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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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At least 55 records · Page 3

Gas Generation in Lithium Cells with High-Nickel Cathodes and Localized High-Concentration Electrolytes

High-nickel layered-oxide cathodes (LiNi x Mn y Co 1-x-y O 2 , x ≥ 0.8) exhibit high capacities, but also experience rapid capacity fade during cycling, and are susceptible to heat generation and gas release. Advanced electrolytes, such as localized high-concentration electrolytes (LHCE), substantially stabilize the cathode during cycling and have lower flammability than conventional electrolytes, but gas generation with these electrolytes is yet to be assessed. We demonstrate here that gas generation from a high-nickel cathode in an LHCE is half as much as in a conventional electrolyte at 4.4 V. The gas generation in LHCE is further reduced at 4.3 V, but the LHCE generates a similar amount of gas as the conventional electrolyte at 4.6 V. Neither electrolyte can prevent gas generation after cycling; cathodes after 200 cycles generate similar amounts of gas as pristine cathodes during high-voltage hold. Finally, it is shown that in both electrolytes, oxygen from the cathode lattice plays a critical role in gas generation.

25 ENERGY STORAGE↗

Electrochemical devices comprising compressed gas solvent electrolytes

Disclosed are novel electrolytes, and techniques for making and devices using such electrolytes, which are based on compressed gas solvents. Unlike conventional electrolytes, disclosed electrolytes are based on “compressed gas solvents” mixed with various salts, referred to as “compressed gas electrolytes.” Various embodiments of a compressed gas solvent includes a material that is in a gas phase and has a vapor pressure above an atmospheric pressure at a room temperature. The disclosed compressed gas electrolytes can have wide electrochemical potential windows, high conductivity, low temperature capability and/or high pressure solvent properties.

25 ENERGY STORAGE↗

Life cycle analysis of polylactic acids from different wet waste feedstocks

Producing a valuable chemical product through diversion of wet wastes can simultaneously resolve the problems associated with increasing wastes and greenhouse gas emissions from conventional chemical production processes. In this work, we investigated the life-cycle greenhouse gas emissions, water, and fossil-fuel consumption for waste-derived polylactic acids (PLA) from three different waste feedstocks, namely wastewater sludge, food waste, and swine manure, using the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model. The decarbonization potential of replacing fossil-based resins with the waste-derived polymer was also investigated. The results show that swine manure-to-PLA pathway was the least carbon intensive (—1.4 kgCO 2 e/kg) among the three waste-to-PLA pathways on a cradle-to-grave basis, followed by the food waste case (—1.3 kgCO 2 e/kg) and then by the wastewater sludge case (0.6 kgCO 2 e/kg). In the baseline scenario, all three waste-to-PLA pathways were less carbon intensive than both fossil-based PET and HDPE on a cradle-to-grave basis: 66% (vs. PET) and 56% (vs. HDPE), 171 and 192%, 181 and 205% reduction in GHG emissions for wastewater sludge-, food waste-, and swine manure-to-PLA pathway, respectively. For all sensitivity cases investigated, the food waste- and swine manure-to-PLA pathways were significantly less carbon intensive than their fossil-counterparts. In terms of the annual decarbonization potential of replacing fossil-based PET or HDPE, the wastewater sludge- and food waste-pathway showed higher mitigation potential than the swine manure-pathway: i) 18–28 kilotons CO 2 e-reduction per year for wastewater sludge pathway; ii) 23–26 kTCO 2 e-reduction/yr for food waste pathway; and iii) about 5 kTCO 2 e-reduction/yr for swine manure pathway depending on the type of conventional resin replaced. However, given the abundant availability of the swine manure feedstocks across the United States, the decarbonization potential of swine manure-based pathway can also increase as the plant capacity or the number of plants grow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microporous water with high gas solubilities

Liquids with permanent microporosity can absorb larger quantities of gas molecules than conventional solvents , providing new opportunities for liquid-phase gas storage, transport, and reactivity. Current approaches to designing porous liquids rely on sterically bulky solvent molecules or surface ligands and thus are not amenable to many important solvents, including water. Here, we report a generalizable thermodynamic strategy to preserve permanent microporosity and impart high gas solubilities to liquid water. Specifically, we show how the external and internal surface chemistry of microporous zeolite and metal–organic framework nanocrystals can be tailored to promote the formation of stable dispersions in water while maintaining dry networks of micropores that are accessible to gas molecules. As a result of their permanent microporosity, these aqueous fluids can concentrate gases, including oxygen (O 2 ) and carbon dioxide (CO 2 ), to much higher densities than are found in typical aqueous environments. Furthermore, when these fluids are oxygenated, record-high capacities of O 2 can be delivered to hypoxic red blood cells, highlighting one potential application of this new class of microporous liquids for physiological gas transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating Fracture Network Deformation Using Noble Gas Release

We investigate deformation mechanics of fracture networks in unsaturated fractured rocks from subsurface conventional detonation using dynamic noble gas measurements and changes in air permeability. We dynamically measured the noble gas isotopic composition and helium exhalation of downhole gas before and after a large subsurface conventional detonation. These noble gas measurements were combined with measurements of the subsurface permeability field from 64 discrete sampling intervals before and after the detonation and subsurface mapping of fractures in borehole walls before well completion. We saw no observable increase in radiogenic noble gas release from either an isotopic composition or a helium exhalation point of view. Large increases in permeability were observed in 13 of 64 discrete sampling intervals. Of the sampling intervals which saw large increases in flow, only two locations did not have preexisting fractures mapped at the site. Given the lack of noble gas release and a clear increase in permeability, we infer that most of the strain accommodation of the fractured media occurred along previously existing fractures, rather than the creation of new fractures, even for a high strain rate event. These results have significant implications for how we conceptualize the deformation of rocks with fracture networks above the percolation threshold, with application to a variety of geologic and geological engineering problems.

Gardner, W. Payton↗

Hydrogen Analysis by Gas Chromatography–Mass Spectrometry

The detection of hydrogen in complex gas mixtures is essential for many applications. Conventional approaches such as gas chromatography (GC) with thermal conductivity detection (TCD) and residual gas analyzers (RGAs) face significant limitations: TCD exhibits poor response when helium is used as a carrier gas, whereas RGAs lack chromatographic separation, preventing reliable quantification of hydrogen because of interference from other species. Traditional GC methods rely on dual-column configurations with packed or molecular-sieve porous layer open tubular (PLOT) columns to separate hydrogen from O2, N2, CO, CO2, CH4, and other hydrocarbons, increasing system complexity and limiting compatibility with mass spectrometry (MS) detection. In this work, we developed and validated a robust GC–MS method capable of directly detecting and quantifying hydrogen using electron ionization (EI) without dopants, reagent gases, or ion–molecule reaction schemes. By integrating a modified EI source and a cryogenically cooled single capillary column configuration, we achieved baseline separation of hydrogen from all major permanent gases and hydrocarbons in a refinery gas mixture using helium as the carrier gas. The method demonstrated excellent linearity, high sensitivity, and exceptional reproducibility. Adjustable sample-loop volumes and split ratios enabled optimization of peak shape and signal-to-noise performance for trace-level and percent-level hydrogen concentrations. Beyond hydrogen quantitation, the method provides simultaneous compositional profiling of other gases in a mixture in a single run, making it valuable for a wide range of tasks.

Lobodin, Vlad [ORNL]↗

An index to characterize gas‐solid and solid‐solid mixing from average volume fraction fields

Abstract A mixing index based on solid volume fraction fields is developed for gas‐solid flows. Conventional mixing indices are based on particle realizations of granular mixing and are applicable to experimental data or discrete element method simulations. However, these indices cannot be used as‐is for multifluid models, and an index for characterizing mixing in gas‐solid flows from continuous fields is needed. The performance of the new mixing index is tested in two applications. The first is a 3D simulation of the mixing of biomass and sand in a fluidized bed reactor, and the second is a 2D simulation of binary particle segregation in a fluidized bed. The simulations are performed using OpenFOAM®. The mixing index is used to quantify gas‐solid mixing using solid volume fractions and solid‐solid mixing using solid fractions. The formulation of conventional mixing indices is extended to be used with solid volume fractions fields, and methods for performance improvement are presented.

09 BIOMASS FUELS↗

A Novel Relative Permeability Model for Gas and Water Flow in Hydrate-Bearing Sediments With Laboratory and Field-Scale Application

In a producing gas hydrate reservoir the effective porosity available for fluid flow constantly changes with dissociation of gas hydrate. Therefore, accurate prediction of relative permeability using legacy models (e.g. Brooks-Corey (B-C), van Genuchten, etc.) that were developed for conventional oil and gas reservoirs would require empirical parameters to be calibrated at various S h over its range of variation, but such calibrations are precluded because of lack of experimental relative permeability data. This study proposes a new relative permeability model for gas hydrate-bearing media that is a function of maximum capillary pressure, capillary entry pressure, pore size distribution index, residual saturations, hydrate saturation, and four other constants. The three novel features of the proposed model are: (i) requires fitting its six empirical parameters only once using experimental data from any single S h , and the same set of empirical parameters predict relative permeability at all S h , (ii) includes the effect of capillarity, and (iii) includes the effect of pore-size distribution. From practical standpoint, the model can be used to simulate multiphase flow in gas hydrate-bearing sediments where the proposed relative permeability can account for the evolving hydrate saturation. The proposed model is implemented in a numerical simulator and the wall time required to perform simulations using the proposed model is shown to be similar to the time it takes to run same simulations with the B-C model. The proposed model is a step forward towards achieving the goal of physically accurate modeling of multiphase flow for gas hydrate-bearing sediments that accounts for the effect of gas hydrate saturation change on relative permeability.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Life Cycle Assessment for Evaluating the Global Warming Potential of Geothermal Energy Production Using Inactive Oil and Gas Wells for District Heating in Tuttle, Oklahoma

Repurposing abandoned oil and gas infrastructure for geothermal energy production has great potential to reduce greenhouse gas (GHG) emissions. This study quantified the life cycle global warming potential of geothermal energy production using four inactive oil and gas wells repurposed for district heating in Tuttle, Oklahoma. A cradle-to-grave prospective life cycle assessment was performed to compare GHG emissions between the geothermal district heating system and conventional natural gas-fired heating system from 2020 to 2050. For initial implementation of the geothermal system, we investigated two approaches: 1) repurposing abandoned infrastructure from a nearby oil and gas well site, and 2) production and injection well drillings including new construction of a central heat exchange station. Environmental impacts from the geothermal system were estimated for five scenarios where a natural gas peaking boiler is incorporated to supply peak heat demand. The prospective results indicated that cumulative reduction in GHG emissions from transitioning to the geothermal district heating system increase over time as a function of future renewable resource penetration and technological advancements within electricity, fuel, and steel production. Over 30 years, the global warming potential associated with the district heating demand will have been reduced by up to 24 % with the repurposed system. These results imply that repurposing existing oil and gas infrastructure for geothermal energy systems of district heating will bring future climate benefits.

abandoned oil and gas wells↗

Prediction of gas hydrate saturation using machine learning and optimal set of well-logs

We report resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) electrical resistivity), but the limitations of these two methods are often overlooked, which include (i) well-specific calibration of empirical exponents in the electrical resistivity method, (ii) assumption of known pore morphology for gas hydrates in the acoustic velocity method, and (iii) presence of unknown mineralogy and bulk modulus terms in the acoustic velocity method. NMR-density porosity-derived gas hydrate saturation based on the analysis of the transverse magnetization relaxation time (T2) is considered the most precise method, but acquisition of NMR-based logs is limited at relatively recent drilled sites; additionally, its use in conventional oil and gas reservoirs is not that common due to higher cost and operational deployment limitations associated with acquiring NMR well-logs. This study proposes a new method that predicts gas hydrate saturation (S h ) for any well using porosity, bulk density, and compressional wave (P wave) velocity well-logs with neural network (or stochastic gradient descent regression) without any well-specific calibration and/or other aforementioned shortcomings of the existing methods. The method is developed by examining the underlying dependency between S h and different combinations of well-logs, chosen from 6 routine logs, with 12 different machine learning (ML) algorithms. The accuracy of the proposed method in predicting S h is ~ 84%, which is better than the accuracy of seismic and electrical resistivity methods (≤ 75%) per the results reported by three different studies. The robustness of the method in the specific case of permafrost-associated gas hydrates is demonstrated with well-log data from two wells drilled on the Alaska North Slope.

58 GEOSCIENCES↗

Improving the laser performance of ion beam sputtered dielectric thin films through the suppression of nanoscale defects by employing a xenon sputtering gas

Laser damage-prone precursors in high index materials such as hafnia are believed to be the primary limiter in the performance of dielectric multilayer films to advance ultra-high power and energy laser applications. Removing or suppressing these precursors is the key to fabricating laser damage resistant thin films for the enabling technologies. Early work has revealed that nanobubbles formed by entrapped argon (Ar) working gas in ion beam sputtering (IBS) produced hafnia films are primarily responsible for the onset of laser damage upon exposure to UV, ns-laser pulses. In this study, we demonstrate that the UV ns-laser damage onset of IBS produced hafnia films can be improved to 3.1 +/- 0.2 J/cm 2 by substituting the conventional Ar working gas with xenon (Xe), a nearly 1 J/cm 2 increase from that of the Ar produced hafnia films. In addition to the suppression of the overall point-defect density of the hafnia films, the reduction of the Xe entrapment eliminates the nanobubbles and the generation of plasmas that initiates the laser damage. The defect suppression and its correlation to the increase in laser damage threshold is revealed by the combined analysis of Rutherford backscattering spectroscopy, electron paramagnetic resonance spectroscopy, transmission electron microscopy, and laser damage testing. Monte Carlo simulations suggest a much smaller entrapment of Xe gas by comparison to Ar, which is attributed to the significant difference in the energy of the reflected neutrals (3X) which are likely to be implanted. These results provide an effective process route with a fundamental understanding for producing high laser damage resistant dielectric films for high power and high energy laser applications.

36 MATERIALS SCIENCE↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma catalytic non-oxidative methane conversion to hydrogen and value-added hydrocarbons on zeolite 13X

Non-thermal plasma has unfolded highly efficient, safe to operate novel routes for methane conversion to hydrogen. In this work, methane conversion is performed under atmospheric dielectric barrier discharge (DBD) plasma with and without 13X zeolite-based catalysts i.e., 13X, Ga/13X, Pd/13X, and Pd-Ga/13X. Experimental results indicate that the plasma catalytic process delivered almost twofold higher product yield than the plasma only route. The binary Pd-Ga catalyst possesses highest catalytic performance with about 40 % CH 4 conversion at an input flowrate of 5 cm 3 min -1 and 2W due to the formation of the Pd-Ga alloy, which acts as catalytic active centre for activating C–H bonds. Product yield can be tailored by the catalyst design where the bimetallic Pd-Ga/13X preferably favours the hydrocarbon formation while H 2 is the dominant product obtained over the Pd/13X. The cleavage of C–H bonds of methane molecule over the plasma only route is mainly governed by energetic electrons in the gaseous phase the catalyst activity, and plasma-catalyst synergism play a significant role in the plasma catalysis process. Further, the findings from this work provide significant insights into the methane activation for subsequent optimization of the methane conversion processes operated on floating production, storage, and offloading vessels (FPSOVs). Exploiting untapped offshore natural gas reserves, where conventional pipeline systems are less economical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microscopic Mechanisms of Glasslike Lattice Thermal Transport in Cubic Cu 12 Sb 4 S 13 Tetrahedrites

Materials based on cubic tetrahedrites (Cu 12 Sb 4 S 13 ) are useful thermoelectrics with unusual thermal and electrical transport properties, such as very low and nearly temperature-independent lattice thermal conductivity (κ L ). We explain the microscopic origin of the glasslike κ L in Cu 12 Sb 4 S 13 by explicitly treating anharmonicity up to quartic terms for both phonon energies and phonon scattering rates. We show that the strongly unstable phonon modes associated with trigonally coordinated Cu atoms are anharmonically stabilized above approximately 100 K and continue hardening with increasing temperature in accord with experimental data. This temperature-induced hardening effect reduces scattering of heat carrying acoustic modes by reducing the available phase space for three-phonon processes, thereby balancing the conventional ∝ T increase in scattering due to phonon population and yielding nearly temperature independent κ L . Furthermore, we find that very strong phonon broadening leads to a qualitative breakdown of the conventional phonon-gas model and modify the dominant heat transport mechanism from the particlelike phonon wave packet propagation to incoherent contributions described by the off-diagonal terms in the heat-flux operator, which are typically prevailing in glasses and disordered crystals. Furthermore, our work paves the way to a deeper understanding of glasslike thermal conductivity in complex crystals with strong anharmonicity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of Berry phase on nonlinear response of two-dimensional fermions

We develop a theory of nonlinear response to an electric field of two-dimensional (2D) fermions with topologically nontrivial wave functions characterized by the Berry phase Φ n = n π , n = 1 , 2 , ... . In particular, we find that owing to the suppression of backscattering at odd n , Hall field-induced resistance oscillations, which stem from elastic electron transitions between Hall field-tilted Landau levels, are qualitatively distinct from those at even n : Their amplitude decays with the electric field and their extrema are phase shifted by a quarter cycle. The theory unifies the cases of graphene ( n = 1 ) and graphite bilayer ( n = 2 ) with the case of conventional 2D electron gas ( n = 0 ) and suggests another method to probe backscattering in topological 2D systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Large Eddy Simulation of Lean Mixed-Mode Combustion Assisted by Partial Fuel Stratification in a Spark-Ignition Engine

Partial fuel stratification (PFS) is a promising fuel injection strategy to improve the stability of lean combustion by applying a small amount of pilot injection right before spark timing. Mixed-mode combustion, which makes use of end-gas autoignition following conventional deflagration-based combustion, can be further utilized to speed up the overall combustion. In this study, PFS-assisted mixed-mode combustion in a lean-burn direct injection spark-ignition (DISI) engine is numerically investigated using multi-cycle large eddy simulation (LES). A previously developed hybrid G-equation/well-stirred reactor combustion model for the well-mixed operation is extended to the PFS-assisted operation. The experimental spray morphology is employed to derive spray model parameters for the pilot injection. The LES-based model is validated against experimental data and is further compared with the Reynolds-averaged Navier–Stokes (RANS)-based model. Overall, both RANS and LES predict the mean pressure and heat release rate traces well, while LES outperforms RANS in capturing the cycle-to-cycle variation (CCV) and the combustion phasing in the mass burned space. Liquid and vapor penetrations obtained from the simulations agree reasonably well with the experiment. Detailed flame structures predicted from the simulations reveal the transition from a sooting diffusion flame to a lean premixed flame, which is consistent with experimental findings. LES captures more wrinkled and stretched flames than RANS. Finally, the LES model is employed to investigate the impacts of fuel properties, including heat of vaporization (HoV) and laminar burning speed (SL). Combustion phasing is found more sensitive to SL than to HoV, with a larger fuel property sensitivity of the heat release rate from autoignition than that from deflagration. Moreover, the combustion phasing in the PFS-assisted operation is shown to be less sensitive to SL compared with the well-mixed operation.

fuel property sensitivity↗

Bias-pulsed atomic layer etching of 4H-silicon carbide producing subangstrom surface roughness

A new approach to atomic layer etching (ALE) has been demonstrated, and its application to 4H-SiC is reported here. By pulsing only the DC bias for an Ar/Cl2 inductively coupled plasma-reactive ion etching system, the etch cycle duration is reduced by more than an order of magnitude relative to conventional ALE processes. Gas flows are not changed throughout the ALE process. With this process protocol, we achieved an etch rate of 2.48±0.09 Å/cycle with 6 s cycles, an RMS surface roughness (Rq) of 0.83±0.08 Å, and an ALE synergy value of S = 99%. The parameters explored within this ALE process demonstrate effective subangstrom smoothening of 4H-SiC surfaces and is well-suited for a variety of classical and quantum device nanofabrication.

42 ENGINEERING↗