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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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NASA NTRS1994

Application of electron paramagnetic resonance imaging to the characterization of the Ultem(R) exposed to 1 MeV electrons. Correlation of radical density data to tiger code calculations

A major long-term goal of the Materials Division at the NASA Langley Research Center is the characterization of new high-performance materials that have potential applications in the aircraft industry, and in space. The materials used for space applications are often subjected to a harsh and potentially damaging radiation environment. The present study constitutes the application of a novel technique to obtain reliable data for ascertaining the molecular basis for the resilience and durability of materials that have been exposed to simulated space radiations. The radiations of greatest concern are energetic electrons and protons, as well as galactic cosmic rays. Presently, the effects of such radiation on matter are not understood in their entirety. It is clear however, that electron radiation causes ionization and homolytic bond rupture, resulting in the formation of paramagnetic spin centers in the polymer matrices of the structural materials. Since the detection and structure elucidation of paramagnetic species are most readily accomplished using Electron Paramagnetic Resonance (EPR) Spectroscopy, the NASA LaRC EPR system was brought back on-line during the 1991 ASEE term. The subsequent 1992 ASEE term was devoted to the adaptation of the EPR core system to meet the requirements for EPR Imaging (EPRI), which provides detailed information on the spatial distribution of paramagnetic species in bulk media. The present (1994) ASEE term was devoted to the calibration of this EPR Imaging system, as well as to the application of this technology to study the effects of electron irradiation on Ultem(exp R), a high performance polymer which is a candidate for applications in aerospace. The Ultem was exposed to a dose of 2.4 x 10(exp 9) Rads (1-MeV energy/electron) at the LaRC electron accelerator facility. Subsequently, the exposed specimens were stored in liquid nitrogen, until immediately prior to analyses by EPRI. The intensity and dimensions of the EPR Images that were generated for the irradiated specimens showed that the electrons penetrated the material to a depth of approximately 0.125 inch. These data show a very high degree of correlation to the energy deposition profile as predicted by the Tiger Code, a Monte Carlo code that provides guidelines for the transport of electrons in matter. Subsequent efforts will focus on delineating the transport properties of energetic protons in Ultem(R).

Suleman, Naushadalli K.↗

NASA NTRS2020

Petrologic Evidence of Hydrothermal Activity on the EL3 Parent Asteroid

Introduction: Hydrothermal alteration is an important process in the evolution of asteroids. It was active in the earliest stages of asteroid evolution as evidenced by the secondary minerals in the meteorite record and is thought to be active today in the asteroid belt on icy bodies such as Ceres, as suggested by imaging and surface mineralogy from the DAWN mission. The Northwest Africa (NWA) 8785 enstatite chondrite is an anomalous EL3 chondrite that shows potential evidence of extensive hydrothermal activity on the E chondrite parent asteroid. The enstatite meteorites are of particular significance for the evolution of the terrestrial planets, having stable (O, Cr, Ti, Ni, Zn) isotope com- positions similar to the Earth-Moon and reduced chemistry similar to planet Mercury, as inferred from experiments. NWA 8785 is the first EL3 enstatite chondrite known to be rich in fine-grained matrix and is further unusual in that the matrix is FeO-rich. All previously studied enstatite chondrites are matrix-poor and/or their matrices are composed of reduced mineral assemblages similar to their chondrules. Here we describe the matrix mineralogy of this unusual EL3 chondrite NWA 8785 and discuss its implications for the EL3 parent asteroid(s) and hydrothermal activity in meteorite parent bodies.

Weisberg, K.↗

NASA NTRS1992

Time and wavelength domain algorithms for chemical analysis by laser radar

Laser-induced fluorescence (LIF) is a promising technique for laser radar applications. Laser radar using LIF has already been applied to algae blooms and oil slicks. Laser radar using LIF has great potential for remote chemical analysis because LIF spectra are extremely sensitive to chemical composition. However, most samples in the real world contain mixtures of fluorescing components, not merely individual components. Multicomponent analysis of laser radar returns from mixtures is often difficult because LIF spectra from solids and liquids are very broad and devoid of line structure. Therefore, algorithms for interpreting LIF spectra from laser radar returns must be able to analyze spectra that overlap in multicomponent systems. This paper analyzes the possibility of using factor analysis-rank annihilation (FARA) to analyze emission-time matrices (ETM) from laser radar returns instead of excitation-emission matrices (EEM). The authors here define ETM as matrices where the rows (or columns) are emission spectra at fixed times and the columns (or rows) are temporal profiles for fixed emission wavelengths. Laser radar usually uses pulsed lasers for ranging purposes, which are suitable for measuring temporal profiles. Laser radar targets are hard instead of diffuse; that is, a definite surface emits the fluorescence instead of an extended volume. A hard target would not broaden the temporal profiles as would a diffuse target. Both fluorescence lifetimes and emission spectra are sensitive to chemical composition. Therefore, temporal profiles can be used instead of excitation spectra in FARA analysis of laser radar returns. The resulting laser radar returns would be ETM instead of EEM.

Rosen, David L.↗

NASA NTRS2016

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

ozone↗

NASA NTRS2016

Evaluating a Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product.TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

TEMPO↗

NASA NTRS1976

Development and evaluation of a Hadamard transform imaging spectrometer and a Hadamard transform thermal imager

A spectrometric imager and a thermal imager, which achieve multiplexing by the use of binary optical encoding masks, were developed. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. Spatial and/or spectral data is obtained in the form of a Hadamard transform of the spatial and/or spectral scene; computer algorithms are then used to decode the data and reconstruct images of the original scene. The hardware, algorithms and processing/display facility are described. A number of spatial and spatial/spectral images are presented. The achievement of a signal-to-noise improvement due to the signal multiplexing was also demonstrated. An analysis of the results indicates both the situations for which the multiplex advantage may be gained, and the limitations of the technique. A number of potential applications of the spectrometric imager are discussed.

Harwit, M.↗

NASA NTRS1990

The relation between ferroelasticity and superconductivity

The high-temperature superconductivity is explained widely by the layered crystal structure. The one- and two-dimensional subsystems and their interaction are investigated here. It is assumed that the high-T(sub c) superconductivity takes place in the two-dimensional subsystem and the increase of the phase transition temperature from 60 K up to 90 K is the consequence of turning on the influence of one-dimensional chains. The interaction between the two subsystems is transferred along the c axis by the phonons of breathing mode, which causes the hybridization of the electronic bonds between these subsystems. The experimental works indicate that the existence of both the chains Cu(1)-O and their interaction with the superconducting plane of Cu(2)-O modify the temperature of the transition to the superconducting state. It is seen from the neutron scattering data that the rates of the interatomic distance dependencies on temperature are changed around 140 K and 90 K. The 'zig-zag' order in Cu(1)-O chains has been postulated but, on the other hand, the vibrations with a large amplitude only were reported. The bi-stabilized situation of the oxygen ions can be caused by the change of distance between these ions and the Ba ions. It leads to the appearance of a two-well potential. Its parameters depend on temperature and the dynamics of the oxygen ions' movement. They can induce the antipolar order, which can be, however, more or less chaotic. The investigation of the ferroelastic properties of Y-Ba-Cu-O samples lead to the conclusion that they are related to jumps of ions inside the given chain and not to a diffusion between different sites in the ab plane. Researchers deduce thus that the fluctuating oxygen ions from these chains create dipoles in the ab plane. They can be described with the pseudo-spin formalism/ - Pauli matrices/. The system can be described with the Ising model. The pseudo-spins interact with phonons and influence the superconductivity in the second subsystem.

Molak, A.↗

NASA NTRS1991

The relation between ferroelasticity and superconductivity

The high-temperature superconductivity is explained widely by the layered crystal structure. The one- and two-dimensional subsystems and their interaction are investigated here. It is assumed that the high-T(sub c) superconductivity takes place in the two-dimensional subsystem and the increase of the phase transition temperature from 60 K up to 90 K is the consequence of turning on the influence of one-dimensional chains. The interaction between the two subsystems is transferred along the c axis by the phonons of breathing mode, which causes the hybridization of the electronic bonds between these subsystems. The experimental works indicate that the existence of both the chains Cu(1)-O and their interaction with the superconducting plane of Cu(2)-O modify the temperature of the transition to the superconducting state. It is seen from the neutron scattering data that the rates of the interatomic distance dependencies on temperature are changed around 240 K and 90 K. The 'zig-zag' order in Cu(1)-O chains has been postulated but, on the other hand, the vibrations with a large amplitude only were reported. The bi-stabilized situation of the oxygen ions can be caused by the change of distance between these ions and the Ba ions. It leads to the appearance of a two-well potential. Its parameters depend on temperature and the dynamics of the oxygen ions' movement. They can induce the antipolar order, which can be, however, more or less chaotic. The investigation of the ferroelastic properties of Y-Ba-Cu-O samples lead to the conclusion that they are related to jumps of ions inside the given chain and not to a diffusion between different sites in the ab plane. Researchers deduce, thus, that the fluctuating oxygen ions from these chains create dipoles in the ab plane. They can be described with the pseudo-spin formalism (- Pauli matrices). The system can be described with the Ising model. The pseudo-spins interact with phonons and influence the superconductivity in the second subsystem.

Molak, A.↗

NASA NTRS1993

The analysis of convolutional codes via the extended Smith algorithm

Convolutional codes have been the central part of most error-control systems in deep-space communication for many years. Almost all such applications, however, have used the restricted class of (n,1), also known as 'rate 1/n,' convolutional codes. The more general class of (n,k) convolutional codes contains many potentially useful codes, but their algebraic theory is difficult and has proved to be a stumbling block in the evolution of convolutional coding systems. In this article, the situation is improved by describing a set of practical algorithms for computing certain basic things about a convolutional code (among them the degree, the Forney indices, a minimal generator matrix, and a parity-check matrix), which are usually needed before a system using the code can be built. The approach is based on the classic Forney theory for convolutional codes, together with the extended Smith algorithm for polynomial matrices, which is introduced in this article.

Mceliece, R. J.↗

NASA NTRS2018

Extension of Space Food Shelf Life Through Hurdle Approach

The processed and prepackaged space food system is the main source of crew nutrition, and hence central to astronaut health and performance. Unfortunately, space food quality and nutrition degrade to unacceptable levels in two to three years with current food stabilization technologies. Future exploration missions will require a food system that remains safe, acceptable and nutritious through five years of storage within vehicle resource constraints. The potential of stabilization technologies (alternative storage temperatures, processing, formulation, ingredient source, packaging, and preparation procedures), when combined in hurdle approach, to mitigate quality and nutritional degradation is being assessed. Sixteen representative foods from the International Space Station food system were chosen for production and analysis and will be evaluated initially and at one, three, and five years with potential for analysis at seven years if necessary. Analysis includes changes in color, texture, nutrition, sensory quality, and rehydration ratio when applicable. The food samples will be stored at -20 C, 4 C, and 21 C. Select food samples will also be evaluated at -80 C to determine the impacts of ultra-cold storage after one and five years. Packaging film barrier properties and mechanical integrity will be assessed before and after processing and storage. At the study conclusion, if tested hurdles are adequate, formulation, processing, and storage combinations will be uniquely identified for processed food matrices to achieve a five-year shelf life. This study will provide one of the most comprehensive investigations of long duration food stability ever completed, and the achievement of extended food system stability will have profound impacts to health and performance for spaceflight crews and for relief efforts and military applications on Earth.

Cooper, M. R.↗

NASA NTRS2004

Thermo-Mechanical Properties of SiC/SiC Composites with Hybrid CVI-PIP Matrices

For long term structural service, the upper temperature capability for slurry-cast melt infiltrated (MI) SiC/SiC composites is limited to approx. 1315 C because of silicon reaction with the SiC fibers. For applications requiring material temperatures in excess of 1315 C, alternate methods of manufacturing the SiC matrices without silicon are being investigated, such as a hybrid combination of CVI and PIP. In this study, stacked fabric plies of Sylramic i-BN SiC fibers were coated with a CVI BN interface layer followed by a partial CVI SiC matrix. The remaining porosity in the SiC/SiC preforms was then infiltrated with silicon carbide matrix by PIP. Thermo-mechanical property measurements indicate that these composites are stable to 1700 C in inert environments under no load conditions for 100 h and under load conditions to 1450 C in air for 300 h. The advantages, disadvantages, and potential of this composite system for high temperature applications will be discussed.

Bhatt, R. T.↗

NASA NTRS2006

Using CO2:CO Correlations to Improve Inverse Analyses of Carbon Fluxes

Observed correlations between atmospheric concentrations of CO2 and CO represent potentially powerful information for improving CO2 surface flux estimates through coupled CO2-CO inverse analyses. We explore the value of these correlations in improving estimates of regional CO2 fluxes in east Asia by using aircraft observations of CO2 and CO from the TRACE-P campaign over the NW Pacific in March 2001. Our inverse model uses regional CO2 and CO surface fluxes as the state vector, separating biospheric and combustion contributions to CO2. CO2-CO error correlation coefficients are included in the inversion as off-diagonal entries in the a priori and observation error covariance matrices. We derive error correlations in a priori combustion source estimates of CO2 and CO by propagating error estimates of fuel consumption rates and emission factors. However, we find that these correlations are weak because CO source uncertainties are mostly determined by emission factors. Observed correlations between atmospheric CO2 and CO concentrations imply corresponding error correlations in the chemical transport model used as the forward model for the inversion. These error correlations in excess of 0.7, as derived from the TRACE-P data, enable a coupled CO2-CO inversion to achieve significant improvement over a CO2-only inversion for quantifying regional fluxes of CO2.

Palmer, Paul I.↗

NASA NTRSDate not supplied

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS2023

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

Saik Anam Siam↗

NASA NTRS1995

Sensitivity analysis for aeroacoustic and aeroelastic design of turbomachinery blades

A new method for computing the effect that small changes in the airfoil shape and cascade geometry have on the aeroacoustic and aeroelastic behavior of turbomachinery cascades is presented. The nonlinear unsteady flow is assumed to be composed of a nonlinear steady flow plus a small perturbation unsteady flow that is harmonic in time. First, the full potential equation is used to describe the behavior of the nonlinear mean (steady) flow through a two-dimensional cascade. The small disturbance unsteady flow through the cascade is described by the linearized Euler equations. Using rapid distortion theory, the unsteady velocity is split into a rotational part that contains the vorticity and an irrotational part described by a scalar potential. The unsteady vorticity transport is described analytically in terms of the drift and stream functions computed from the steady flow. Hence, the solution of the linearized Euler equations may be reduced to a single inhomogeneous equation for the unsteady potential. The steady flow and small disturbance unsteady flow equations are discretized using bilinear quadrilateral isoparametric finite elements. The nonlinear mean flow solution and streamline computational grid are computed simultaneously using Newton iteration. At each step of the Newton iteration, LU decomposition is used to solve the resulting set of linear equations. The unsteady flow problem is linear, and is also solved using LU decomposition. Next, a sensitivity analysis is performed to determine the effect small changes in cascade and airfoil geometry have on the mean and unsteady flow fields. The sensitivity analysis makes use of the nominal steady and unsteady flow LU decompositions so that no additional matrices need to be factored. Hence, the present method is computationally very efficient. To demonstrate how the sensitivity analysis may be used to redesign cascades, a compressor is redesigned for improved aeroelastic stability and two different fan exit guide vanes are redesigned for reduced downstream radiated noise. In addition, a framework detailing how the two-dimensional version of the method may be used to redesign three-dimensional geometries is presented.

Lorence, Christopher B.↗

NASA NTRS2004

Lunar and Planetary Science XXXV: Organics and Alteration in Carbonaceous Chondrites: Goop and Crud

The session "Organics and Alteration in Carbonaceous Chondrites: Goop and Crud" included the following reports:Organics on Fe-Silicate Grains: Potential Mimicry of Meteoritic Processes?; Molecular and Compound-Specific Isotopic Study of Monocarboxylic Acids in Murchison and Antarctic Meteorites; Nanoglobules, Macromolecular Materials, and Carbon Sulfides in Carbonaceous Chondrites; Evidence for Terrestrial Organic Contamination of the Tagish Lake Meteorite; Nitrogen Isotopic Imaging of Tagish Lake Carbon Globules; Microscale Distribution of Hydrogen Isotopes in Two Carbonaceous Chondrites; The Nature and Origin of Aromatic Organic Matter in the Tagish Lake Meteorite; Terrestrial Alteration of CM Chondritic Carbonate; Serpentine Nanotubes in CM Chondrites; Experimental Study of Serpentinization Reactions; Chondrule Glass Alteration in Type IIA Chondrules in the CR2 Chondrites EET 87770 and EET 92105: Insights into Elemental Exchange Between Chondrules and Matrices; Aqueous Alteration of Carbonaceous Chondrites: New Insights from Comparative Studies of Two Unbrecciated CM2 Chondrites, Y 791198 and ALH 81002 ;and A Unique Style of Alteration of Iron-Nickel Metal in WIS91600, an Unusual C2 Carbonaceous Chondrite.

Source record↗

NASA NTRS1989

Electron Spin Resonance (ESR) studies of returned comet nucleus samples

The most important objective of the Comet Nucleus Sample Returm Mission is to return samples which could reflect formation conditions and evolutionary processes in the early solar nebula. It is expected that the returned samples will consist of fine-grained silicate materials mixed with ices composed of simple molecules such as H2O, NH3, CH4 as well as organics and/or more complex compounds. Because of the exposure to ionizing radiation from cosmic-ray, gamma-ray, and solar wind protons at low temperature, free radicals are expected to be formed and trapped in the solid ice matrices. The kind of trapped radical species together with their concentration and thermal stability can be used as a dosimeter as well as a geothermometer to determine thermal and radiation histories as well as outgassing and other possible alternation effects since the nucleus material was formed. Since free radicals that are known to contain unpaired electrons are all paramagnetic in nature, they can be readily detected and characterized in their native form by the Electron Spin Resonance (ESR) method. In fact, ESR has been shown to be a non-destructive, highly sensitive tool for the detection and characterization of paramagnetic, ferromagnetic, and radiation damage centers in terrestrial and extraterrestrial geological samples. The potential use of ESR as an effective method in the study of returned comet nucleus samples, in particular, in the analysis of fine-grained solid state icy samples is discussed.

Tsay, Fun-Dow↗

NASA NTRS2020

Dual Anion-Cation Crosslinked Poly(ionic liquid) Composite Membranes for Enhanced CO2 Separation

Herein, we propose a strategy of developing novel dual anionic-cationic crosslinked poly(IL)-IL composite membranes via a photopolymerization method for enhanced CO2 separations. These are the first examples of dually photopolymerized anionic-cationic poly(IL)-IL composite systems, in which the backbones of poly(IL)s feature both pendant anions and cations without any mobile counterions unlike poly(IL) reported so far in the literature. A new type of dual photopolymerizable anionic-cationic IL (DIL) monomer having methacrylate functional group tethered with highly delocalized sulfonimide anion (–SO2–N(-)–SO2–C7H7) and a vinylimidazolium counterion ([C4(vim)](+)) was successfully synthesized and photopolymerized with four distinct amounts of free IL with a structurally analogous cation ([C4(mim)][Tf2N]) and 20 wt% PEGDA crosslinker, offering novel composite matrices. Further, the structure-property relationships as well as gas separation behaviors of the four newly developed dual anioniccationic poly(IL)-IL composite membranes were extensively characterized by FT-IR, DSC, and XRD. All of the newly developed dual anionic-cationic poly(IL)-IL composite membranes displayed outstanding permselectivites for CO2/CH4, CO2/N2, and CO2/H2 gas pairs together with reasonable CO2 permeabilities. As a result, all the dual anionic-cationic poly(IL)-IL composite membranes outperformed the common poly(IL)-IL systems in the upper bound limit plots with best CO2 permeability of 40 barrer and CO2/CH4 permselectivity of 85. This study may pave a new platform to explore countless potential poly(IL)-IL composites for selective separation of CO2 from flue gas, natural gas, and syngas streams.

Irshad Kammakakam↗