Search NASA⌕ Search

SEARCH · Search NASA

Results for “conditioning”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Poisson equation method for prescribing fully developed non-Newtonian inlet conditions for computational fluid dynamics simulations in models of arbitrary cross-section

Prescribing inlet boundary conditions for computational fluid dynamics (CFD) simulations of internal flow in complex geometries such as anatomical vascular models is challenging. In the absence of patient-specific inlet velocity data, a common approach for long blood vessels is to assume that the inlet flow is fully developed. In vessels of irregular cross section, however, prescribing fully developed conditions is complicated due to the lack of a general closed-form analytical solution. In this study, we develop a simple Poisson equation method for prescribing fully developed inlet conditions for the flow of either Newtonian or non-Newtonian fluids in CFD models of arbitrary cross-section. We first derive the generalized Poisson equation for fully developed flow of a non-Newtonian fluid and we then develop and verify a methodology for numerically computing the solution on any planar boundary domain. In addition, we develop a simple extension of the method for prescribing a non-orthogonal inlet velocity that represents fully developed flow from an upstream tube that is connected to the CFD inlet at a non-orthogonal angle. This may be used to investigate a common source of uncertainty in CFD simulations of internal flow that is due to a lack of information concerning the exact streamwise flow direction at the inlets. Comparison to several Newtonian and non-Newtonian benchmark verification solutions shows the method to be extremely accurate. As a practical demonstration case, we use the method to prescribe fully developed conditions on multiple non-circular inlets for the non-Newtonian flow of blood in a patient-specific model of the inferior vena cava (IVC). Finally, we further demonstrate the utility of the method by performing a sensitivity study using the patient-specific IVC model, wherein we investigate the influence of inlet velocity flow direction on the non-Newtonian IVC hemodynamics. Given its simplicity and computational efficiency, the method is shown to be far superior to alternative approaches for prescribing fully developed inlet conditions in such complicated geometries. In conclusion, to facilitate the adoption of our Poisson equation method, we have distributed our OpenFOAM source code and the associated test cases from this study as open-source software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Precision Structure Engineering of High-Entropy Oxides under Ambient Conditions

High-entropy oxides (HEOs) have unveiled a unique frontier in the realm of heterogeneous catalysis, taking advantage of the entropic effect and increased complexities to deliver ultrahigh stability and large tuning capability. However, current HEO synthesis mainly relies on high-temperature annealing approaches affording HEOs possessing no or low surface area, inferior active site exposure efficiency, and low controllability over the structure tuning. The grand challenge lies in producing high-quality HEO catalysts with high active site utilization efficiency, which relies on precision structure engineering, preferably under mild conditions. In this work, an in situ lattice engineering approach was developed to afford a supported HEO catalyst under ambient conditions. The HEO compositions (CuCoFeNiMnO x ) were uniformly integrated into the lattice of CeO 2 driven by cavitation-induced nucleation being generated via ultrasonication. The as-afforded catalysts were featured by high surface area, atomically dispersed HEO compositions, active redox properties, abundant oxygen vacancies (O V ), antiagglomeration, and high phase stability under harsh conditions. Compared with the ex situ introduction of HEO on the surface, the in situ method provides dual benefits to maintain the dispersity of HEO via entropic and lattice confinement effects. Engineering the complex HEO within the lattice of fluorite-structured CeO 2 also yields abundant defects (e.g., O V ) and active metal sites with strong reducing properties (e.g., Ce 3+ and Cu + ), which greatly improves the activity of the lattice oxygen and tunability of the adsorption behavior of the guest molecules, especially in the presence of impurities (e.g., water and propane). The catalytic performance of the supported HEO catalyst in oxidative procedures surpasses the pure dense phase HEO as well as the ex situ-generated catalysts. Further, the synthesis approach being developed in this work, together with the fundamental understanding in structure evolution and reaction mechanism, showcases a facile pathway under ambient conditions to generate stable catalysts capable of maintaining structural robustness in high-temperature conditions while delivering enhanced catalytic performance.

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

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗
DOE OSTI2022

Real-time wall conditioning and recycling modification utilizing boron and boron nitride powder injections into the Large Helical Device

Controlled particulate injections from the PPPL impurity powder dropper (IPD) into the Large Helical Device have demonstrated positive effects on the wall conditions on both an intra and inter-shot basis. Here injections over a range of densities, input powers, pulse lengths, heating schemes, injection quantities and main ion species show conclusive evidence of improvement to plasma wall conditions. Successful injections are confirmed by both spectroscopic measurements as well as real-time visible camera signals. In 7 s long plasmas the responses include a reduction in wall recycling as well as a reduction in native impurity content as observed over the course of several discharges. For plasmas longer than 40 s, improvements to the recycling rate and increased impurity control are observed in real time as a consequence of the extended particulate injections. These experiments demonstrate the extended applicability of this solid particulate conditioning technique to the control and maintenance of the plasma wall conditions. In addition they are an important initial step in the development of the real-time boronization technique as a supplement to standard conditioning scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Stability Analysis of Interface Conditions for Ocean-Atmosphere Coupling

In this paper, we analyze the stability of different coupling strategies for multidomain PDEs that arise in general circulation models used in climate simulations. We focus on fully coupled ocean–atmosphere models that are needed to represent and understand the complicated interactions of these two systems, becoming increasingly important in climate change assessment in recent years. Numerical stability issues typically arise because of different time-stepping strategies applied to the coupled PDE system. In particular, the contributing factors include using large time steps, lack of accurate interface flux, and single-iteration coupling. We investigate the stability of the coupled ocean–atmosphere models for various interface conditions such as the Dirichlet–Neumann condition and the bulk interface condition, which is unique to climate modeling. By analyzing a simplified model, we demonstrate here how the parameterization of the bulk condition and other numerical and physical parameters affect the coupling stability and establish stability conditions for different coupling strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Mineral-specific heterogeneous neptunium sorption onto geological repository rocks in oxic and anoxic conditions and various temperatures

Neptunium poses challenges for radioactive wastes management due to its long half-life and ingrowth from americium decay, as well as its high mobility in water in its oxidized forms. Np(V)-bearing aqueous solutions were contacted with polished and crushed gneiss and dolerite from the Yeniseisky site, Russia, which is under consideration as a location for an underground repository, both in oxic and anoxic conditions at 20 and 90 °C. Neptunium sorption on crushed gneiss and dolerite in oxic conditions at 20 °C was quite low, but increased substantially in anoxic conditions. Autoradiography on samples treated at 20 °C revealed that sorbed Np was associated mostly with dark colored iron-bearing minerals, and solvent extraction indicated partial reduction of Np(V) to Np(IV). Sorption of Np from aqueous solutions contacted with dolerite and gneiss at 90 °C was in all cases higher than at the lower temperature. Autoradiography of polished rock samples treated in anoxic conditions at 90 °C revealed that Fe-bearing minerals had 3–4 orders of magnitude more Np sorbed on them than the quartz and feldspar grains. X-ray photoelectron spectroscopy indicated this sorbed Np was present as NpO 2 . This study supports the concept that the geologic conditions present at the planned repository site will retard Np migration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Spray and combustion characteristics of butanol-diesel and hexanol-diesel blends under high-altitude conditions

Due to their excellent fuel properties, butanol and hexanol are considered as two promising renewable fuels for diesel engine applications. The objective of this work is to investigate and compare the spray and combustion characteristics of butanol-diesel and hexanol-diesel blends under high-altitude conditions. A constant volume combustion chamber was used to provide the desired environment. Experiments were conducted under various ambient temperatures ranging from 800 K to 1200 K and various ambient densities ranging from 11 kg/m3 to 15 kg/m3. Fuel blends with 20% blend ratio (B20 and H20) and neat diesel were used as test fuels. The spray and combustion characteristics of the test fuels were analyzed using measured liquid penetration length, ignition delay, combustion duration, flame lift-off length (FLoL), and spatially integrated natural luminosity (SINL). Here the results revealed that B20 and H20 had shorter liquid penetration length than diesel under low ambient temperature and density conditions due to their higher volatility. The blended fuels showed significantly longer ignition delay than diesel under low ambient temperature conditions, but it could be overcome by increasing the ambient temperature. Adding butanol and hexanol into diesel both extended FLoL especially under low ambient temperature and density conditions, but the effects of hexanol was less dramatic compared to butanol due to its lower latent heat of vaporization and higher chemical reactivity. Both B20 and H20 showed lower SINL than diesel under any conditions, indicating their ability of reducing soot emissions. However, no apparent differences could be found between these two fuels until the ambient temperature dropped to 800 K.

42 ENGINEERING↗
DOE OSTI2023

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

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

Effect of initial water saturation on the performance of fracturing fluids with and without polyallylamine under simulated EGS conditions

Objectives/Scope: StimuFrac (US Patents 9,873,828 B2 and 9,447,315 B2), a CO 2 - reactive polymer aqueous solution [polyallylamine (PAA) 1wt% in water] combined with CO 2 , can be used as a potentially less water-intensive fracturing fluid for enhanced geothermal systems (EGS). Our previous results show that in hot dry rock (HDR), PAA/CO 2 fracturing fluids outperformed other fluids such as water, CO 2 , and CO 2 /water in generating large fractures with less fluid consumed. The objective of this work is to investigate the effect of initial water saturation on the performance of StimuFrac by conducting hydraulic fracturing tests with ½ foot cubic rock samples held under representative EGS stress/temperature conditions and by using cyclic injection strategies (under constant injection rate). The resulting fracture hydraulic conductivities, breakdown pressures, and volumes of fluids required are compared. Methods/Procedures/Process: To simulate geothermal reservoir conditions, in all tests, the rock sample was held under triaxial confinement and at 200 °C, and different volumes of water were initially injected into the rock sample before any fracturing processes were initiated. For the single-cycle PAA (or water) alternating CO 2 (PAG or WAG) injection fracturing experiments, one complete cycle consisted of two steps: (1) injecting a PAA slug (or water slug) followed by (2) injecting CO 2 to initiate and propagate the fracture. For experiments involving multiple injection cycles, the CO 2 injection pressure is increased until it peaks and begins to decline (indicating fracture initiation at this moment), and then continued being injected for another 30 seconds to propagate the fracture. Then, these two-step cycles [injection of PAA (or water) followed by CO 2 injection (up to 2-4 mL/min)] are repeated. Applications/Significance/Novelty: The results of this study suggest that water saturation significantly affects the fracturing fluid transmission into the rock pore space, thus affecting the fracture initiation and propagation. In this study, fracturing tests via a single injection cycle or multiple injection cycles were performed. Splitting the rock samples in half after testing reveals that fracture propagation is significantly limited under high water saturation conditions (three-day initial water injection) compared to stimulation experiments performed in hot dry rock. The fractures propagate less than 1/3 of the distance from the wellbore to the outer rock surface, and in some cases, no fracture is generated. This may be caused by leak-off dominating the fracturing process and the fluid injection rate is insufficient to overcome leak-off, even under high injection rate conditions. Additionally, CO 2 could be leaking off into the wellbore annulus and this may be making it more difficult to generate sufficiently high-pressure gradients away from the near-wellbore region. Under low water saturation conditions (dry rock or after 1-day initial water injection), PAA/CO 2 consistently generated significantly larger fractures compared with the other fluids. CO 2 generated large fractures only in the hot dry rock and only when using high injection rates, though data variability is high.

58 GEOSCIENCES↗
DOE OSTI2024

Impact of cement composition, brine concentration, diffusion rate, reaction rate and boundary condition on self-sealing predictions for cement-CO 2 systems

Geological CO 2 storage (GCS) plays an important role in curbing CO 2 emissions by reducing the carbon footprint of difficult to decarbonize operations and achieve negative CO 2 emissions through activities like Bioenergy with Carbon Capture and Storage (BECCS) and Direct Air Carbon Capture and Storage (DACCS). Leakage of CO 2 through wells is an important concern when it comes to deployment of large-scale GCS. Existing wells in sites that are otherwise suitable for GCS can act as conduits for stored CO 2 to escape the reservoir. There is broad consensus that the main risk of leakage through wellbores is via fractures/damaged pathways. The results from several studies evaluating the permeability evolution of cement fractures in wells upon leakage of CO 2 agree that smaller fracture apertures, slower brine velocities and higher brine residence times promote self-sealing of fractures by mineral precipitation. Quantitatively, however, the differences in sealing conditions are significant and are typically attributed to differences in experimental conditions or model assumptions. Here we examine the sensitivity of our model, describing CO 2 leakage through wellbores, to cement composition, brine concentration, diffusion rates, and reaction rates. We also evaluate the impact of the boundary condition to allow comparisons between observations from experiments performed at constant flow rate and model predictions made at constant pressure conditions. Our results show that diffusion and reactions rates have the most impact on the self-sealing criteria for cement-CO 2 systems. In addition, conditions associated with self-sealing of fractures at constant flow rate require longer fractures, smaller fracture apertures, and slower velocities than under constant pressure.

58 GEOSCIENCES↗
DOE OSTI2021

Hydroxide melt induced corrosion of Ni at elevated temperatures under steam electrolysis conditions

Molten alkali electrolyte based high temperature water electrolysis (HTWE) process offers an efficient pathway to integrate renewable energy resources for large scale and economic hydrogen production. Long term and stable operation of these systems require an in-depth understanding of materials stability under anodic and cathodic exposure conditions of the cell and cell stacks. In the present study, we report our findings on the corrosion of Ni in the presence and absence of (LieNa) hydroxide melt at 600 °C under oxidizing and reducing conditions representative of HTWE. While the Ni electrode was found to remain thermodynamically stable in metallic form under cathodic (reducing) exposure conditions, the corrosion rate in molten hydroxide under oxidizing conditions was found to be nonparabolic in nature. A cyclic voltammetry study provides the breakdown of the passive metal-oxide surface layer at the anodic overpotential region between 0.45 V and 2 V in molten hydroxide under oxidizing conditions. As a result, a thermochemical process for accelerated corrosion based on the oxide scale fluxing in hydroxide melt has been developed.

08 HYDROGEN↗
DOE OSTI2022

Methane foam performance evaluation in water-wet unconsolidated porous media: A systematic experimental investigation at elevated pressure and temperature conditions

In the petroleum industry, enhanced oil recovery (EOR) techniques employ foam extensively to establish conformance control in heterogeneous and fractured reservoirs in order to increase the sweep efficiency. In such applications, foam performance evaluation under complex subsurface conditions is pivotal for the effective and optimized deployment of foam treatment. However, there is a scarcity of hydrocarbon gas foam generation and evaluation studies that examine the relationships between foam performance and the critical foam parameters at high-pressure and high-temperature conditions. Here, this study aims at methodically investigating the effects of several foam parameters on methane foam performance in water-wet proppant packs under harsh operating conditions. This is in relation to the technical needs of hydrocarbon foam injection into hydraulically-induced, propped fractures in unconventional oil reservoirs. To this end, a state-of-the-art experimental foam generation apparatus was designed, fabricated, and commissioned. We performed a large number of foam flow experiments on proppant packs using methane gas and different foaming agents at 3500 psi and 115°C. Anionic and amphoteric surfactants were employed to probe the effect of their ionic nature on foam performance. Foam performance sensitivities to various foam generation parameters and operating conditions, such as surfactant concentration, gas fraction, total injection rate, operating pressure, salinity, and proppant pack length were investigated. To this end, steady-state pressure drops across the proppant packs during foam generation and foam's apparent viscosity were measured to quantify the foam performance of surfactants. The results were then analyzed to determine optimum values of the foam parameters and the interplay between these parameters are discussed here. The systematic results achieved from this work are in agreement with the trends available in the literature and provide new insights into complexities of in situ foam generation in water-wet, unconsolidated porous media at extreme reservoir conditions.

03 NATURAL GAS↗
DOE OSTI2026

NOx mediated formation of ε – UO 3 during thermal decomposition of uranyl nitrate hexahydrate under static air conditions

The thermal decomposition of uranyl nitrate hexahydrate in air at temperatures of 650 – 800 °C is expected to yield α – U 3 O 8 through intermediate UO 3 phases. Here, n this study, Raman spectroscopy complimented by powder X-ray diffraction revealed the unexpected formation of ε – UO 3 as an accompanying phase during thermal decomposition of UNH at 700 °C under static air conditions. Experiments demonstrated that ε – UO 3 does not form during the initial ramp up stage nor during the high temperature heating period; but instead forms during the cooling stage between 250 – 400 °C. Additional experiments revealed that UNH initially decomposes through an amorphous UO 3 intermediate prior to α – U 3 O 8 formation. Attempts to bypass the U 3 O 8 precursor in the formation of ε – UO 3 were unsuccessful, supporting the necessity of U 3 O 8 (α – U 3 O 8 in this study) in the formation of ε – UO 3 . The observed phase evolution is proposed to result from the NOx species generated during UNH thermal decomposition, which create localized oxidizing conditions within the furnace under static air conditions. Furthermore, a predominantly phase pure ε – UO 3 was synthesized under static air conditions through the addition of an extra plateau at 250 °C during the cooling step. These findings demonstrate the importance of gas-phase chemistry and cooling conditions in uranium oxide phase evolution and provide additional insight into ε – UO 3 formation pathways.

Epsilon uranium trioxide↗
DOE OSTI2020

Unraveling Spatio-Temporal Chemistry Evolution in Laser Ablation Plumes and Its Relation to Initial Plasma Conditions

The chemistry evolution in a laser ablation plume depends strongly on its initial physical conditions. In this article, we investigate the impact of plasma generation conditions on the interrelated phenomena of expansion dynamics, plasma chemistry, and physical conditions. Plasmas are produced from a uranium metal target in air using nanosecond, femtosecond, and femtosecond filament-assisted laser ablation. Time-resolved two-dimensional spectral imaging was performed for evaluating the spatio-temporal evolu-tion of atoms, diatoms, polyatomic molecules, and nanoparticles in situ. Emission spectral features reveal that molecular formation occurs at early times in both femtosecond and filament ablation plumes, although with different temporal decay. In contrast, mo-lecular formation is found to occur at much later times in nanosecond plasma evolution. Spectral modeling is used to infer tem-poral behavior of plasma excitation temperature, and results highlighted that nanosecond plume temperatures decay rapidly while plumes generated by filament ablation show slowest decay. In this work, we find U atoms and UO molecules co-exist in ultrafast laser produced plasmas even at early times after plasma onset owing to favorable temperatures for molecular formation. Regardless of irradiation conditions, plume emission features showed presence of higher oxides (i.e. UxOy), although with different temporal histories. Our study provides insight into the impact of plasma generation conditions on chemistry evolution in plasmas produced from traditional focused femtosecond, nanosecond, and filament-assisted laser ablation.

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

On the Thermodynamic Condition for Adsorption Azeotropes

Adsorption azeotropy is a common phenomenon in mixed-gas adsorption equilibria. Since the first literature report of binary adsorption azeotropes in 1933, numerous studies investigated the thermodynamic conditions for adsorption azeotropes but failed to reach definitive conclusions. Based on the generalized Langmuir isotherm model for multicomponent adsorption equilibria which takes into account the vacant site as part of the adsorbed phase, this study presents the thermodynamic condition for adsorption azeotropes as derived from the generalized Langmuir isotherm to be the equality of the ratios of adsorbed phase activity coefficient γi and adsorption equilibrium constant $K$$^{o}_{i}$ for the two adsorbates in the binary 1–2 adsorption system, i.e., γ 1 /$K$$^{o}_{1}$ = γ 2 /$K$$^{o}_{2}$. This adsorption azeotropic condition is analogous to the vapor–liquid equilibrium azeotropic condition, i.e., the equality of the products of liquid phase activity coefficient and saturation vapor pressure Pisat for the two components, i.e., γ 1 $P$$^{sat}_{1}$ = γ 2 $P$$^{sat}_{2}$. We validated the thermodynamic condition for adsorption azeotropes with 14 azeotrope-forming adsorption systems in this study. As a result, we investigated the effects of the pressure, temperature, and adsorbed phase nonideality on azeotrope formation.

42 ENGINEERING↗