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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Seamless Hybrid-integrated Interconnect NEtwork (SHINE)

Large-scale date centers are becoming increasingly limited by the capacity of interconnects due to the rapid increasing power consumption and bandwidth demands driven by the rigorous down scaling of CMOS critical dimensions in according with the Moore’s Law. As a result of the continuing bandwidth scaling, optical interconnects based on parallel optics, where data are simultaneously transmitted along more than one lane, have becoming a preferred interconnected solution over copper cables. To building an efficient optical interconnect system, optical coupling between different elements, such as optical fibers, photonics chips, is a critical step, which is challenging due to the mode mismatch of varies optical ports. In this project, we proposed and demonstrated an optical interfacing scheme, which provided a light coupling approach with low energy loss, broadband operation, high alignment tolerance and compatible with scalable fabrication and testing. Here, the mode transformation is achieved by a total internal reflection from a chip integrated microscale freefrom surface. Due to the enormous light wavefront manipulating ability associated with the gigantic design space, the freeform couplers platform is universally applicable to a wide range of optical coupling scenarios, such as the interfacing between a waveguide to a fiber, another waveguide, surface normal device, or free space.

42 ENGINEERING↗
DOE OSTI2019

Development of Transient Coupled Chemical-Thermal-Fluids Simulation for Unsealed Aluminum-Clad Spent Nuclear Fuel Storage Canister - 19273

This study examines a preliminary three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model of the unsealed canisters containing aluminum-clad spent nuclear fuel from INL's ATR in the irradiated fuel storage facility. This 3D CFD model considers fully resolved fuel plates in an unsealed canister with small mass exchange with surrounding air as time evolves in the simulation and contains a network of chemical reactions to consider due to several of the side reactions occurring in the presence of water vapor, nitrogen, oxygen and carbon dioxide rather than in helium backfilled DOE standard canisters. Prior to the CFD modeling, the full set of chemical reactions under these conditions was analyzed, reduced, and refit to a more manageable number of equations for the computational efficiency of the 3D CFD simulation. To deal with the long time-scale of interest for tracking the possible buildup of trace species such as nitric acid, NOx, and hydrogen, a segregated time stepping algorithm is used, wherein the velocity field is only updated periodically, and assumed to be in a pseudo steady state. This study first examines the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields, hydrogen gas and nitric acid concentrations within unsealed canisters in conditions relevant to the INL INTEC CPP-603 facility over a long period of time. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Free-spray characteristics and spray-wall interactions of methanol on a gasoline direct injector under flash-boiling and non-flash-boiling conditions

Methanol is considered a promising alternative fuel for internal combustion engines (ICEs) due to its high-octane number, fast laminar flame speed, and elevated latent heat of vaporization, all of which support higher compression ratios and improved thermal efficiency. However, its substantial latent heat of vaporization also poses cold-start challenges, such as misfire and fuel film deposition. This study aims to investigate methanol spray morphology and spray-wall interaction using the Spray M injector from the Engine Combustion Network within a constant-pressure flow vessel. A recently developed unified numerical framework capable of modeling both flash and non-flash boiling sprays is validated against experimental liquid volume fraction data acquired via 3-D computed tomography. Here, the results reveal that flash boiling significantly alters the spray morphology, leading to smaller droplets and spray collapse due to enhanced air-entrainment-induced turbulence. Quantitative agreement between experiments and simulations confirms this behavior. Coupled 0-D equilibrium and 3-D computational fluid dynamics analyses show that flash boiling accelerates evaporation and reduces fuel residence time, while non-flash conditions maintain a persistent liquid core more susceptible to wall wetting. Wall temperature diagnostics reveal that spray collapse alters heat transfer patterns by shifting cooling effects. Mixture fraction analysis indicates that evaporation is primarily governed by shear-layer turbulence, though deviations from adiabatic equilibrium mixing emerge under low-turbulence conditions. Finally, increasing fuel, ambient, and wall temperatures reduces wall wetting and film thickness, mitigating cold-start risks. These findings enhance the understanding of methanol sprays’ behavior and support its adoption as a viable, alternative fuel for ICEs.

Engine Combustion Network↗
DOE OSTI2023

Active Thermochemical Tables: Enthalpies of Formation of Bromo- and Iodo-Methanes, Ethenes and Ethynes

Here, the thermochemistry of halocarbon species containing iodine and bromine is examined through an extensive interplay between new Feller–Peterson–Dixon (FPD) style composite methods and a detailed analysis of all available experimental and theoretical determinations using the thermochemical network that underlies the Active Thermochemical Tables (ATcT). From the computational viewpoint, a slower convergence of the components of composite thermochemistry methods is observed relative to species that solely contain first row elements, leading to a higher computational expense for achieving comparable levels of accuracy. Potential systematic sources of computational uncertainty are investigated, and, not surprisingly, spin-orbit coupling is found to be a critical component, particularly for iodine containing molecular species. The ATcT analysis of available experimental and theoretical determinations indicates that prior theoretical determinations have significantly larger uncertainties than originally reported, particularly in cases where molecular spin-orbit effects were ignored. Accurate and reliable heats of formation are reported for 38 halogen containing systems, based on combining the current computations with previous experimental and theoretical work via the ATcT approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Digital Twin for Chemical Science: a case study on water interactions on the Ag(111) surface

Directly visualizing chemical trajectories offers insights into catalysis, gas-phase reactions and photoinduced dynamics. Tracking the transformation of chemical species is best achieved by coupling theory and experiment. Here we developed Digital Twin for Chemical Science (DTCS) v.01, which integrates theory, experiment and their bidirectional feedback loops into a unified platform for chemical characterization. DTCS addresses a core question: given a set of experimental conditions, what is the expected outcome and why? It consists of a forward solver that takes a chemical reaction network and predicts spectra under experimental conditions, and an inverse solver that infers kinetics from measured spectra. We applied DTCS to ambient-pressure X-ray photoelectron spectroscopy measurements of the Ag–H2O interface as an example. This approach enables real-time knowledge extraction and guides experiments until a stopping condition is met based on accuracy and degeneracy. As a step toward autonomous chemical characterization, DTCS provides mechanistic knowledge in a verified, standardized manner.

Chemistry↗
DOE OSTI2024

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗
DOE OSTI2019

A deep learning enabler for nonintrusive reduced order modeling of fluid flows

Here in this paper, we introduce a modular deep neural network (DNN) framework for data-driven reduced order modeling of dynamical systems relevant to fluid flows. We propose various DNN architectures which numerically predict evolution of dynamical systems by learning from either using discrete state or slope information of the system. Our approach has been demonstrated using both residual formula and backward difference scheme formulas. However, it can be easily generalized into many different numerical schemes as well. We give a demonstration of our framework for three examples: (i) Kraichnan-Orszag system, an illustrative coupled nonlinear ordinary differential equation, (ii) Lorenz system exhibiting chaotic behavior, and (iii) a nonintrusive model order reduction framework for the two-dimensional Boussinesq equations with a differentially heated cavity flow setup at various Rayleigh numbers. Using only snapshots of state variables at discrete time instances, our data-driven approach can be considered truly nonintrusive since any prior information about the underlying governing equations is not required for generating the reduced order model. Our a posteriori analysis shows that the proposed data-driven approach is remarkably accurate and can be used as a robust predictive tool for nonintrusive model order reduction of complex fluid flows.

42 ENGINEERING↗
DOE OSTI2022

Grid-Interactive Electric Vehicle and Building Coordination Using Coupled Distributed Control: Preprint

As an increasing number of controllable devices are introduced onto the grid, they can individually provide ancillary services in support of grid stability. However, the goals of each device differ due to their type and individual objectives, causing instances where they may conflict. To reduce the chances of these devices contributing to grid instability, these devices must effectively communicate in a cooperative manner to both meet their own needs while providing services to the grid. Previous work demonstrates that the NALD (Network Lasso-ADMM - Limited Communication - DMPC) algorithm allows coordination between two subsystems that use different control algorithms (building and charging stations) to provide services to the grid and individually optimize their performance in a specific scenario. The ideal NALD algorithm should be generalized to allow plug-and-play capabilities across devices of differing characteristics. This paper takes a step toward generalizability by updating the electric vehicle charging objective and re-defining the communication scheme compared to prior work to generalize the coordination and, as a result, improve the performance of the NALD algorithm.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2018

Simulating the density of organic species in the atmosphere of Titan with a coupled ion-neutral photochemical model

We introduce a one-dimensional coupled ion-neutral photochemical kinetics and diffusion model to study the atmospheric composition of Titan in light of new theoretical kinetics calculations and scientific findings from the Cassini–Huygens mission. The model extends from the surface to the exobase. The atmospheric background, boundary conditions, vertical transport and aerosol opacity are all constrained by the Cassini–Huygens observations. The chemical network includes reactions between hydrocarbons, nitrogen and oxygen bearing species. It takes into account neutrals and both positive and negative ions with masses extending up to 116 and 74 u, respectively. We incorporate high-resolution isotopic photoabsorption and photodissociation cross sections for N 2 as well as new photodissociation branching ratios for CH 4 and C 2 H 2 . Ab initio transition state theory calculations are performed in order to estimate the rate coefficients and products for critical reactions. Critical reactions of production and loss for neutrals and ions are quantitatively assessed and thoroughly discussed. The vertical distributions of neutrals and ions predicted by the model generally reproduce observational data, suggesting that for the small species most chemical processes in Titan’s atmosphere and ionosphere are adequately described and understood; some differences are highlighted. Notable remaining issues include (i) the total positive ion density (essentially HCNH + ) in the upper ionosphere, (ii) the low mass negative ion densities (CN - , C 3 N - /C4H - ) in the upper atmosphere, and (iii) the minor oxygen-bearing species (CO 2 , H 2 O) density in the stratosphere. Pathways towards complex molecules and the impact of aerosols (UV shielding, atomic and molecular hydrogen budget, nitriles heterogeneous chemistry and condensation) are evaluated in the model, along with lifetimes and solar cycle variations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

SCOPE: Spectral cloud optical property estimation using real-time GOES-R longwave imagery

The output of ground-based, solar power generation systems is strongly dependent on cloud cover, which is the main contributor to solar power variability and uncertainty. Cloud optical properties are typically over-simplified in forecasting applications due to the lack of realtime, accurate estimates. In this work, we introduce a method, the Spectral Cloud Optical Property Estimation (SCOPE), for estimating cloud optical properties directly from high-resolution (5-min, 2 km) imagery from Geostationary Operational Environmental Satellite (GOES)-R, which is the newest generation of the GOES system. The SCOPE method couples a two-stream, spectrally resolved radiative model with the longwave GOES-R sensor output to simultaneously estimate the cloud optical depth, cloud top height, and cloud thickness during both day and night at 5-min intervals. The accuracy of SCOPE is evaluated using one year (2018) of downwelling longwave (DLW) radiation measurements from the Surface Radiation Budget Network, which consists of seven sites spread across climatically diverse regions of the contiguous United States. During daytime clear-sky periods, SCOPE predicts DLW within instrument uncertainty (10 W m -2 ) for four of the seven locations, with the remaining locations yielding errors of the order of 11.2, 17.7, and 20.2 W m -2 . For daytime cloudy-sky, daytime all-sky (clear or cloudy), and nighttime all-sky periods, SCOPE achieves root mean square error values of 23.0–34.5 W m -2 for all seven locations. These results, together with the low-latency of the method (1 s per sample), show that SCOPE provides a viable solution to real-time, accurate estimation of cloud optical properties for both day and night.

42 ENGINEERING↗
DOE OSTI2022

Twistronics of Janus transition metal dichalcogenide bilayers

Twisted multilayers of two-dimensional (2D) materials are an increasingly important platform for investigating quantum phases of matter, and in particular, strongly correlated electrons. The moiré pattern introduced by the relative twist between layers creates effective potentials of long wavelength, leading to electron localization. However, in contrast to the abundance of 2D materials, few twisted heterostructures have been studied until now. Here, in this study, we develop a first-principles continuum theory to study the electronic bands introduced by moire patterns of twisted Janus transition metal dichalcogenide (TMD) homo- and heterobilayers. The model includes lattice relaxation, stacking-dependent effective mass, and Rashba spin-orbit coupling. We then perform a high-throughput generation and characterization of DFT-extracted continuum models for more than a hundred possible combinations of materials and stackings. Our model predicts that the moiré physics and emergent symmetries depend on chemical composition, vertical layer orientation, and twist angle, so that the miniband wave functions can form triangular, honeycomb, and kagome networks. Rashba spin-orbit effects, peculiar of these systems, can dominate the moiré bandwidth at small angles. Our work enables detailed investigation of Janus twisted heterostructures, allowing the discovery and control of novel electronic phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Experiments to Quantify the Shielding Efficacy of Materials to be Implemented for Portable Shielding Enclosures that Adequately Mitigate EMI from Lighting Attachment Events

Mitigating electric and magnetic fields induced by lightning strike events is critical for the security and longevity of electrical components. Electromagnetic interference originating from a lightning strike is categorized into the low to medium frequency ranges, commonly referred to as the “magnetic coupling” regime. This low-frequency characteristic brings about the problem of shielding magnetic flux lines. Such shielding can be accomplished with highly conductive materials via the generation of eddy currents or by diverting the flux lines using materials with a large relative permeability. The shielding effectiveness of materials with varying thicknesses and geometry are tested using a pulse forming network having comparable characteristics to a scaled lighting strike. A four-stage Marx generator with a peak current of ~33 kA and a risetime of 1.4 μs is used as the pulse forming network to emulate the scaled electric and magnetic fields. The data collected from these experiments provide information and techniques that can be implemented into the design of a portable, deployable shielding enclosure.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Learning thermodynamic master equations for open quantum systems

The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a variety of ways, including by modeling with deep neural networks. However, the majority of mathematical models describing open quantum systems are linear, and the natural nonlinearities in learnable models have not been incorporated using physical principles. We present a data-driven model for open quantum systems that includes learnable, thermodynamically consistent terms. The trained model is interpretable, as it directly estimates the system Hamiltonian and linear components of coupling to the environment. We validate the model on synthetic two and three-level data, as well as experimental two-level data collected from a quantum device at Lawrence Livermore National Laboratory.

Mathematics and Computing↗
DOE OSTI2022

Optimization of Integrated Energy Systems

Integrated energy systems that couple nuclear power plants with additional products including hydrogen, storage, or synthetic fuels provide a more flexible energy source that can be more economical than generating electricity alone. Determining the size and shape of these systems and optimizing their operation is challenging. INL, through the IES program, has developed optimization software to help solve these challenges. Holistic Energy Resource Optimization Network (HERON) is a software tool to optimize the size and capacity of integrated energy systems using stochastic optimization. Optimization of Real-time Capacity Allocation (ORCA) is a software tool under development to perform real-time economic optimization of these systems using economic model predictive control. An overview of these tools and a discussion of their optimization methods will be presented in this talk.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Resistive-Aware Linear Approximations for Solving the Optimal Power Flow Problem for Distribution Networks

Although notable progress has been made to solve the Alternate Current (AC) Optimal Power Flow (OPF), the Direct Current (DC) and Decoupled OPF approximations are still preferable in broad scenarios of practical interest. These approximations typically assume that the resistive nature of the lines in the power system is negligible. This work discusses modifications of these assumptions and presents new approximations of the DC and Decoupled OPF in light of distribution systems, in which line resistances may not be negligible. The Enhanced DC (EDC) OPF and Coupled OPF (COPF) approximations are introduced and assessed, presenting favorable results compared to their classic counterparts.

Moutis, Panayiotis↗
DOE OSTI2023

Covalent Triazine Framework-Derived Membranes: Engineered Sol–Gel Construction and Gas Separation Application

Covalent triazine frameworks (CTFs) represent one of the most extensively studied organic networks characterized by graphitic π-conjugated structures linked by aza-fused rings, possessing unique features such as compositions of light elements (e.g., C, H, and N), porous architectures abundant heteroatom involvement, and extensively conjugated structures. In addition, the textural and chemical structures of CTFs could be engineered via synthesis control to accommodate diverse applications. CTF materials with notable characteristics, including plentiful (ultra-)micropores, high surface areas, and the presence of CO 2 -philic functional groups involving nitrogen (N), oxygen (O), and fluorine (F), hold great promise as potential candidates for anthropogenic CO 2 capture and sequestration (CCS) applications. However, the conventional high-temperature involved ionothermal procedures and the solution-based coupling pathway only afforded CTF materials in powder form, which is difficult to be processed toward membrane formation. Successful fabrication of CTF-derived membranes will rely on the development of alternative polymerization approaches as well as structural engineering to afford membrane architectures with controllable porosity distribution and active interaction sites with CO 2 benefiting the CO 2 separation procedure. In this Account, a demonstration of the latest progress in the development of CTF-derived membranes was provided. The CTF membranes were mainly synthesized via a superacid (e.g., CF 3 SO 3 H)-promoted sol–gel approach involving the polymerization of aromatic nitrile monomers. The formation of the triazine unit through the trimerization of cyano groups served as the cross-linkers, resulting in the creation of π-conjugated networks alongside the arenes present in the starting materials. The aromatic nitrile monomers with rigid and sterically hindered structures were required to afford CTF membranes with nanoporous architectures. The acidity of the superacid and reactivity of the aromatic monomers played critical roles in the polymerization efficiency. The monomer diversity and synthesis tunability endowed the introduction of CO 2 -philic functionalities (e.g., pyrazole and fluorine) within the CTF skeletons, and integration of ionic moieties was achieved by adopting FSO 3 H with stronger acidity as the catalyst and aromatic nitrile monomers with pyrazine structures. To ensure the successful construction of fluorinated CTF membranes, it is important to avoid any fluorines on the ortho-position of the cyano groups on the benzene ring. Through control over the monomers and reaction conditions, flexible, transparent, and insoluble CTF membranes could be fabricated. The sol–gel method could be further expanded to membrane fabrication through acetyl-to-benzene transformation through synthesis control. The mild oxidation-exfoliation-filtration method was also demonstrated to fabricate substrate-supported CTF membranes. The as-afforded membranes are well characterized to determine the structural features and provide information to study the structure-performance relationship. Here, the application of CTF membranes in CO 2 separation was summarized, focusing on the approaches being developed to enhance CO 2 uptake and separation performance. In addition to utilizing the pristine CTF membranes for gas separation, functionalized carbon molecular sieve membranes could be obtained from the pyrolysis of thermally stable CTF membrane precursors toward efficient CO 2 separation, benefiting from the abundant ultramicropores being created during the pyrolysis/decomposition procedure and involvement of CO 2 -philic functionalities such as fluorine and nitrogen-containing moieties. Based on these achievements, unsolved issues in CTF membrane-related fabrication and applications, including the potential solution approaches, have been proposed to advance the application of CTF membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Cross-Linked Poly(ethylene oxide) Ion Gels Containing Functionalized Imidazolium Ionic Liquids as Carbon Dioxide Separation Membranes

1,3-Substituted imidazolium bis(trifluoromethylsulfonyl)imide (Tf 2 N) ionic liquids (ILs) were incorporated at 40 and 60 vol % loading into a cross-linked poly(ethylene oxide) polymer network to create ion gels for carbon dioxide (CO 2 )-selective gas separation membranes. The ILs plasticize the poly(ethylene oxide)-based polymer to increase its gas permeability. Compared to the base polymer, with a CO 2 permeability of 145 barrer and a CO 2 against nitrogen (N 2 ) selectivity of 47, the highest CO 2 permeability achieved was 530 barrer coupled with a CO 2 /N 2 selectivity of 31 by having 60 vol % [1-ethyl-3-methylimidazolium][Tf 2 N]. The extent of gas permeability improvement depends on the cation’s terminal substituent. Substituents that promote additional noncovalent intermolecular interactions, such as hydroxyl, benzyl, and nitrile, can reduce the gas diffusivity by reducing the polymer chain mobility. Here, while n -alkyl, branched alkyl, and oligo(ethylene glycol) substituents can significantly increase the gas permeability, the shortest substituents (such as ethyl) were the most effective because they promote high ionic charge density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗