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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Variable Inhibition of Nitrous Oxide Reduction in Denitrifying Bacteria by Different Forms of Methanobactin

Aerobic methanotrophic activity is highly dependent on copper availability, and methanotrophs have developed multiple strategies to collect copper. Specifically, when copper is limiting (ambient concentrations < 1 μM), some methanotrophs produce and secret a small modified peptide (< 1,300 Da) termed methanobactin (MB) that binds copper with high affinity. As MB is secreted into the environment, other microbes that require copper for their metabolism may be inhibited as MB may make copper unavailable; e.g., inhibition of denitrifiers as complete conversion nitrate to dinitrogen involves multiple enzymes, some of which are copper-dependent. Of key concern is inhibition of the copper-dependent nitrous oxide reductase (NosZ), the only known enzyme capable of converting nitrous oxide (N 2 O) to dinitrogen. Herein, we show that different forms of MB differentially affect copper uptake and N2O reduction by Pseudomonas stutzeri strain DCP-Ps1 (that expresses clade I NosZ) and Dechloromonas aromatica strain RCB (that expresses clade II NosZ). Specifically, in the presence of MB from Methylocystis sp. strain SB2 (SB2-MB), copper uptake and nosZ expression were more significantly reduced than in the presence of MB from Methylosinus trichosporium OB3b (OB3b-MB). Further, N2O accumulation increased more significantly for both P. stutzeri strain DCP-Ps1 and D. aromatica strain RCB in the presence of SB2-MB versus OB3b-MB. These data illustrate that copper competition between methanotrophs and denitrifying bacteria can be significant and that the extent of such competition is dependent on the form of MB that methanotrophs produce.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Targeting the Spike Receptor Binding Domain Class V Cryptic Epitope by an Antibody with Pan-Sarbecovirus Activity

Novel therapeutic monoclonal antibodies (MAbs) must accommodate comprehensive breadth of activity against diverse sarbecoviruses and high neutralization potency to overcome emerging variants. Here, in this study, we report the crystal structure of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain (RBD) in complex with MAb WRAIR-2063, a moderate-potency neutralizing antibody with exceptional sarbecovirus breadth, that targets the highly conserved cryptic class V epitope. This epitope overlaps substantially with the spike protein N-terminal domain (NTD) -interacting region and is exposed only when the spike is in the open conformation, with one or more RBDs accessible. WRAIR-2063 binds the RBD of SARS-CoV-2 WA-1, all variants of concern (VoCs), and clade 1 to 4 sarbecoviruses with high affinity, demonstrating the conservation of this epitope and potential resiliency against variation. We compare structural features of additional class V antibodies with their reported neutralization capacity to further explore the utility of the class V epitope as a pan-sarbecovirus vaccine and therapeutic target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evolution of carbapenemase activity in the class C β-lactamase ADC-1

Antibiotic resistance in bacteria poses a significant threat to public health. Among dozens of available antimicrobial agents, carbapenems are used as drugs of choice for the treatment of serious infections caused by pathogens resistant to other antibiotics. However, their usefulness has been severely compromised due to the emergence and wide spread of carbapenem-resistant clinical isolates worldwide. High-level resistance to carbapenems in bacteria is mediated by the production of β-lactamases from three molecular classes, A, B, and D, but not by class C enzymes. In this study, we selected a triple mutant of the intrinsic class C Acinetobacter-derived cephalosporinase ADC-1 (ADC-1 TM ) that confers high-level resistance to the carbapenems meropenem, ertapenem, and doripenem. Kinetic experiments demonstrated that the apparent binding affinity, along with the acylation and deacylation rates, were all improved for the mutant enzyme. X-ray crystallography, molecular docking, and molecular dynamics simulations revealed that the amino acid substitutions in ADC-1 TM produce significant changes in the enzyme active site architecture and binding mode of the carbapenem ertapenem. These changes allow for better positioning of a deacylating water for nucleophilic attack, thus explaining the significantly improved rate of ertapenem deacylation by ADC-1 TM . In this study, we showed for the first time that a class C β-lactamase can produce high-level resistance to carbapenem antibiotics, which underlines the potential for enzymes of this class to evolve such resistance and could further exacerbate the problem of antibiotic resistance in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Resistance to oxyimino-cephalosporins conferred by an alternative mechanism of hydrolysis by the Acinetobacter -derived cephalosporinase-33 (ADC-33), a class C β-lactamase present in carbapenem-resistant Acinetobacter baumannii (CR Ab )

ABSTRACT Antimicrobial resistance inAcinetobacter baumanniiis partly mediated by chromosomal class C β-lactamases, theAcinetobacter-derived cephalosporinases (ADCs). Recently, a growing number of emerging variants were described, expanding this threat. Consistent with other β-lactamases, one of the main areas of variance exists in the Ω-loop region near the site of cephalosporin binding. Interestingly, a common alanine duplication (Adup) is found in this region. Herein, we studied specific Adup variants expressed in a uniformEscherichia coligenetic background that demonstrated high-level resistance to multiple oxyimino-cephalosporins. For ceftolozane and ceftazidime, the Adup ADCs significantly increased levels of resistance (minimum inhibitory concentration [MIC] ≥ 512 µg/mL and MIC ≥ 1,024 µg/mL, respectively). These observations were consistent with the increasedk cat /K M for ceftazidime. For cefiderocol, three Adup variants exhibited increased MICs and increasedk cat /K M for this compound. Timed electrospray ionization mass spectrometry demonstrated stable cephalosporin:ADC adducts with ADC-30 (non-Adup), but not with ADC-33 (Adup), consistent with turnover. The X-ray crystal structure of Adup variant ADC-33 in complex with ceftazidime was determined (1.57 Å resolution) and suggests that increased turnover is facilitated by conformational changes (shift in Tyr221 and orientation of the oxyimino portion of the R1 side chain) and repositioning of water in the active site. These changes appear to favor substrate-assisted catalysis as an alternative mechanism to base-assisted catalysis. These studies also provide unprecedented insight into the mechanism underlying oxyimino-cephalosporin hydrolysis by expanded-spectrum ADC β-lactamases and possibly other class C β-lactamases, which is of critical importance to future drug design. IMPORTANCE The characterization of emergingAcinetobacter-derived cephalosporinase (ADC) variants is necessary to understand the increasing resistance to β-lactam antibiotics inAcinetobacterspp. In this study, cefiderocol retains effectiveness against ADC variants with and without an Ω-loop alanine duplication (Adup). However, the presence of the Adup appears to introduce loop flexibility and structural alterations resulting in increased resistance and steady-state turnover of larger cephalosporins. Further characterization provides unprecedented insight into the mechanism of cephalosporin hydrolysis by ADC β-lactamases and supports a concomitant increase in ADC structural flexibility and cephalosporin affinity that leads to more efficient hydrolysis. In addition, the crystal structure of ADC-33 in complex with ceftazidime is consistent with a substrate-assisted catalysis mechanism. The structural differences in the ADC-33 active site leading to ceftazidime catalysis provide a better understanding of β-lactamase Adup variants and open important opportunities for future drug design and development.

Microbiology↗
DOE OSTI2023

Antibiotic that inhibits trans -translation blocks binding of EF-Tu to tmRNA but not to tRNA

trans-Translation is conserved throughout bacteria and is essential in many species. High-throughput screening identified a tetrazole-based trans-translation inhibitor, KKL-55, that has broad-spectrum antibiotic activity. A biotinylated version of KKL-55 pulled down elongation factor thermo-unstable (EF-Tu) from bacterial lysates. Purified EF-Tu bound KKL-55 in vitro with a K d = 2 µM, confirming a high-affinity interaction. An X-ray crystal structure showed that KKL-55 binds in domain 3 of EF-Tu, and mutation of residues in the binding pocket abolished KKL-55 binding. RNA-binding assays in vitro showed that KKL-55 inhibits binding between EF-Tu and transfer-messenger RNA (tmRNA) but not between EF-Tu and tRNA. These data demonstrate a new mechanism for the inhibition of EF-Tu function and suggest that this specific inhibition of EF-Tu•tmRNA binding is a viable target for antibiotic development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A shift between mineral and nonmineral sources of iron and sulfur causes proteome-wide changes in Methanosarcina barkeri

ABSTRACT Iron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS − ). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS 2 ). Recently, paradigm-shifting studies indicate that Fe and S in FeS 2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS 2 , as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS 2 , Fe(II)/HS − , or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS − , either as a component of the growth medium [Fe(II)/HS − ] or generated through reduction of FeS 2 , were likely a major factor underpinning these phenotypic differences. IMPORTANCE The methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Maturation experiments reveal bias in the chemistry of fossil melanosomes

Fossil melanosomes are a major focus of paleobiological research because they can inform on the original coloration, phylogenetic affinities, and internal anatomy of ancient animals. Recent studies of vertebrate melanosomes revealed tissue-specific trends in melanosome-metal associations that can persist in fossils. In some fossil vertebrates, however, melanosomes from all body regions are enriched only in Cu, suggesting diagenetic overprinting of original chemistry. We tested this hypothesis using laboratory experiments on melanosomes from skin and liver of the African clawed frog Xenopus laevis. After maturation in Cu-rich media, the metal chemistry of melanosomes from these tissues converged toward a common composition, and original differences in Cu oxidation state were lost. Elevated Cu concentrations and a pervasive Cu(II) signal are likely indicators of diagenetically altered melanosomes. These results provide a robust experimental basis for interpretating the chemistry of fossil melanosomes.

58 GEOSCIENCES↗
DOE OSTI2021

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Deep neural networks (DNNs) have achieved state-of-the-art performance across a variety of traditional machine learning tasks, e.g., speech recognition, image classification, and segmentation. The ability of DNNs to efficiently approximate high-dimensional functions has also motivated their use in scientific applications, e.g., to solve partial differential equations and to generate surrogate models. In this paper, we consider the supervised training of DNNs, which arises in many of the above applications. We focus on the central problem of optimizing the weights of the given DNN such that it accurately approximates the relation between observed input and target data. Devising effective solvers for this optimization problem is notoriously challenging due to the large number of weights, nonconvexity, data sparsity, and nontrivial choice of hyperparameters. To solve the optimization problem more efficiently, we propose the use of variable projection (VarPro), a method originally designed for separable nonlinear least-squares problems. Our main contribution is the Gauss--Newton VarPro method (GNvpro) that extends the reach of the VarPro idea to nonquadratic objective functions, most notably cross-entropy loss functions arising in classification. These extensions make GNvpro applicable to all training problems that involve a DNN whose last layer is an affine mapping, which is common in many state-of-the-art architectures. In our four numerical experiments from surrogate modeling, segmentation, and classification, GNvpro solves the optimization problem more efficiently than commonly used stochastic gradient descent (SGD) schemes. Finally, GNvpro finds solutions that generalize well, and in all but one example better than well-tuned SGD methods, to unseen data points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2022

Conservative and Accurate Solution Transfer Between High-Order and Low-Order Refined Finite Element Spaces

Here, in this paper, we introduce general transfer operators between high-order and low-order refined finite element spaces that can be used to couple high-order and low-order simulations. Under natural restrictions on the low-order refined space we prove that both the high-to-low-order and low-to-high-order linear mappings are conservative, constant preserving, and high-order accurate. While the proof holds for affine geometries, numerical experiments indicate that the results hold for more general curved meshes. We present several numerical results confirming our analysis and demonstrate the utility of the new mappings in the context of adaptive mesh refinement and conservative multidiscretization coupling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses

Here, this work proposes a framework for large-scale stochastic derivative-free optimization (DFO) by introducing STARS, a trust-region method based on iterative minimization in random subspaces. This framework is both an algorithmic and theoretical extension of a random subspace derivative-free optimization (RSDFO) framework, and an algorithm for stochastic optimization with random models (STORM). Moreover, like RSDFO, STARS achieves scalability by minimizing interpolation models that approximate the objective in low-dimensional affine subspaces, thus significantly reducing per-iteration costs in terms of function evaluations and yielding strong performance on largescale stochastic DFO problems. The user-determined dimension of these subspaces, when the latter are defined, for example, by the columns of so-called Johnson-Lindenstrauss transforms, turns out to be independent of the dimension of the problem. For convergence purposes, inspired by the analyses of RSDFO and STORM, both a particular quality of the subspace and the accuracies of random function estimates and models are required to hold with sufficiently high, but fixed, probabilities. Using martingale theory under the latter assumptions, an almost sure global convergence of STARS to a first-order stationary point is shown, and the expected number of iterations required to reach a desired first-order accuracy is proved to be similar to that of STORM and other stochastic DFO algorithms, up to constants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Role of Functionalized Conducting Polymer Binders in Improving Power Density and Cycle Life of Lithium-Sulfur Batteries

Lithium-Sulfur batteries are promising as the next-generation of low-cost, high-energy rechargeable batteries. However, the commercialization of this battery has been limited by poor rate capability and cycle life. To improve the performance of Li-S cells, we have investigated the role of two n-dopable conducting polymers, N2200 and N2200-OE, as binders for the sulfur cathode. The electron and ion transport properties of these polymer binders, along with their strong affinity for polysulfides, results in significantly enhanced performance compared to cells with the traditional insulating PVDF binder. The role of these conducting polymer binders in enhancing the performance of the cells is analyzed using impedance spectroscopy, shuttle current measurements, conductivity measurements, UV–vis spectroscopy, GIWAXS studies and post-cycling analysis of the anodes. The conducting polymer binders reduce the cell impedance by a factor of four leading to a marked improvement in rate capability. The shuttling of the polysulfides and the formation of insoluble sulfides at the anode is curtailed by the interaction of the polysulfides with the backbone of the polymer binders, leading to an impressive capacity retention of 82% after 500 cycles. These studies demonstrate the benefit of tailored polymer binders at the sulfur electrode in addressing the limitations of lithium-sulfur batteries.

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

Development and Applications of an eReaxFF Force Field for Graphitic Anodes of Lithium-Ion Batteries

Graphene is one of the most promising materials for lithium-ion battery anodes due to its superior electronic conductivity, high surface area for lithium intercalation, fast ionic diffusivity and enhanced specific capacity. A reliable description of many battery processes requires an explicit description of electrochemical interactions involving electrons. A detailed atomistic modeling of electronic conduction and non-zero voltage simulations of graphitic materials require the inclusion of an explicit electronic degree of freedom. To enable large length- and time-scale simulations of electron conduction in graphitic anodes, we developed an eReaxFF force field concept describing graphitic materials with an explicit electron. The newly developed force field, verified against quantum chemistry-based data describing, amongst others, electron affinities and equation of states, reproduces the qualitative behavior of electron conductivity in pristine and imperfect graphitic materials at different applied temperatures and voltages. In addition, excess electron localization near a defect site estimated from eReaxFF simulations agree quite well with the corresponding density functional theory calculations. Here, our eReaxFF simulations show the initiation of lithium-metal-plating driven by electron transfer from the graphene surface to the exposed lithium ions demonstrating the method’s potential for studying lithium-graphene interactions with explicit electrons and explain many unresolved electrode and electrode-electrolyte interface processes.

25 ENERGY STORAGE↗
DOE OSTI2022

Investigating the Influence of Ni, ZrO 2 , and Y 2 O 3 from SOFC Anodes on Siloxane Deposition

Siloxanes, as a type of impurity in biogas, can poison the Ni-YSZ anode of SOFCs. However, the influence of individual components of the anode, such as Ni, ZrO 2 , and Y 2 O 3 , on the siloxane deposition process has not been investigated extensively. In this study, Ni, ZrO 2 , and Y 2 O 3 pellets were exposed to H 2 + N 2 + H 2 O + D4 (octamethylcyclotetrasiloxane, 2.5 ppmv) and H 2 + N 2 + D4 (2.5 ppmv siloxane) gas mixtures at 750 °C to investigate their affinity and tolerance for siloxane degradation. Surface morphology analysis and electrochemical analysis including electrochemical impedance spectroscopy (EIS), related distribution of relaxation times (DRT) analysis and equivalent circuit modeling with complex nonlinear least square (CNLS) fitting were conducted. Here, a microstructure parameter—tortuosity factor to porosity ratio $\tau /\varepsilon $ calculated by diffusion polarization resistance was utilized for siloxane deposition evaluation. After comparing pellets surface morphology changes before and after experiments and $\tau /\varepsilon $ change following the contamination, Ni is considered as a major factor in siloxane deposition reactions in Ni-YSZ anode.

25 ENERGY STORAGE↗
DOE OSTI2024

Development of Mixed Matrix Membranes by Using NH 2 ‐Functionalized UiO‐66 and [APTMS][AC] Ionic Liquid for the Separation of CO 2

The ever‐escalating CO 2 concentration in the atmosphere calls for accelerated development and deployment of carbon capture processes to reduce emissions. Mixed matrix membranes (MMMs), which are fabricated by incorporating the beneficial properties of highly selective inorganic fillers into a polymer matrix, have exhibited significant progress and the ability to enhance the performance of a membrane for gas separation. In this research, an amine‐based ionic liquid (IL) [APTMS][AC] was prepared, which has greater CO 2 affinity and greater solubility due to its amine moiety. The metal–organic framework (MOF) UiO‐66 with a multidimensional crystalline structure was used as a filler due to its appropriate porosity and tunable properties, and it was functionalized with NH 2 . MOFs were further modified with an IL to prepare UiO‐66@IL and UiO‐66‐NH 2 @IL, and MMMs incorporating each MOF were fabricated with the polymer Pebax‐1657. All the prepared membranes and MOFs were characterized to predict their separation efficiency. Several characterization techniques, namely, FTIR spectroscopy, XRD, and SEM, were used to successfully synthesize UiO‐66@IL and UiO‐66‐NH 2 @IL composites and confirmed proper dispersion and excellent polymer‒filler compatibility at filler loadings ranging from 0 to 30 wt.%. The separation performances were investigated, and the results showed that the incorporation of RTIL with the highly crystalline structure and large surface area of UiO‐66 enhanced the separation efficiency of the membrane. The permeability of CO 2 for all fabricated membranes continuously increased with increasing filler concentration, wherein the permeability was comparatively high for the UiO‐66‐NH 2 MMMs. The CO 2 /CH 4 selectivity improved by 35%, 54%, and 60%, respectively, for UiO‐66@IL, UiO‐66‐NH 2 , and UiO‐66‐NH 2 @IL MMMs compared to simple UiO‐66 for CO 2 /CH 4 and by 28%, 36%, and 63%, respectively, for CO 2 /N 2 , with an increase in filler loading in the MMMs.

Khalid, Hafiza Mamoona (ORCID:0009000135165855)↗