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DOE OSTI2022

Exploring the benefits of utilizing small modular device for sustainable and flexible shale gas water management

Growing shale gas extraction in recent years has triggered wide discussions on the associated freshwater requirement and wastewater management. Many optimization approaches have been developed for shale gas water management; however, most of the studies assumed permanent utilization of wastewater treatment facilities with fixed capacities. Considering the rapidly declining characteristics of shale gas wastewater production, these treatment facilities could remain largely underutilized after the first few months/years of production, making them less economically attractive. To maximize the capacity utilization of treatment facilities and further improve the economic performance of shale gas development, this study develops a systematic optimization framework, where the capacity strategy of conventional treatment facilities and utilization of the recent concept of modular manufacturing are both considered for flexible shale gas water management. The proposed mixed-integer linear programming (MILP) model simultaneously optimizes the design and planning of integrated shale gas and water supply chain, with a focus on capacity planning for both large-scale conventional treatment facilities and small-scale modular devices. A series of Marcellus-based case studies are performed to illustrate the applicability of the proposed model and provide general insights into the trade-offs between the multiple types of treatment facilities. The optimization results reveal that the combinatorial utilization of conventional facilities and modular devices for wastewater treatment (66% by conventional facilities and 34% by modular devices) brings 9.3% more reused water for other well development and 6.2% savings in water-related costs, compared to flexible management of only conventional facilities. Furthermore, this work suggests that taking modular device as auxiliary equipment for shale gas water management is most beneficial to increase the capacity utilization of treatment facilities and achieve a more economic and sustainable shale gas production system.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2020

Disordering of helium gas bubble superlattices in molybdenum under ion irradiation and thermal annealing

Self-organization of gas bubbles causes the formation of an ordered array of nanoscale gas bubbles (a gas bubble superlattice), a highly efficient mechanism for gas storage under irradiation. Here, the stability of helium (He) gas bubble superlattices in molybdenum (Mo) under krypton (Kr) ion irradiation and thermal annealing has been investigated. The He gas bubble superlattices gradually become disordered under Kr ion irradiation at 300° C, and the order-disorder transformation process completes at 2.5 dpa. Both transmission electron microscopy (TEM) and synchrotron-based small-angle X-ray scattering (SAXS) reveal that the order-disorder transformation of He gas bubble superlattices is associated with a slight increase in the average bubble size. Phase-field modeling indicates that the inhomogeneous growth and coarsening of bubbles/voids cause the disordering of imperfect superlattices under irradiation and implies that highly ordered superlattices could potentially exhibit much stronger resistance to irradiation damage. Under thermal annealing, the He gas bubble superlattices in Mo become unstable and disordered at 1000° C with the bubble size increasing from ~1.1 to ~1.6 nm. The finding in this research provides insights into the disordering mechanisms of defect superlattices as well as guidance for designing stable defect superlattices in harsh environments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Gas-driven short disconnection mitigates thermal runaway in Li-ion batteries under mechanical abuse

Mechanical abuse poses a critical safety risk to Li-ion batteries by inducing internal short circuits that initiate thermal runaway. Remarkably, voltage recovery frequently emerges during thermal runaway initiation, a phenomenon that conventional theories fail to explain. Here, our study develops a new multiphysics mechanism to explain voltage recovery, termed gas-driven short disconnection, whereby internal gas pressure mechanically disengages short-circuit contacts and causes the cell voltage to rebound. This mechanism incorporates gas generation and its structural impact on the short circuit. Real-time optical and thermal imaging and X-ray computed tomography reveal fluid-structure interaction between internal gas flow and adjacent shorting contacts. We establish a mechanistic framework linking gas-driven short disconnection to cell-level voltage and temperature responses, elucidating the extension–truncation pattern of voltage recovery. Furthermore, thermal regime maps show that a voltage recovery duration exceeding 5 s correlates with limited temperature rise below 150 °C, indicating that sustained short-circuit disconnection suppresses Joule heating. Additionally, a dimensionless criterion is deduced from scaling analysis for physical plausibility of gas-driven short disconnection in mechanically abused cells. This finding inspires smart venting control, which regulates gas release to maintain the internal pressure while dissipating gas enthalpy, thereby providing a device-level strategy for thermal runaway mitigation.

Gas-driven short disconnection↗

DOE OSTI2020

A pseudo-kinetic model to simulate phase changes in gas hydrate bearing sediments

Herein, modeling of the phase transitions anticipated in gas hydrate bearing sediments (GHBS) is critical for a proper understanding of time-dependent changes in states and volumes (e.g. the production of methane from this type of soils). We propose a new pseudo-kinetic approach to simulate the typical phase changes anticipated in GHBS, using published experimental results involving gas hydrate dissociation that are the basis of a widely used kinetic model. The proposed pseudo-kinetic model is formulated in the pressure-temperature (P-T) plane and assumes a rate of gas hydrate dissociation (or formation) proportional to the distance between the current state and the phase boundary. The model consists of only one parameter and is simple to implement in numerical simulators. A similar concept is used to model ice formation/thawing phenomena, but based on the ice/liquid-water phase boundary. We implemented the pseudo-kinetic model in a fully coupled thermo-hydro-chemo-mechanical (THCM) finite element code and validated it against experimental results performed on the dissociation of synthetic gas hydrate. We also evaluated the pseudo-kinetic model using synthetic cases covering several scenarios associated with gas hydrate formation/dissociation and ice formation/thawing. The model successfully reproduced the gas production test from a natural GHBS core from Korea (scaled gas venting experiment over 14 h), and also the formation of gas hydrate and ice in permafrost in Alaska (over 2 × 10 6 years). -The analyses show the versatility of the proposed pseudo-kinetic approach by applying it to model the different types of phase transitions typically encounter in GHBS. The simple formulation, easy implementation in numerical simulator, and reduced number of parameters (only one per phase change) make this model an attractive option for simulating phase transformations in problems involving GHBS.

58 GEOSCIENCES↗

DOE OSTI2024

An in situ imaging investigation of the effect of gas flow rates on directed energy deposition

Gas flow rates in Directed Energy Deposition (DED) Additive Manufacturing (AM) can significantly affect the quality of built parts by altering melt pool geometry. Using a DED process replicator and in situ synchrotron radiography, together with analogous experiments in an industrial DED machine, we investigate the impact of carrier gas and shield gas flow rates on build quality. The results reveal that there is a critical shield gas flow rate above which melt pools are flattened, tracks widen, and thus layer thickness decreases. The reduction in layer thickness is most prominent in conditions with low carrier gas flow rate, as the highly turbulent shield gas flow may divert slow moving powder particles away from the melt pool, decreasing capture efficiency. Very high flow rates increase internal porosity, as fast-moving particles impacting the melt pool surface can entrain chamber gas behind them. High gas flow rates also cool the melt pool, creating shallower melt pools with increased thermal gradients near the solidification front, increasing pore entrapment in the solidified track.

Additive manufacturing↗

DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Clean Condensing Gas Furnace

Natural gas furnaces are the most common space heating equipment in the U.S. residential and commercial building markets. However, current residential natural gas condensing furnaces generate substantial acidic condensate as well as significant emissions of sulfur oxides (SOx), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC), and methane (CH 4 ) contributing to environmental degradation of air, water, and soil. This report describes a novel solution to reduce the environmental impact of natural gas condensing furnaces based on the technology of a monolithic acidic gas reduction (AGR) catalyst for SOx trapping, NOx redox to nitrogen, and oxidation of formic acid, CO, HC, and CH 4 . The AGR technology offers the following benefits: (1) a neutral furnace condensate with a pH of ~7, allowing its safe release into the sewer system thus eliminating a second drainage system; (2) trapping and removing nearly all SOx emissions; (3) NOx emissions nearly at nearly 1-2 ng/J, more than 95% lower than new emissions standards in California; (4) the use of a low-cost heat exchanger as a condensing heat exchanger (HX) since the condensate is not acidic, avoiding the need for expensive stainless steel alloys; and (5) unburnt fuel energy recovery to boost efficiency.The AGR component and AGR-enabled furnace performance were broadly tested to determine their effects on long-term reliability and durability, as well as SOx storage and regeneration activity. The AGR regeneration does not impair the performance in achieving neutral condensate and ultra-low NOx emissions, and the AGR catalyst subjected to regeneration activities continued to function well and achieved slightly better annual fuel utilization efficiency (AFUE). The 400-hour reliability and durability test of the retrofitted condensing furnace with the AGR component shows that the furnace unit still achieves a neutral furnace condensate with a pH of ~7 and enables 0~3 ng/J of NOx emissions. However, the 400-hour operation slightly degraded the AFUE because of soot particle accumulation caused by frequent incomplete combustion owing to inappropriate condensate drainage during testing. Thus, proper condensate drainage is critical for AGR-enabled furnaces. Furthermore, neutron computed tomography was employed to survey the aged AGR component and demonstrate high-resolution 2D and 3D representations for the nondestructive diagnosis of the AGR component. The tomography showed that the AGR component did not deform or suffer broken AGR channels. A new AGR catalyst with low precious metal loading was preliminarily explored to identify a pathway of optimizing AGR material loading and maximizing acidic gas reduction at low cost. The new AGR component can reduce precious metal loading by 38% and still achieve neutral condensate and ultralow NOx emissions. The furnace with the AGR component of low Pt/Rh loading enables a maximum AFUE of 97%, which is meaningfully higher than the original furnace. Long-duration testing for the furnace enabled with the low precious metal loading AGR component will be vital in future research. Although the current work demonstrates a proof of concept for the AGR-enabled furnace, the AGR assembly needs to be optimized and integrated into the design of new OEM furnace products. Furthermore, the AGR technology can be applied not only for residential gas furnaces, but also for commercial rooftop units, gas heat pumps, gas-fired water heaters, combustion boilers, and other systems.

03 NATURAL GAS↗

DOE OSTI2026

Mechanistic Modeling of TEG Dehydrator Emissions in Oil and Gas Industry

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.

MAES↗

DOE OSTI2020

Natural gas liquefaction employing independent refrigerant path

A method of liquefying natural gas. The method comprises cooling a gaseous natural gas process stream with a refrigerant flowing in a path isolated from the natural gas process stream. The refrigerant may differ in composition from a composition of the natural gas process stream, and the refrigerant composition may be selected to enhance efficiency of the refrigerant path with regard to a specific composition of the natural gas process stream. The refrigeration path may be operated at pressures, temperatures and flow rates differing from those of the natural gas process stream. Other methods of liquefying natural gas are described. A natural gas liquefaction plant is also described.

03 NATURAL GAS↗

DOE OSTI2020

Adaptive sensing for a gas leak detection

A method, a system and an apparatus for adaptively sensing a gas leak. The method includes: obtaining wind data from a wind sensor, identifying at least one wireless mote in a plurality of wireless motes that is most likely to detect a gas plume from the wind data, activating the identified at least one wireless mote to trigger measuring gas concentration of the gas plume, and identifying the location of the gas leak if the gas concentration is above a predetermined threshold. Also included is a system for adaptively sensing a gas leak having a wind sensor, a plurality of wireless motes and a server in communication therewith. An apparatus for adaptively sensing a gas leak in an industrial site is also provided.

03 NATURAL GAS↗

DOE OSTI2021

Coordinated Modeling of Electric Grid and Natural Gas Network Operations

Presentation based upon full report of a Colorado case study and coordination framework, which is available at https://www.nrel.gov/docs/fy20osti/77096.pdf. JISEA analysts Brian Sergi, Omar Guerra, and Bri-Mathias Hodge will present on recent JISEA work on coordination between the natural gas and electricity sectors. Power and gas are becoming increasingly interdependent but weren't designed to function together. How does greater coordination impact system operations with different levels of solar and wind penetrations? This free JISEA presentation will take place in a Webinar on Tuesday, May 11, 2021 at 12 p.m.: Learn how greater coordination between the natural gas and electricity sectors impacts system operations with different levels of solar and wind penetrations. Presentation information includes: Historical and projected data for natural gas consumption and power generation in the United States as demonstrated by 2014 East Coast Polar Vortex, 2021 Texas Winter Storm Uri. Showing coupling points, FERC identified need for better coordination, different levels of coordination (decision making and optimization control), coordination framework. Case study on Colorado Front Range, ramping requirements and gas nominations, real-time dispatch (June and December scenarios), results of analysis of impacts of coordination on unserved load. Total real-time gas offtakes by node, impacts on unserved gas, effect on CO2 emissions. Discussions on clusions drawn from Colorado Case study expanded co-simulation via HELICS, objectives of the HELICS+ natural gas use case, modeling of hydrogen blending, techno economic assessment of blending, and blending impacts on energy content and pressure.

analysis↗

DOE OSTI2023

Portable chemical detection platform for on-site monitoring of odorant levels in natural gas

The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert–butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1–5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.

03 NATURAL GAS↗

DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗

DOE OSTI2022

Phase I: Natural Gas-Based Energy Storage at Abbott Power Plant

Compressed Natural Gas Energy Storage (CNGES), uses the potential energy of compressed natural gas within an integrated energy storage system. Specifically, an inventory of high-pressure natural gas is stored during off-peak hours in a first stage by controlling the balance of gas entering a pipeline from the transmission system, and in a second stage by using new compressors to fill vessels onsite. The natural gas storage medium is then discharged through an expander-generator to use the potential energy from the gas to generate electricity without combustion. The excess chemical energy stored in the natural gas is integrated with an existing fossil-based asset to provide power generation during peak hours and increase the reliability of the associated fossil generating facility.

03 NATURAL GAS↗

DOE OSTI2023

Molecular Dynamics Simulation of Pore-Size Effects on Gas Adsorption Kinetics in Zeolites

Strong gas-mineral interactions or slow adsorption kinetics require a molecular-level understanding of both adsorption and diffusion for these interactions to be properly described in transport models. In this combined molecular simulation and experimental study, noble gas adsorption and mobility is investigated in two naturally abundant zeolites whose pores are similar in size (clinoptilolite) and greater than (mordenite) the gas diameters. Simulated adsorption isotherms obtained from grand canonical Monte Carlo simulations indicate that both zeolites can accommodate even the largest gas (Rn). However, gas mobility in clinoptilolite is significantly hindered at pore-limiting window sites, as seen from molecular dynamics simulations in both bulk and slab zeolite models. Further, experimental gas adsorption isotherms for clinoptilolite confirm the presence of a kinetic barrier to Xe uptake, resulting in the unusual property of reverse Kr/Xe selectivity. Finally, a kinetic model is used to fit the simulated gas loading profiles, allowing a comparison of trends in gas diffusivity in the zeolite pores.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Noble gas adsorption to tuff

For this report a method was developed to measure trace noble gas element adsorption to the surfaces of geologic materials in the presence of a background gas that could potentially compete for surface adsorption sites. Adsorption of four noble gas elements (Ne, Ar, Kr, and Xe) at a concentration of 100 ppm in helium and nitrogen were measured on a sample of crushed tuff at 0, 15, 30, and 45°C. In addition, Ne, Ar, Kr, and Xe at 250 ppm and 500 ppm in nitrogen at 15°C were measured. Noble gas adsorption was found to increase with increasing atomic mass and decreasing temperature. It was also observed that the relative increase in noble gas element adsorption with decreasing temperature tends to increase with increasing atomic mass. Noble gas adsorption from nitrogen was approximately an order of magnitude greater than for the noble gases in helium. As the noble gas concentrations in nitrogen increased, adsorption increased in a slightly non-linear fashion which could be modeled using a Freundlich isotherm. For noble gas concentrations that were ≤100 ppm Henry's Law constant were calculated.

58 GEOSCIENCES↗

DOE OSTI2023

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗

DOE OSTI2025

Pressure-stable supported ionic liquid membranes using isoporous supports for evaluating pure- and mixed-gas light paraffin fractionation

Advances in horizontal drilling and hydraulic fracturing have spurred the growth of domestic U.S. energy production. Membranes, typically silicone rubbers, have found utility in shale gas treatment as fuel gas conditioning units to selectively remove C 2 + hydrocarbons at pressures up to 30 bar, producing clean CH 4 for gas engines. However, more selective materials could be beneficial for broader shale gas treatment applications, such as dew point control units. Supported ionic liquid membranes (SILMs) offer a potential opportunity for improving C 3 H 8 /CH 4 selectivity, but they lack pressure-stability. Here, we report C 3 H 8 /CH 4 selective and pressure-stable SILMs using isoporous supports. SILMs with supports that had minimal defects remained stable up to 15 bar of transmembrane pressure. This stability allowed for pure- and mixed-gas testing of the resulting membranes at elevated pressures. Furthermore, these tests revealed that low viscosity ILs (<100 cp) may display mixed-gas permeances and permselectivity nearly identical to pure-gas results. On the other hand, higher viscosity ILs may display increasing permeances and permselectivity with increasing C 3 H 8 fugacity, similar to rubbery polymers. Ultimately, the SILMs demonstrated relatively high pressure-stability due to the isoporous supports and competitive mixed-gas C 3 H 8 /CH 4 permselectivity compared to silicone rubber.

Rosenthal, Justin J. [University of Texas at Austi↗