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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This study aimed to study the impact of continuous positive airway pressure (CPAP) on chest anatomy and tumor motion in patients receiving radiation therapy.
One of the most challenging and consequential problems in climate modeling is to provide probabilistic projections of sea level rise. A large part of the uncertainty of sea level projections is due to uncertainty in ice sheet dynamics. At the moment, accurate quantification of the uncertainty is hindered by the cost of ice sheet computational models. In this work we develop a hybrid approach to approximate existing ice sheet models at a fraction of their cost. Our approach consists of replacing the finite element model for the momentum equations for the ice velocity, the most expensive part of an ice sheet model, with a Deep Operator Network, while we retain a classic finite element discretization for the evolution of the ice thickness. We show that the resulting hybrid model is very accurate and it is an order of magnitude faster than the traditional finite element model. Further, a distinctive feature of the proposed model, compared to other neural network approaches, is that it can handle high-dimensional parameter spaces (parameter fields) such as the basal friction at the bed of the glacier and can therefore be used for generating samples for uncertainty quantification. Further, we study the impact of hyper-parameters, number of unknowns and correlation length of the parameter distribution on the training and accuracy of the Deep Operator Network on a synthetic ice sheet model. We then target the evolution of the Humboldt glacier in Greenland and show that our hybrid model can provide accurate statistics of the glacier mass loss and can be effectively used to accelerate the quantification of uncertainty.
The dislocation dense cellular structures observed in additively manufactured (AM) stainless steels can allow these materials to have enhanced strength and ductility compared to conventionally manufactured materials. Effective design of radiation resistant materials often necessitates creating microstructures containing of a high density of dislocations that act as sinks for radiation induced defects. This work uses molecular dynamics simulations to study the impact of pre-existing defects on radiation damage in stainless steel 316L fabricated by the laser powder bed fusion process. The evolution of synthetically generated dislocations in a crystal system in response to multiple radiation collision cascades suggest that dislocation dense regions reduce the probability of surviving point defects forming clusters. This finding seems to result from the dislocation cores’ ability to absorb point defects, thereby limiting the formation of clusters during the recombination phase. However, after successive cascades, the ability of the dislocation entanglement to prevent defect formation is diminished and defect cluster formation trends to an equilibrium. Accordingly, it is hypothesized that in an experimental setting the dislocation cells will initially act as neutral sinks for point defects, potentially delaying the onset of radiation damage effects; but, these structures will be degraded due to radiation-enhanced diffusion and lose their effectiveness at doses above 1.5–2 displacements per atom. Nevertheless, the ability to produce complex and feature-specific microstructures suggests promise for the design of radiation tolerant materials using AM methods.
In-situ neutron diffraction and ex-situ dilatometry experiments were performed on a chemically banded, quenched uranium-6wt% niobium shape memory alloy to study the impact of deformation-(detwinning-) induced texture on the evolution of thermally induced strains (and associated stresses). Thermal heating and cooling cycles between 5K and 473K were performed in-situ with neutron diffraction, and the lattice strain evolution is reported for the observed monoclinic α" phase. Comparisons between the measured diffraction strains and macroscopic dilatometry experiments reveal relationships between micro- and macro-level thermal expansion. Softening of the texture during heating suggests that twin boundary motion can accommodate the large internal thermal strains which are approximately 2% greater than that typically observed during the 175K heating interval used to age more randomly oriented polycrystalline material. Assuming weak constraint of neighboring grains in randomly textured polycrystals, the single crystal thermal expansion tensor is extracted from measurements of lattice strains over the range 5K to 473K. Predictions of polycrystalline thermal expansion, based upon this single crystal thermal expansion tensor, are shown to compare favorably with bulk thermal expansion observations of the as quenched microstructure. However, such a lower-bound estimate is insufficient to explain all aspects of the behavior of the textured material, where the matrix is not isotropic. In conclusion, it is hypothesized that relaxation processes which occur within the quenched microstructure during heating are responsible for the distinct thermal expansion behavior observed during the initial heating cycle compared to cooling and subsequent cycling.
The vertical structure of vegetation canopies creates micro-climates. However, the land components of most Earth System Models, including the Energy Exascale Earth System Model (E3SM), typically neglect vertical canopy structure by using a single layer big-leaf representation to simulate water, CO 2 , and energy exchanges between the land and the atmosphere. In this study, we developed a Multi-Layer Canopy Model for the E3SM Land Model to resolve the micro-climate created by vegetation canopies. The model developed in this study re-implements the CLM-ml_v1 to support heterogeneous computing architectures consisting of CPUs and GPUs and includes three additional optimization-based stomatal conductance models. The use of Portable, Extensible Toolkit for Scientific Computation provides a speedup of 25–50 times on a GPU relative to a CPU. The numerical implementation of the model was verified against CLM-ml_v1 for a month-long simulation using data from the Ameriflux US-University of Michigan Biological Station site. Model structural uncertainty was explored by performing control simulations for five stomatal conductance models that exclude and include the control of plant hydrodynamics (PHD) on photosynthesis. The bias in simulated sensible and latent heat fluxes was lower when PHD was accounted for in the model. Additionally, six idealized simulations were performed to study the impact of three environmental variables (i.e. air temperature, atmospheric CO 2 , and soil moisture) on canopy processes (i.e. net CO 2 assimilation, leaf temperature, and leaf water potential). Increasing air temperature reduced net CO 2 assimilation and increased air temperature. Net CO 2 assimilation increased at higher atmospheric CO 2 , while decreasing soil moisture resulted in lower leaf water potential.
Performance of symmetric-architecture metal-supported solid oxide fuel cells was improved significantly by optimizing the catalyst infiltration process and metal support structure. Optimization of component structure and processing parameters was performed during tape-casting and fabrication of button cells. Mass transport of oxygen in the metal support was identified as a major limitation. To overcome this limitation, pore former loading and thickness of the metal support (130–250 μm) were optimized. The catalyst infiltration process was also improved by studying the impact of firing temperature (400 °C–900 °C) and infiltration cycle numbers (1–15). The maximum power density of the optimized cell was 0.9 W cm –2 at 700°C using hydrogen as a fuel, a three-fold increase over the baseline cell performance. The degradation rate of optimized cells at 550 °C, 600 °C, and 700 °C was 2%, 4.5%, and 5.5% per 100 h, respectively. Here, the phenomena of mass transport, catalyst coarsening, and chromium poisoning on the catalyst were analyzed by electrochemical impedance spectroscopy and scanning electron microscopy.
The transition metal carbides have been known to act as traps for hydrogen in steels as well as potential materials for hydrogen storage. Despite numerous experimental and a few theoretical studies, what impacts hydrogen trapping and storage in the transition metal carbides is not well understood. In this work, we use density functional theory to systematically investigate the bulk trapping and storage capabilities of the transition metal carbides. We specifically examine how trapping and storage changes with the transition metal, from the group IVB to group VIB, carbon concentration, and structure. Our results demonstrate a strong correlation between the trap energy and the number of valence electrons in the transition metal, suggesting that the group IVB transition metal carbides are the best carbides for trapping and storage. Hydrogen preferentially sits at octahedral interstices, e.g., the carbon vacancies, in the structure except in certain cases near the Me 2 C concentration when tetrahedral interstices, devoid of nearest neighbor carbon, can become more favorable. Our results further demonstrate that the lower the carbon concentration, the more hydrogen the transition metal carbide can store. These results demonstrate which carbides will act as the best traps for hydrogen.
This work studies the impact of explicit and homogenized modeling approaches on the multiphysics simulation of TRistructural ISOtropic (TRISO) fuel compacts in prismatic High Temperature Gas Reactors (HTGRs) and the silver release predictions. TRISO fuel compacts exhibit complex double heterogeneity that significantly affects heat conduction, neutron transport, and fission products release. In this work, we use Cardinal, a multiphysics tool based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to couple neutron transport and heat conduction. OpenMC is used for neutron transport and the MOOSE heat transfer module is used for the heat conduction. Then, we use BISON for the silver release predictions. Two different modeling approaches—explicit modeling of individual TRISO particles and homogenized representation using effective thermal properties—are compared at high TRISO packing fractions (20% and 40%) across varying power densities. Results demonstrate that homogenization significantly under-predicts peak temperatures, for the case of high power/TRISO, there is a difference of 83.73 K in the maximum temperature. Additionally, homogenization underestimates the silver release predictions compared to explicit modeling. Specifically, the temperature and power density differences lead to significant differences in silver release predictions. This work demonstrates the importance of accurately modeling heterogeneity of the TRISO particles to reliably predict fission product release and assess reactor safety margins.
Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.
Sweet potatoes are a rich source of nutrients and bioactive compounds, but their quality can be impacted by the drying process. This study investigates the impact of slot jet reattachment (SJR) nozzle and ultrasound (US) combined drying (SJR + US) on sweet potato quality, compared to freeze-drying (FD), SJR drying, and hot air drying (HAD). SJR + US drying at 50 °C closely resembled FD in enhancing quality attributes and outperformed HAD and SJR in key areas such as rehydration, shrinkage ratios, and nutritional composition. Notably, SJR + US at 50 °C produced the highest total starch (36.84 g/100 g), total dietary fiber (8.48 g/100 g), total phenolic content (158.19 mg GAE/100 g), total flavonoid content (119.08 mg QE/g), DPPH antioxidant activity (6.44 μmol TE/g), β-carotene (31.98 mg/100 g), and vitamin C (5.27 mg/100 g). It also exhibited higher glass transition temperatures (Tg: 14.49 °C), indicating better stability at room temperature. The hardness values for SJR + US samples were similar to FD, while HAD samples had the highest hardness. SJR + US at 50 °C resulted in the lowest total color changes (ΔE), indicating minimal impact on appearance. Additionally, FTIR analysis revealed that peaks in specific spectral regions indicated superior preservation of bioactive compounds in SJR + US samples compared to other methods, which was also confirmed by principal component analysis (PCA) and heatmap visualization. Overall, these findings suggest that SJR + US is an effective alternative to conventional drying techniques, significantly improving the quality of dried sweet potatoes.
Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. Finally, we anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.
The interaction of radio-frequency (RF) waves with edge turbulence modifies the incident wave spectrum, and can significantly affect RF heating and current drive in tokamaks. Previous lower hybrid (LH) scattering models have either used the weak-turbulence approximation, or treated more realistic, filamentary turbulence in the ray tracing limit. In this study, a new model is introduced which retains full-wave effects of RF scattering in filamentary turbulence. First, a Mie-scattering technique models the interaction of an incident wave with a single Gaussian filament. Next, an effective differential scattering width is derived for a statistical ensemble of filaments. Lastly, a Markov chain solves for the transmitted wave spectrum in slab geometry. This model is applied to LH launching for current drive. The resulting wave spectrum is asymmetrically broadened in angular wavenumber space. This asymmetry is not accounted for in previous LH scattering models. The modified wave spectrum is coupled to a ray tracing/Fokker–Planck solver (GENRAY/CQL3D) to study its impact on current drive. The resulting current profile is greatly altered, and there is significant increase in the on-axis current and decrease in the off-axis peaks. This is attributed to a portion of the modified wave spectrum that is strongly dampened on-axis during the first pass.
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Formation of the sp 3 -defect due to covalent functionalization of a single-walled carbon nanotube (SWCNT) results in a new red-shifted emissive excitons. Here, using density functional theory, we study the impact of the intrinsic molecular dipole moments and the local charges induced by various molecular adducts on the energy and localization properties of the optically active defect-based exciton in a (10,5) SWCNT. The interplay of two effects plays a role in the localization of the exciton and, therefore, its red shift, but at different scales: The source of the leading order contribution is the defect conformation, resulting in the red shift of the defect-associated exciton with respect to the E 11 band of the pristine SWCNT on the order of ~100 meV, while the individual dipoles and polarization properties of molecular adducts lead to significantly smaller red shifts on the order of ~10 meV. While the species-dependent trends in defect-induced charges do not directly correlate to the exciton red shift, the charge at the sp 3 -defect exhibits a distinct behavior between ortho- and para-defect configurations and is relevant to the chemical reactivity of the defect position depending on the adduct type. Overall, our computational results may be helpful for diverse synthetic strategies to fine-tune emission of SWCNTs toward desired applications.
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.
Brucite [Mg(OH) 2 ] is a promising sorbent for carbon dioxide removal (CDR) due to its availability and low calcination temperatures. However, natural and synthetic brucites tend to contain metal impurities, such as iron or manganese, and how these impurities affect the interfacial chemical reactivity is uncertain. Here, in this study, the impact of low concentrations of iron and manganese impurities on the carbonation efficiency of Mg(OH) 2 was examined. Mg(OH) 2 with small amounts (1–5 mol %) of Fe and Mn was synthesized. The increasing substitution of Fe into Mg(OH) 2 was accompanied by the oxidation of Fe. The phase transformation sequence during the carbonation was found to be brucite [Mg(OH) 2 ] → amorphous magnesium carbonate (MgCO 3 ·nH 2 O) → nesquehonite (MgCO 3 ·3H 2 O), regardless of impurity concentration. Both the Fe- and Mn-doped Mg(OH) 2 samples were more reactive than endmember Mg(OH) 2 , possibly due to their higher surface areas and lower stabilities. During carbonation, 3 mol % Fe- and Mn-doped Mg(OH) 2 showed the highest reactivity. The variance in reactivity for Mn-doped Mg(OH) 2 was less than that of Fe-doped Mg(OH) 2 . These results suggest that natural or industrial waste Mg(OH) 2 with less than 5 mol % Fe and Mn impurities may be targeted as more effective CDR sorbents than endmember Mg(OH) 2 .
Low catalyst loadings pose challenges to performance stability in proton exchange membrane (PEM) water electrolysis over extended operation. To study the impact of degradation mechanisms and voltage loss rates, different stress tests are applied to membrane electrode assemblies. Potential cycling conditions were observed to induce higher degrees of iridium (Ir) oxide crystallization, ionomer degradation, and catalyst layer (CL) thinning, which likely contributed to higher kinetic loss rates. On the other hand, while Ir migrating into the PEM (Ir band) generally impairs performance, the interconnected and more uniform Ir band formed under a constant 2 V hold may allow for Ir at the catalyst/membrane interface to remain electronically connected and kinetically accessible, as well as indicate greater Ir site access during the applied stressor. The 2 V hold also demonstrates improved kinetic durability through a lower Tafel slope, faster polarization kinetics, and reduced charge transfer resistance. In contrast, potential cycling caused the migration of disconnected Ir agglomerates into the membrane bulk and created a steady increase in charge transfer resistance, a more dramatic decrease in capacitance (46.7% loss), and significant damage to the surrounding ionomer, indicating a decline in both the quality and quantity of active sites in the anode CL. This work underscores the distinct degradation pathways associated with load holds versus cycling, highlighting the role of catalyst-ionomer interactions in kinetic performance and long-term stability. These insights can inform operational strategies for PEM electrolyzers powered by intermittent energy sources, aiming to minimize efficiency losses over extended operation.
Improving building energy performance requires the development of new highly insulative materials. An affordable retrofitting solution comprising a thin film could improve the resistance to heat flow in both residential and commercial buildings and reduce overall energy consumption. Here, we propose cellulose aerogel films formed from pellicles produced by the bacteria Gluconacetobacter hansenii as insulation materials. We studied the impact of the density and nanostructure on the aerogels’ thermal properties. A thermal conductivity as low as 13 mW/(K·m) was measured for native pellicle-based aerogels that were dried as-is with minimal post-treatment. The use of waste from the beer brewing industry as a solution to grow the pellicle maintained the cellulose yield obtained with standard Hestrin-Schramm media, making our product more affordable and sustainable. In the future, our work can be extended through further diversification of food wastes as the substrate sources, facilitating higher potential production and larger applications.