Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “loss reduction”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Where Have All of the Electrons Gone? Understanding the Role of Alternative Electron Flow and O 2 Reduction in Balancing Cellular Redox (Final Technical Report)

An informed understanding of the fundamentals of light-driven electron transfer reactions in photoautotrophic organisms is necessary to enable improved photosynthetic efficiencies for the production of renewable fuels and novel biomaterials. To obtain high photosynthetic yields, light energy must be efficiently coupled to the fixation of CO 2 . Sub-optimal environmental conditions and metabolic routing (caused by blocks in biosynthetic routes) can severely impact the conversion of light energy to biomass and lead to reactive oxygen production, which in turn can cause cellular damage and productivity losses. Hence, plants, algae, and photosynthetic bacteria have evolved a network of alternative outlets to sustain the flow of photosynthetically derived-electrons. Our research was focused on the nature and integration of these outlets. The data obtained in this project will inform efforts to rationally engineer crop plants and algae to improve photosynthetic yields by enhancing electron transfer reactions to CO 2 reduction and targeted biomass accumulation. A major project research thrust was focused on identifying and quantifying the flow of photosynthetic reductant through electron transfer circuits that result in the light-dependent reduction of O 2 . New energy management strategies were identified that are used when normal carbon assimilation pathways are compromised due to nutrient deprivation, and/or by a reduction in starch synthesis/carbon storage, all conditions resulting in highly reduced intracellular redox pools. The green alga Chlamydomonas reinhardtii, and likely many other algae, have multiple O 2 -reducing pathways that play critical roles in maintaining cellular metabolic balance and scavenging electrons that could potentially cause cellular damage, which in some instances leads to reduced photosynthetic yields but increased fitness. We explored the activities of three essential outlets associated with Chlamydomonas reinhardtii photosynthetic electron transport: (1) reduction of O 2 to H 2 O through Flavodiiron proteins (FLVs) and (2) Plastid Terminal Oxidases (PTOX), and (3) the synthesis of starch. Real-time measurements of O 2 exchange demonstrated that FLVs immediately engage during dark to light transitions, allowing electron transport when the CBBC is not fully activated. Under these conditions, we quantified, for the first time, maximal FLV activity and its overall capacity to direct photosynthetic electrons towards O 2 reduction. However, when starch synthesis is compromised, a greater proportion of electrons is directed toward O 2 reduction through the FLVs, while PTOX, which is sensitive to the PQ pool redox state, is activated. This suggests, that starch synthesis has an important role in priming/regulating CBBC and electron transport. We also identified a biological ‘switch’ in the green alga Chlamydomonas reinhardtii that reversibly restricts photosynthetic electron transport (PET) at the cytochrome b 6 f complex when reductant and ATP generated by PET are in excess of the capacity of carbon metabolism to utilize these products; we specifically show a restriction at this switch when sta6 mutant cells, which cannot synthesize starch, are limited for nitrogen (growth inhibition) and subjected to a dark to light transition. This restriction causes diminished electron flow to PSI, which prevents PSI photodamage, and the plastid alternative oxidase (PTOX) becomes fully activated, serving as an electron valve that dissipates excitation energy absorbed by PSII, thereby lessening PSII photoinhibition. Furthermore, illumination of the cells following the dark acclimation gradually diminishes the restriction at the switch. Future engineering of these switches may allow more effective electron transfer to lipid (biofuel) pathways and diminish the number of electrons “wasted” in the reduction of O 2 to water. Lastly, we explored metabolic routing of electrons during algal fermentation and discovered multiple novel pathways that are activated when the preferred anoxic routes are blocked. These provide valuable products (e.g. lactate, glycerol) that can be used in broad portfolio of biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tailoring Carbide Dispersed Steels: A Path to Increased Strength and Hydrogen Tolerance

The use of transition metal carbides is reported for use as a hydrogen trapping mechanism for ferritic and austenitic steel materials. The program combined computational modeling and simulations to guide experiments towards candidate metal carbide traps, both for interfacial and interior trapping. It was found that interfacial trapping is less effective than interior trapping, with the group IVB transition metal carbides being the most effect internal traps with a loss of carbon. The sub-stoichiometric rocksalt structure accommodate the hydrogen atoms in its octahedral interstices. Using percolation theory, carbon loss of approximately 25% or more was sufficient to ensure an interconnected network of vacancies for such trapping from the surface to the internal sites within the carbide. Using this as a guide, the program developed a means to provide a uniform dispersion of ZrC nanoparticles with either Fe or 304L micron-scale powders which was then consolidated by direct current sintering. Electrolytic hydrogen diffusivity studies confirmed the reduction of hydrogen diffusion in the matrix with increasing ZrC content, which was a linear response over the sample range studied (0.01 to 1.0 wt.%). The consolidated material was micro-tensile tested in either a non-hydrogen or hydrogen charge condition and compared to a control with no carbides. Additions up to 0.05 wt.% ZrC increased the yield strength with no loss in ductility in either the non-hydrogen or hydrogen tested condition. ZrC concentrations above this amount further increased the yield strength at the expense of ductility. While these samples had a lower absolute ductility value prior to failure, the relative change in ductility between the non-hydrogen and hydrogen charge states was less for the carbides than that of the control. Metal-rich ZrC nanoparticles were fabricated through a conformal coating process yielding ZrC0.66 particles that were then incorporated into a metal matrix. Notch fatigue testing in a hydrogen environment was conducted where the number of cycles to failure was found to be less in the control than that of the carbide addition. However, the spread in experimental data and the number of samples tested limits a conclusive outcome based on defects noticed in the gauge section of all the powder processed samples. The collective outcomes of this report provide further insight into the mechanisms by which carbides act as hydrogen traps; a means to process such carbides through powder metallurgy; and their associated mechanical performance in either a non-hydrogen or hydrogen-charged condition.

08 HYDROGEN↗
DOE OSTI2022

Efficient monolithic all-perovskite tandem solar modules with small cell-to-module derate

All-perovskite tandem solar modules are promising to reduce the cost of photovoltaic systems with their high efficiency and solution fabrication, but their sensitivity to air still imposes a great challenge. Here a hot gas-assisted blading method is developed to accelerate the perovskite solidification, forming compact and thick narrow bandgap (NBG) perovskite films. Adding a reduction agent into NBG films followed by a short period of air exposure and a post-fabrication storage surprisingly increases carrier recombination lifetime and enables laser scribing in ambient conditions without obvious loss of device performance. This combination suppresses tin and iodide oxidation and forms a thin SnO 2 layer on the NBG film surface. Monolithic all-perovskite tandem solar modules showed a champion efficiency of 21.6% with a 14.3 cm 2 aperture area, corresponding to an active area efficiency of 23.0%. Lastly, the very small cell-to-module derate of 6.5% demonstrates the advantage of a tandem monolithic structure for solar modules.

14 SOLAR ENERGY↗
DOE OSTI2024

Active control of Alfvén eigenmodes by external magnetic perturbations with different spatial spectra

Alfvén eigenmodes have been suppressed and excited in tokamak plasmas by (just) modifying the poloidal spectra of externally applied static magnetic perturbations. This effect is observed experimentally when toroidal spectra of n = 2, n = 4 as well as a mixed spectrum of n = 2 and n = 4 is applied. Under the n = 2 magnetic perturbations, the modes are excited or suppressed by modifying the coil phasing between the upper and the lower set of coils. Regardless of the absolute rotation, an even parity for the n = 4 perturbation is observed to reduce the amplitude of the Alfvénic instabilities, while an odd parity amplifies it. To combine the stabilizing (and destabilizing) effect of n = 2 and n = 4, a mixed spectrum is applied, finding similar reduction (and amplification) trends. However, the impact on the mode amplitude is more subtle, due to the reduced coil current required for a mixed spectrum. The signal level on the fast-ion loss detector is sensitive to the applied poloidal spectrum, which is consistent with Hamiltonian full-orbit modelling of an edge resonant transport layer activated by the 3D perturbative fields. An internal redistribution of the fast-ion population is induced, modifying the phase-space gradients driving the Alfvénic instabilities, and ultimately determining their existence. The calculated edge resonant layers for both n = 2 and n = 4 toroidal spectra are consistent with the observed suppressed and excited phases. Moreover, hybrid kinetic-magnetohydrodynamic (MHD) simulations reveal that this edge resonant transport layer overlaps in phase-space with the population responsible for the fast-ion drive. The results presented here may help to control fast-ion driven Alfvénic instabilities in future burning plasmas with a significant fusion born alpha particle population.

Alfvén waves↗
DOE OSTI2024

A Redox-Electrodialysis Model with Zero Fitting Parameters: Insights into Process Limitations, Design, and Material Interventions

Redox-Electrodialysis (r-ED) is an electrochemical desalination cell architecture that has recently received considerable interest, due to its low energy demand relative to electrochemical desalination technologies that rely on electrode-based ion removal. To further improve the energy efficiency of r-ED, we developed a lumped mathematical model with no adjustable parameters to investigate the various sources of overpotential within the cell. Existing models of electrodialysis and r-ED cells either do not accurately incorporate all phenomena contributing to the overpotential or utilize empirical fitting parameters. The model developed here indicates that ohmic overpotentials, especially in the diluate chamber, are the most significant contributors to energy losses. Based on this insight, we hypothesized that adding an ion exchange resin wafer in the diluate compartment would increase the ionic conductivity and decrease the energy demand. Experimental results showed an 18% reduction in specific energy use while achieving the same degree of salt removal (20 mM to 12 mM). Furthermore, the resin wafer enabled complete desalination to potable drinking levels at a current density previously unachievable within practical operating voltage limits (4.93 mA cm -2 ). We also expanded the model to explore differences in r-ED energy use between configurations using multiple cells and a single cell with increased area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High-Temperature Linear Receiver Enabled by Multicomponent Aerogels

Concentrating solar thermal (CST) technology has significant potential mainly due to its dispatchability and low cost of storage. However, to compete with other sources, including utility-scale solar PV, its final cost (cents/kWh) still needs to be lowered. Cost reduction can be achieved by improving the system level efficiency of the CST plants through the deployment of advanced power cycles, which operate at high temperatures of ~700°C. However, optical, and thermal losses pose a major challenge to the efficiency of such CST systems. The overall aim of this project is to investigate and de-risk a linear solar receiver concept called an Aerogel Insulated Receiver (AIR) that generates high temperatures (up to 700°C) at a low solar concentration ratio (<100) and with a high collection efficiency (optical × receiver). Our prior work has demonstrated the thermal stability1 and optical and heat-insulating properties2,3 of transparent aerogel insulation at a one-inch scale. The focus of this work is on (1) co-optimization of the geometry of the aerogel tile and receiver enclosure to fit a standard parabolic collector (PTC), (2) scale-up of aerogels into 4-inch tiles while preserving key properties, (3) experimental measurement of receiver heat loss (W/m) in a >70-cm test stand and validation of anticipated receiver performance at high temperatures. Regarding (1), appropriate optical and thermal models for a parabolic trough receiver (PTR) are developed and validated. The geometry of the aerogels and the receiver enclosure are co-optimized to maximize the collection efficiency. The model predicts a 54% collection efficiency at 700°C for an AIR design based on flat aerogels. By combining the collection efficiency with the power block efficiency of supercritical CO 2 cycles, we predict >10% improvements in peak plant efficiency relative to existing line-focusing CST systems. The application of curved plasmonic aerogels is predicted to further increase the collection efficiency to 64%. Regarding (2), we demonstrate the successful development of 6-inch-long refractory aerogel tiles with optical, thermal, and stability characteristics consistent with our prior work. This scale-up requires a transition to a larger ALD station and modifying the ALD process variables such as exposure time and the number of precursor doses. Regarding (3), we design and develop an AIR test stand measuring 3 feet in length. Heat loss performance analysis is carried out using the test stand. The results indicate that aerogel insulation can significantly reduce receiver thermal losses at the high operating temperatures required for next-generation PTRs. The experimental results agree with the heat loss performance predicted by our receiver model. Lastly, we conducted preliminary failure mode and effects (FMEA) and techno-economic (TEA) analyses to identify failure mitigation strategies and commercial opportunities, respectively. Overall, this project identifies key opportunities and challenges in deploying aerogel insulating receivers in next-generation line-focusing CST technologies.

14 SOLAR ENERGY↗
DOE OSTI2024

Application of Modified Meshgraphnets for Subsurface Prediction during CO2 Sequestration

In the face of the increasingly dire consequences of anthropogenic climate change, capturing and storing carbon dioxide is paramount. However, several impediments exist to the safe and effective subsurface storage of CO2, such as cost of transport, identification of suitable sites for subsurface storage, and assessment of long-term risk from storage in subsurface aquifers. Accurate subsurface modeling is necessary to ensure that CO2 storage is both safe and effective. Still, such modeling has traditionally required either substantial time and computational power (numerical simulation) or a substantial amount of pre-existing data for training (machine learning models). Additionally, these models lack flexibility in dealing with both changes in discretization of the input data and generalizability beyond the data on which they are trained. In order to address these issues, this research applies graph neural networks (GNNs) to predict subsurface saturation and pressure during CO₂ injection in a model of the Illinois Basin-Decatur Project (IBDP). GNNs provide a flexible, intuitive method for representing and manipulating complex unstructured data, which is often found in many practical domain problems such as fluid flow and subsurface characterization. These unstructured grids are easily represented in GNNs by representing spatially-localized features such as permeability, porosity, saturation, and pressure as nodes in a graph and relationships between these properties as edges connecting these nodes. This research applies a specific GNN model called MeshGraphNets (MGN) to model the change in CO2 saturation and pressure over a 50-month time period (36 months of injection, 14 months post-injection). The MGN model leverages a message passing process that allows the network to learn both the spatial and temporal dynamics of this system simultaneously. Additionally, training on a limited dataset (64 realizations, 20 time points each) resulted in a high degree of accuracy in saturation prediction both within the same timeframe as the training (20 months, 0.039 average RMSE) and when projecting out to the end of injection (36 months, 0.053 average RMSE). Temporal predictions such as those generated by MGNs and other similar models are prone to accumulated error over time; in order to address this, a multi-step rollout (MSR) training process was applied to calculate training loss. This method mimics the forward prediction during inference by “rolling out” multiple time points in a single training step using the previous prediction as input to the MGN model. By calculating the loss several time steps forward from the current prediction, the model is forced to find a more stable state over time. Application of MSR to the MGN model resulted in an average 15% reduction in inference error over time during forward prediction. This study showcases the immense potential of GNNs as a game-changing methodology for predicting pressure and saturation evolution in CCS projects, ultimately paving the way for more sustainable and effective carbon storage solutions. Presentation prepared for the 2024 AiChE Annual Meeting, October 27 to November 1 2024, San Diego, CA.

Holcomb, Paul↗
DOE OSTI2022

Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation

Remote sensing estimation of evapotranspiration (ET) directly quantifies plant water consumption and provides essential information for irrigation scheduling, which is a pressing need for California vineyards as extreme droughts become more frequent. Many ET models take satellite-derived Leaf Area Index (LAI) as a major input, but how uncertainties of LAI estimations propagate to ET and the partitioning between evaporation and transpiration is poorly understood. Here we assessed six satellite-based LAI estimation approaches using Landsat and Sentinel-2 images against ground measurements from four vineyards in California and evaluated ET sensitivity to LAI in the thermal-based two-source energy balance (TSEB) model. We found that radiative transfer modeling-based approaches predicted low to medium LAI well, but they significantly underestimated high LAI in highly clumped vine canopies (RMSE ~ 0.97 to 1.27). Cubist regression models trained with ground LAI measurements from all vineyards achieved high accuracy (RMSE ~ 0.3 to 0.48), but these empirical models did not generalize well between sites. Red edge bands and the related vegetation index (VI) from the Sentinel-2 satellite contain complementary information of LAI to VIs based on near-infrared and red bands. TSEB ET was more sensitive to positive LAI biases than negative ones. Positive LAI errors of 50% resulted in up to 50% changes in ET, while negative biases of 50% in LAI caused less than 10% deviations in ET. However, even when ET changes were minimal, negative LAI errors of 50% led to up to a 40% reduction in modeled transpiration, as soil evaporation and plant transpiration responded to LAI change divergently. These findings call for careful consideration of satellite LAI uncertainties for ET modeling, especially for the partitioning of water loss between vine and soil or cover crop for effective vineyard irrigation management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

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

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗
DOE OSTI2022

Ion-Pair Reorganization Regulates Reactivity in Photoredox Catalysts

Cyclometalated and polypyridyl complexes of d6 metals are promising photoredox catalysts, using light to drive reactions with high kinetic or thermodynamic barriers via the generation of reactive radical intermediates. However, while tuning of their redox potentials, absorption energy, excited-state lifetime and quantum yield are well-known criteria for modifying activity, other factors could be important. Here we show that dynamic ion-pair reorganization controls the reactivity of a photoredox catalyst, [Ir[dF(CF3)ppy]2(dtbpy)]X. Time-resolved dielectric-loss experiments show how counter-ion identity influences excited-state charge distribution, evincing large differences in both the ground- and excited-state dipole moment depending on whether X is a small associating anion (PF6-) that forms a contact-ion pair versus a large one that either dissociates or forms a solvent-separated pair (BArF4-). These differences correlate with the reactivity of the photocatalyst toward both reductive and oxidative electron transfer, amounting to a 4-fold change in selectivity toward oxidation versus reduction. These results suggest that ion pairing could be an underappreciated factor that modulates reactivity in ionic photoredox catalysts.

catalysis↗
DOE OSTI2025

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗
DOE OSTI2025

Electronic and reactivity changes in epitaxially grown Ce 1-x Zr x O 2-δ (111) thin films

Ceria composite catalysts have long been used for ketonization reactions, which is a valuable chemistry for the upgrading of biomass-derived carboxylates. To better understand the interaction of zirconia with ceria in the context of ketonization, thin epitaxial films of ceria-zirconia mixed metal oxide Ce 1-x Zr x O 2-δ (x = 0-1) were grown on a Pt(111) substrate in ultrahigh vacuum conditions and studied with X-ray photoelectron spectroscopy (XPS). Core level and valence band XPS results suggest a strong interaction between ceria and zirconia cations, possibly due to increased filling of unoccupied 4f 0 orbitals of ceria from neighboring Zr cations in the lattice structure. This leads to a partial reduction of ceria from Ce 4+ to Ce 3+ , with Zr remaining predominantly in the 4+ oxidation state. Ketonization of acetic acid was studied using temperature programmed desorption (TPD) and high-resolution electron energy loss spectroscopy (HREELS). These results found ketonization over mixed Ce-Zr composite oxides exhibited lower activation energies than for pure CeO 2 and ZrO 2 , with Ce 0.38 Zr 0.62 O 2-δ exhibiting the highest yield of acetone among the studied surfaces. In conclusion, these results suggest the high activity of Ce-Zr catalysts appears to be a result of oxygen vacancy formation, stabilized by electron donation from Zr cations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Disruption thermal load mitigation with shattered pellet injection on the Joint European Torus (JET)

Disruption mitigation remains a critical, unresolved challenge for ITER. To aid in addressing this challenge, a shattered pellet injection (SPI) system was installed on JET and experiments conducted at a range of thermal energy fractions and stored energies in excess of 7 MJ. The primary goals of these experiments were to investigate the efficacy of the SPI on JET and the ability of the plasma to assimilate multiple pellets. Single pellet injections produced a saturation in total radiated energy (Wrad) with increasing injected neon content, suggesting total radiation of stored thermal energy. Further increases in injected neon quantities resulted in reduced cooling times and current quench (CQ) durations, indicating higher impurity assimilation. No significant variation in CQ duration or W rad was observed when varying the deuterium content at fixed neon quantities. Additionally, higher assimilation, inferred by shorter CQ durations, was measured when a mechanical punch was used to launch the pellets and this was attributed to a lower pellet velocity leading to higher solid content in the pellet plume and larger fragments penetrating deeper into the plasma. Radiation asymmetries averaged over the cooling time were inferred from Emis3D and ranged from 1.6 to 1.9. Asymmetries averaged over the entire disruption sequence were found to increase at higher thermal energy fractions. The radiated energy fractions decreased with increasing thermal energy fractions but this trend was eliminated when toroidal asymmetries were accounted for with Emis3D. Pure deuterium pellets were able to produce cooling times of up to 75 ms with a gradual loss in thermal stored energy of up to 80%. Experiments with multiple pellet injection indicated W rad can be increased through pellet superposition and density can be increased with an additional D2 injection without a reduction in W rad . KPRAD modelling accurately reproduced the cooling times and the CQ duration at high thermal energies. Assimilation estimates from KPRAD indicated CQ rates scale strongly whilst W rad scales weakly and saturates with assimilated neon content. Comparable W rad can be achieved with lower assimilated neon quantities as longer cooling times are attained. Thus reduced neon content can be preferential in a thermal load mitigation scheme as it may reduce radiation asymmetries and prevent flash melting.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

High-Q suspended optical resonators in 3C silicon carbide obtained by thermal annealing

We fabricate suspended single-mode optical waveguides and ring resonators in 3C silicon carbide (SiC) that operate at telecommunication wavelength, and leverage post-fabrication thermal annealing to minimize optical propagation losses. Annealed optical resonators yield quality factors of over 41,000, which corresponds to a propagation loss of 7 dB/cm, and is a significant improvement over the 24 dB/cm in the case of the non-annealed chip. This improvement is attributed to the enhancement of SiC crystallinity and a significant reduction of waveguide surface roughness, from 2.4 nm to below 1.7 nm. The latter is attributed to surface layer oxide growth during the annealing step. We confirm that the thermo-optic coefficient, an important parameter governing high-power and temperature-dependent performance of SiC, does not vary with annealing and is comparable to that of bulk SiC. Our annealing-based approach, which is especially suitable for suspended structures, offers a straightforward way to realize high-performance 3C-SiC integrated circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Analysis of PV Fleet Performance in Western United States During August 2020 Extreme Heat Wave

Starting in June 2020 through the end of that year, the western and central United States experienced a widespread heat wave and drought, which resulted in US$5.44 billion (CPI-adjusted) worth of damages. The ongoing heat and drought produced record large wildfires across the region, responsible for an additional US$19.9 billion in damage. These natural disasters directly impacted the energy system in the western US, leading to power blackouts in August 2020. In this work, we analyze the NLR PV Fleets data set, focusing on the geographic area covered by the Western Coordinating Council (WECC). We find that over the 10-day period from August 14 through 24, the median PV system produced 12% lower energy than expected, with some locations experiencing total losses of around 30%. Analyzing the spatial-temporal structure of the data and supplementing with limited operational current and voltage data where available, we find that system underperformance was more strongly impacted by irradiance reduction from wildfire smoke rather than by the high heat itself.

14 SOLAR ENERGY↗
DOE OSTI2025

Fuel Bonding and its Impact on Axial Gas Communication Behavior in Light-Water Reactor Fuel Rods

Axial gas communication concerns the flow along the axial axis of nuclear fuel rods during ramp and loss of coolant accident (LOCA) conditions. During power ramps, the higher linear heat generation rate may cause fuel-to-clad gap closure that may prevent transport of released fission gases to the plenum. Upon reduction in power the gas then can communicate to the plenum. This phenomenon has been experimentally observed by short power dips during ramp experiments completed at the Risø reactor. At higher burnups it is observed that the UO2 fuel and Zircaloy cladding forms a chemical bond. This bond results in complete closure of the gap. When these high burnup rods are subjected to a LOCA, the bond has implications on both the mechanical response (i.e., ballooning) of the cladding and subsequent fuel relocation and axial gas communication. In the LOCA scenario, gas communication is of interest in two different regimes: 1) pre-rupture communication from the plenum towards the lower pressure ballooning area and 2) the post-rupture depressurization of the plenum to the external system pressure. In both regimes the presence of a fuel-to-cladding bond will impact the rate of depressurization. In this work we present a fuel-to-clad bonding model that is coupled to an existing axial gas communication model framework in the BISON fuel performance code. The effect of considering the bond on fuel performance modeling predictions is presented through comparisons to existing experimental data. Experiments considered include several rods from the Halden IFA-650 test series. An evaluation on a full-length rod that explores the combined effect of plenum size and bonding status on axial gas communication behavior is also presented.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

How nitrogen and oxygen shape SRF cavity performance

Nitrogen and oxygen-based surface treatments have revolutionized the performance of superconducting radiofrequency (SRF) cavities, enabling them to reach higher gradients and lower losses. However, the exact mechanisms by which these treatments improve cavity performance remain largely unknown. This work provides new insights into the role of nitrogen and oxygen in SRF cavity performance by using time-of-flight secondary ion mass spectrometry (TOF-SIMS) to precisely quantify the concentrations and depth profiles of these impurities within niobium cutouts. We correlate these impurity profiles with detailed cavity performance measurements, including surface resistance and quality factor, and compare our findings with predictions from BCS theory. The results demonstrate that while both nitrogen and oxygen enhance performance, ten times more oxygen is required to achieve the same reduction in BCS resistance as interstitial nitrogen. We present a potential model in which the observed variation arises from nitrogen's greater effectiveness in trapping hydrogen, thus reducing the formation of niobium hydrides and enhancing superconducting gap.

Hu, Hannah [Chicago U.]↗