Basalt amendments led to modest increases in modeled yields and the nitrogen use efficiency (i.e., fertilizer‐N recover in crop production) of maize but did not affect the productivity of miscanthus. However, enhanced soil P availability maintained the long‐term productivity of crops with high nutrient requirements. The alleviation of plant P limitation led to enhanced plant N uptake, thereby contributing to lower microbial N availability and N 2 O emissions from crops with high nutrient requirements. Our results from the improved model suggest that the large‐scale deployment of basalt, by reducing N 2 O fluxes of cropping systems, could contribute to the sustainable intensification of agriculture and enhance the climate mitigation potential of bioenergy with carbon capture and storage strategies.

59 BASIC BIOLOGICAL SCIENCES↗