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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Progress Towards a New Model Chemolithoautotrophic Host (CRADA Final Report)

Some of the largest scale chemical processes for the production of important commodity chemicals and fuels involve an H 2 -containing gas mixture as an intermediate [e.g. ammonia, urea, methanol, Fischer-Tropsch (F-T) diesel, and hydrotreatment of crude petroleum to refined fuels]. The successful development of a model H 2 -oxidizing chemoautotrophic host could expand the range of fuels and chemicals produced from H 2 and CO 2 intermediates in the chemical, oil, and gas sectors in the near term, as well as from renewable and waste-derived sources of these gases that are expected to greatly expand in coming years. Among non-photosynthetic bacteria that can utilize H 2 and CO 2 , Cupriavidus necator (C. necator, formerly Ralstonia eutropha), is the best studied. C. necator is an excellent microbial host for the production of a variety of chemicals because it grows extremely quickly to very high cell densities autotrophically on H 2 and CO 2 , is genetically tractable, and has the ability to accumulate polymers, such as polyhydroxybutyrate, at industrial levels. Despite having great potential as a platform bioproduction host, genetic tools are limited, making metabolic engineering of this organism slow and laborious. In this CRADA project, we developed a number of genetic tools for C. necator: 1) Improvement of C. necator genetic transformation efficiency 2) Integration of heterologous genes into the C. necator chromosome and development of promoter library 3) Development of graded RBSs to control heterologous protein expression 4) Use of RBSs to demonstrate fatty alcohol production in C. necator 5) Demonstration of CRISPR-Cas9 gene editing in C. necator

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

Assessing the Role of the Support in Acetic Acid Hydrodeoxygenation Selectivity on Pt/TiO2

To produce drop-in quality biofuels following the thermochemical conversion of biomass via catalytic fast pyrolysis (CFP), hydrodeoxygenation (HDO) reactions can be performed to remove excess oxygen and create a more stable bio-oil product. HDO reactions involve co-feeding the CFP vapor-phase product and H2 gas over bi-functional catalysts, such as noble-metal catalysts supported on reducible metal oxides (e.g., Pt/TiO2). Recent model-compound studies, focusing on important classes of species in the CFP vapor mixture, have sought to determine the role of the various Pt/TiO2 actives sites (i.e., Pt-metal, TiO2-support, Pt-TiO2-interfacial sites) in producing the observed desired deoxygenation and undesired decarboxylation/decarbonylation products. One important class of compounds in the CFP vapor-phase product is carboxylic acids (e.g., acetic acid). Prior experimental work on acetic acid HDO (AA-HDO) found that Pt/C and Pt/TiO2 catalysts favored the formation of undesired C-C and desired C-O bond-dissociation products; however, the fundamental surface chemistry driving this shift in selectivity has not been established. This presentation employs atomic-scale modeling to determine, through comparisons of adsorption and reaction energetics, how Pt-metal, Pt-TiO2-interface, and interfacial-vacancy sites catalyze the competing reaction pathways for AA-HDO. Our analysis indicates that hydroxyl vacancies at the Pt-TiO2 interface are critical for lowering barriers for C-O bond-cleavage steps, such that they become favorable/competitive with respect to C-C bond-dissociation steps.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2021

Multiphysics and Multiscale Modeling of Coupled Transport of Chloride Ions in Concrete

Chloride ions (Cl−)-induced corrosion is one of the main degradation mechanisms in reinforced concrete (RC) structures. In most situations, the degradation initiates with the transport of Cl− from the surface of the concrete towards the reinforcing steel. The accumulation of Cl− at the steel-concrete interface could initiate reinforcement corrosion once a threshold Cl− concentration is achieved. An accurate numerical model of the Cl− transport in concrete is required to predict the corrosion initiation in RC structures. However, existing numerical models lack a representation of the heterogenous concrete microstructure resulting from the varying environmental conditions and the indirect effect of time dependent temperature and relative humidity (RH) on the water adsorption and Cl− binding isotherms. In this study, a numerical model is developed to study the coupled transport of Cl− with heat, RH and oxygen (O2) into the concrete. The modeling of the concrete microstructure is performed using the Virtual Cement and Concrete Testing Laboratory (VCCTL) code developed by the U.S. National Institute of Standards and Technology (NIST). The concept of equivalent maturation time is utilized to eliminate the limitation of simulating concrete microstructure using VCCTL in specific environmental conditions such as adiabatic. Thus, a time-dependent concrete microstructure, which depends on the hydration reactions coupled with the temperature and RH of the environment, is achieved to study the Cl− transport. Additionally, Cl− binding isotherms, which are a function of the pH of the concrete pore solution, Cl− concentration, and weight fraction of mono-sulfate aluminate (AFm) and calcium-silicate-hydrate (C-S-H), obtained from an experimental study by the same authors are utilized to account for the Cl− binding of cement hydration products. The temperature dependent RH diffusion was considered to account for the transport of Cl− with moisture transport. The temperature and RH diffusion in the concrete domain, composite theory, and Cl− binding and water adsorption isotherms are used in combination, to estimate the ensuing Cl− diffusion field within the concrete. The coupled transport process of heat, RH, Cl−, and O2 is implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE) developed by the U.S. Idaho National Laboratory (INL). The model was verified and validated using data from multiple experimental studies with different concrete mixture proportions, curing durations, and environmental conditions. Additionally, a sensitivity analysis was performed to identify that the water-to-cement (w/c) ratio, the exposure duration, the boundary conditions: temperature, RH, surface Cl− concentration, Cl− diffusion coefficient in the capillary water, and the critical RH are the important parameters that govern the Cl− transport in RC structures. In a case study, the capabilities of the developed numerical model are demonstrated by studying the complex 2D diffusion of Cl− in a RC beam located in two different climatic regions: warm and humid weather in Galveston, Texas, and cold and dry weather in North Minnesota, Minnesota, subjected to time varying temperature, RH, and surface Cl− concentrations.

composite theory↗
DOE OSTI2023

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗
DOE OSTI2026

Separation of Hydrogen Using Pd/Ag Membranes: Experimental and Modeling Results with Potential Application to Direct Internal Recycle

Implementation of fusion energy requires processing the deuterium-tritium (D-T) mixture used to fuel the reaction, and separation of hydrogen isotopes from other gases is imperative. Specifically, the separation of hydrogen isotopes from helium is a matter of importance to the fusion fuel cycle community. Initial testing with a palladium-silver (Pd-Ag) membrane indicates that even moderate vacuum (~100 torr permeate pressure) can provide a high degree of separation (>90%) at a high ratio of H 2 to He. Given the presence of He in many fusion systems, a high technology readiness level (TRL) for Q 2 /He (where Q represents any isotope of hydrogen) separations is needed. This study demonstrates the efficacy of H 2 removal from He via permeation and potential applications for direct internal recycle. Modeling will accompany the experimental campaign to generate a predictive capability and quantify the separation performance. Modeling from previous hydrogen permeation studies has demonstrated that the typical Sieverts’ law fails to predict the measured permeation rates at high hydrogen fluxes. Existing models are being refined to integrate the effects of surface phenomena into permeation predictions, which have been expanded to account for mixtures with large ranges of Q 2 concentrations. These data will improve the TRL of permeators as a separation technology for the fusion fuel cycle.

08 HYDROGEN↗
DOE OSTI2021

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational Analysis of Different Sparging Systems and their Influence in the Fluid-Dynamic Behavior of Bubble Column Reactors

Bubble column bioreactors are being actively considered for gas fermentation applications, specifically for CO2 utilization, and sugars to fuels conversion. Their main advantages include good mass transfer without any moving parts and low-cost of operation and maintenance. However, the design and scale-up of such reactors is challenging specifically for carbon capture applications where a mixture of gases (e.g. CO2/CO/H2) with variable solubilities is used. The overall performance of scaled-up bioreactors (e.g., mass transfer rate) is largely affected by gas holdup, bubble size distribution (BSD), and multiphase hydrodynamics. We investigate the effect of gas sparger designs on the performance of these large-scale bioreactors using computational fluid dynamics simulations in this work, so as to improve CO2 conversion at scale. The gas distribution systems in bubble column reactors not only determines operational regime, but also affects the evolution of the BSD, which in turn influences interfacial mass transfer and ultimately the efficiency of the gas-liquid exchange process. In addition to the BSD, uniformity in gas sparging affects gas holdup and bubble residence time which constitute important metrics of performance in gas-liquid systems. In this work, we use computational models to simulate high fidelity representations of different sparger designs and their effect on the operation of a bubble column reactor. Four different types of spargers have been selected for the computational study (Fig. 1): ladder, multi-ring, single-ring and toroidal. Their effect on superficial velocity, gas holdup mixing efficiency, and BSD will be evaluated in this work. The model uses a multiphase Eulerian framework similar to [1] and include a composition of mixtures of H2/CO/CO2 gases, common in fermentation applications.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Determining Activity Coefficients of SOA from Isothermal Evaporation in a Laboratory Chamber

Nonideal molecular interactions in aerosol particles influence the partitioning of semivolatile organic compounds (SVOCs). However, few direct measurements exist that determine activity coefficients (γ), which quantify nonideality, for individual organic compounds in different atmospheric mixtures. By measuring the isothermal evaporation of SOA formed from multifunctional SVOCs in an environmental chamber, this study determines the mole-fraction-based γ of the bulk SOA in a variety of pre-existing chemically complex particles, approximated as if the bulk SOA behaved like a single SVOC. These multicomponent mixtures contain molecular structures commonly found in the atmosphere. When treated as a single liquid phase, γ of the bulk SOA tends to increase from ~1 to ~5 as the organic seeds and the SOA have more differing polarities. A high computed γ value of 74 for a wet ammonium sulfate-SOA system indicates phase separation. The γ for some individual species was also quantified based on gas-phase measurements and AIOMFAC model predictions. However, the bulk SOA γ cannot be explained by the simplified speciated SVOC–seed interactions, suggesting incomplete compositional understanding of the bulk SOA. In this work, these results demonstrate a method to quantify nonideal behavior and show that it can occur in multicomponent mixtures and therefore influence OA formation, evolution, and lifetimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Data Science Tools to Reveal and Understand Subtle Relationships of Inhibitor Structure in Frontal Ring-Opening Metathesis Polymerization

The rate of frontal ring-opening metathesis polymerization (FROMP) using the Grubbs generation II catalyst is impacted by both the concentration and choice of monomers and inhibitors, usually organophosphorus derivatives. Herein we report a data-science-driven workflow to evaluate how these factors impact both the rate of FROMP and how long the formulation of the mixture is stable (pot life). Using this workflow, we built a classification model using a single-node decision tree to determine how a simple phosphine structural descriptor (V bur-near ) can bin long versus short pot life. Additionally, we applied a nonlinear kernel ridge regression model to predict how the inhibitor and selection/concentration of comonomers impact the FROMP rate. Furthermore, the analysis provides selection criteria for material network structures that span from highly cross-linked thermosets to non-cross-linked thermoplastics as well as degradable and nondegradable materials.

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

On the non-existence of stepped-pressure equilibria far from symmetry

The Stepped Pressure Equilibrium Code (SPEC) (Hudson et al 2012 Phys. Plasmas 19 112502) has been successful in the construction of equilibria in 3D configurations that contain a mixture of flux surfaces, islands and chaotic magnetic field lines. In this model, the plasma is sliced into sub-volumes separated by ideal interfaces, and in each volume the magnetic field is a Beltrami field. In the cases where the system is far from possessing a continuous symmetry, such as in stellarators, the existence of solutions to a stepped-pressure equilibrium with given constraints, such as a multi-region relaxed MHD minimum energy state, is not guaranteed but is often taken for granted. Using SPEC, we have studied two different scenarios in which a solution fails to exist in a slab with analytic boundary perturbations. Here we found that with a large boundary perturbation, a certain interface becomes fractal, corresponding to the break up of a Kolmogorov–Arnold–Moser (KAM) surface. Moreover, an interface can only support a maximum pressure jump while a solution of the magnetic field consistent with the force balance condition can be found. An interface closer to break-up can support a smaller pressure jump. We discovered that the pressure jump can push the interface closer to being non-smooth through force balance, thus significantly decreasing the maximum pressure it can support. Our work shows that a convergence study must be performed on a SPEC equilibrium with interfaces close to break-up. These results may also provide insights into the choice of interfaces and have applications in finding out the maximum pressure a machine can support.

3D equilibrium↗
DOE OSTI2026

Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 < z < 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1 Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurements of Density and Sound Speed in Mixtures Relevant to Supercritical CO2 Cycles

Abstract The objective of this research is to validate properties of mixtures relevant to supercritical carbon dioxide (sCO2) power cycles. Direct-fired sCO2 cycles are a promising technology for the future power generation systems. The working fluid of sCO2 cycles will be near and above critical point of CO2. One of the challenges is that the simulation of mixtures should consider real gas behavior. Expected operating conditions of Allam cycles reach up to 300 bar and 1000 °C. Characterizing the mixtures at the extreme conditions is an important issue in current researches and industrial applications. Thermophysical properties of mixtures may be beyond the valid range of the widely used database such as NIST REFPROP. Experimental data of mixture properties in the literature are limited which is necessary to develop high-fidelity design tools for sCO2 power cycles. We measured the density and sound speed of several multi-component mixtures. A temperature-controlled high-pressure test cell was used for the density measurements. Sound speed was measured by resonant frequency detection using an external speaker and a piezoelectric pressure sensor. Mixtures studied in this work include carbon dioxide, methane, oxygen, and water vapor. Properties of pure CO2 were measured to show the validity of our technique. Compositions were selected to be close to frozen mixtures at the inlet, mid-progress, and exhaust conditions of a model sCO2 combustor in the previous numerical simulation work. Corresponding reaction progress variables (RPV) were RPV = 0, 0.5, and 1. Temperature and pressure conditions of experiments are 310–450 K and 0–150 bar. In our study, density and sound speed from the NIST REFPROP database agree with experimental measurements within the range of our measurement uncertainties.

Energy & Fuels↗
DOE OSTI2020

Editors’ Choice—Review—Recent Advances in Mixed Potential Sensors

Gas sensors are widely used in environmental monitoring and provide controls especially when working with toxic gases. YSZ based λ-sensors have been utilized in the automobile industry for exhaust gas monitoring for more than 40 years. However, recent regulations on emissions reduction has forced further development of toxic gases monitoring in various applications. Mixed potential sensors with YSZ electrolyte are receiving increased attention due to their higher sensitivity and durability under harsh conditions. This review focuses on recent (past 5 years) developments made on electrode and electrolyte structure along with new sensing electrode materials towards detecting gases such as NO x , NH 3 , H 2 , CO and hydrocarbons (HCs). The theory of mixed potential sensors is discussed along with recent developments in detection of multi-gas mixtures using the output from an array of sensors in a mathematical model. Future directions for mixed potential sensor research, and methodologies to improving sensing characteristics are also outlined

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The Study on the Shock Wave Propagation Rule of a Gas Explosion in a Gas Compartment

Combined with the k-ε turbulence model of general application, a refined finite element model of a utility tunnel’s gas compartment filled with the methane/air mixture is developed. A series of analyses are made by using the powerful industry-leading computational fluid dynamics (CFD) software flame acceleration simulator (FLACS) to study the shock wave propagation rule in the gas compartment. The longitudinal and transversal distribution laws of the explosion shock wave are gained taking into consideration the spatial characteristics of the gas compartment. The influences of a few parameters, such as initial conditions and section size of the gas compartment, on the shock wave propagation rule are further discussed. The basic procedure for predicting the peak pressure of the blast wave is provided by considering the initial conditions and the gas compartment, and the corresponding injury effect of the explosion wave on the living beings is assessed. The investigation demonstrates that the peak pressure by the coupled effect between the initial conditions is significantly influenced, especially at the upper and lower gas explosion limits. The peak pressure increases gradually as the width or height increases, and both basically meet the linear relation. The proposed method can forecast the peak pressure of the explosion shock wave in the gas compartment accurately. According to the peak pressure longitudinal and transversal distributions of the blast wave, the peak pressure is far greater than the killing pressure threshold in the underground and closed space; consequently, it is not safe for the living beings in the gas compartment.

Lin, Shu-Chao↗
DOE OSTI2025

Polar Bear™ – Innovative Capture of Storage Tank Vapors

Polar Bear™ is a patented technology developed by the Energy & Environmental Research Center (EERC) to capture storage tank vapors and eliminate methane emissions from upstream oil- and gas-producing facilities. Sparked by early commercial investment, the EERC licensed the technology and extended the intellectual property to storage tanks. Polar Bear™ is uniquely engineered and adapted to individual lower-producing facilities where there is otherwise no economic alternative for capturing tank vapors. A high number of small producing oil and gas wells are distributed across the country. The aggregate contributes to a significant volume of emissions. Because of the lack of economy of scale, gas volumes from these facilities are typically not recovered and contribute to methane emissions. Polar Bear™ provides a fit-for-purpose compression solution that addresses cost by reducing complexity with respect to conventional vapor recovery units and eliminating oil changes. Unique to Polar Bear™ is the capability to separate oxygenated gas from storage tank vapors. Storage tanks are designed to “breathe,” allowing gas to enter and escape during internal level and temperature changes. This infiltration of air into the tank headspace imparts undesirable oxygen content with respect to pipeline gathering. Polar Bear™ separates the vapor stream, allowing oxygen-rich gas to be used as fuel on-site while recovering the liquids-rich portion of the gas where oxygen content is minimized. A prototype system was tested to verify process models, evaluate operational performance, and advance the technology readiness level from 5 to 6. Results provide a good match between experimental measurements and process models, indicating the models are useful for future scale-up and field design. Various mixtures of nitrogen and liquefied petroleum gas were tested to understand the mass balance of nitrogen and how it relates to the potential control of oxygen content. Findings indicate that less than 2000 ppm of oxygen is likely to remain in the liquid portion of the gas in field applications. The research and development prepare the technology for field implementation to eliminate routine and fugitive methane emissions from storage tanks.

02 PETROLEUM↗
DOE OSTI2024

DME-Propane Autoignition Measurements inside a Shock Tube

Dimethyl ether (DME) is a biofuel that has the potential to replace diesel in heavy-duty engines. A blend of propane (C3H8) and DME could reduce emissions when compared to diesel at heavy-duty compression engine-relevant conditions. Testing a potential new mixture in a compression engine requires a high-fidelity chemical kinetics model that accurately predicts autoignition delay times, which is especially necessary for a compression engine. In this work, autoignition data has been gathered at an equivalence ratio of 2.0 for pressures of 60 and 80 bar. DME and propane were combusted in synthetic air while excited hydroxyl (OH*) chemiluminescence was used to gather ignition delay times. Data was compared to recent chemical kinetic mechanisms for the two different pressures. Using the mechanism with the best fit of autoignition data, a sensitivity analysis was conducted to analyze the chemical kinetics of the DME/C3H8 combustion at elevated pressures.

Mohammed, Zuhayr Pasha↗
DOE OSTI2026

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.

25 ENERGY STORAGE↗