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Beta-Amino Carboxylate (BAC) non-aqueous physical solvents for enhanced CO2 separations in pre-combustion carbon capture, industrial CO 2 capture, and biogas upgrading processes

Novel beta-amino carboxylate (BAC) solvents have been synthesized and tested to efficiently capture carbon dioxide (CO 2 ) from process gas streams with CO 2 partial pressure intermediate between pre-combustion and post-combustion capture. The BAC solvents have molecular structures characterized by alkyl-substituted amides or esters containing a secondary amine functional group on the second carbon from the carbonyl carbon (referred to as the beta “β” carbon). The ester or amide functional group combined with optimal steric crowding around the amine nitrogen by proximate alkyl groups are tailored to modify the strength of CO 2 binding in the solvent. The solvents possess high CO 2 solubilities and high gas selectivity including good CO 2 /H 2 O selectivity and can be utilized for CO 2 absorption over a range of partial pressures. Due to low volatility, many of the solvents can be operated at or above ambient temperature which eliminates solvent chilling and allows regeneration using low grade waste heat. These novel solvents offer an opportunity for efficient carbon capture for a range of applications including biogas upgrading, hydrogen production, and pre-combustion carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Understanding Isomeric Effects on Properties of Aviation Fuels via a Group Contribution Method: Preprint

The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.

33 ADVANCED PROPULSION SYSTEMS

Detecting Reactive Products in Carbon Capture Polymers with Chemical Shift Anisotropy and Machine Learning

Aminopolymers are attractive sorbents for CO 2 direct air capture applications due to their high density of amine groups, which can readily react with atmospheric levels of CO 2 to form chemisorbed species. The identity of these chemisorbed species and the functional groups that form upon oxidative degradation depends on both material properties and processing conditions, forming a variety of carbonyl-type sites such as ammonium carbamates, bicarbonates, carbonates, carbamic acids, ureas, and amides. 13 C solid-state nuclear magnetic resonance (NMR) is often used to help elucidate the identity of these reacted species, but it is challenging due to the narrow chemical shift range of carbonyl sites. Herein, we demonstrate the application of a two-dimensional (2D) chemical shift anisotropy (CSA) recoupling pulse sequence (ROCSA) to obtain CSA tensor values at each isotropic chemical shift, overcoming limitations of isotropic peak resolution. CSA tensor values describe the local chemical environment and can readily differentiate between the chemisorbed and degradation products. To aid identification, we also developed a k-nearest neighbor (kNN) classification model to distinguish the functional groups via their CSA tensor parameters. This methodology was demonstrated on poly(ethylenimine) in γ-Al 2 O 3 exposed to CO 2 and showed that the chemisorbed products are ammonium carbamate and a mixed carbamate–carbamic acid species. The sample was analyzed again after desorption at 100 °C inducing mild degradation, and the remaining products were strongly bound carbamate and urea species. In conclusion, the combination of 2D CSA measurements coupled with a kNN classification model enhances the ability to accurately identify chemisorbed or degradation products in complex carbon capture materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Role of Surface Termination in the Structural and Electronic Properties of Sc$_2$CT$_\textrm{x}$ MXene

Graphene-like layered transition metal carbides, nitrides, or carbonitrides, called MXenes, obey the stoichiometric formula of M n+1 X n T x , where M is an early transition metal such as scandium (Sc), n is a natural number, X is C, N, or CN, and T x is a functional group such as –O, –F, or –OH that passivates the surface of the MXene. The electronic structure of bare Sc 2 C and functionalized Sc 2 CT x MXenes are explored by performing first-principles density functional theory (DFT) calculations. The bare Sc 2 C is metallic, but less stable than its passivated structure. The Sc 2 C MXene has an interlayer 2D electron gas not bound to Sc or C atoms but free to move, making it an electride. DFT calculations show that functionalization can open an energy gap in Sc 2 CT x MXenes. The size and type (direct versus indirect) of the bandgap vary with the functional groups, which provides a means for opening and tuning of the band gap.

DFT

Mechanically Reinforced Pseudosolid Polyelectrolyte Membranes via Layer-by-Layer Assembly for High-Performing Lithium-Metal Batteries

Ionogels are emerging as high-potential pseudosolid electrolytes for lithium-metal batteries (LMBs), leveraging their intrinsic high ionic conductivity from entrapped ionic liquid (IL) electrolytes. However, their practical application is hindered by poor mechanical strength stemming from the confinement of ILs within a polymer matrix. To address this challenge, the formation of conformal polyion coatings with functional groups is reported to be relevant to LMBs’ application on ionogels, utilizing a layer-by-layer (LbL) assembly strategy. Here, this approach significantly enhances the mechanical strength (Young's modulus and tensile strength) and electrochemical performance of ionogels, owing to the tailored interface modifications introduced by functional groups’ specific conformal polyion coatings. The core of this methodology leverages the inherent ionic structure of ionogels to enable facile interface modification through Coulombic interactions between polyanions and polycations. These conformally coated interface functionalized membranes show improved electrochemical performance when integrated with cathode materials such as LiFePO 4 (LFP) and LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) in an LMB configuration, underscoring their potential for robust, high-conductivity, pseudosolid membranes for LMB applications. These innovative pseudosolid membranes offer improved mechanical and electrochemical properties, leading to higher battery efficiency and safety, making them promising candidates for next-generation LMB technology.

25 ENERGY STORAGE

Late Metal Sandwich Catalysts for Olefin Polymerization

Polyolefins are by far the most ubiquitous industrially produced polymers and are primarily produced by early transition metal catalysts. These catalysts are not functional group tolerant, and copolymerization of ethylene and polar vinyl monomers is quite challenging. Furthermore, early metal catalysts convert ethylene to linear polyethylene, and introduction of branches requires addition of comonomers. In this Account, we describe our efforts in designing and implementing new Pd(II) and Ni(II) olefin polymerization catalysts based on mechanistic understanding of the chain growth process. Here, the original hindered nickel- and palladium-aryl-substituted diimine complexes were discovered in 1995. The key to the success of these now “classic” systems in generating high polymers rather than dimers or oligomers was realizing that incorporation of ortho-disubstituted aryl groups partially blocks the axial sites of the metal and thus retards the rate of chain transfer relative to propagation. Two key features of these late metal catalysts distinguish them from early metal complexes. First, they tolerate certain functional groups, which allows copolymerization of olefins with polar comonomers. Second, they can form a branched polymer from ethylene without the need to add α-olefin comonomers. Importantly, for nickel catalysts, branching levels can be modulated by changing reaction conditions, such as temperature and monomer pressure.

Catalysts

2D Nitrogen‐Doped Graphene Materials for Noble Gas Separation

Abstract Noble gases, notably xenon, play a pivotal role in diverse high‐tech applications. However, manufacturing xenon is an inherently challenging task, due to its unique properties and trace abundance in the Earth's atmosphere. Consequently, there is a pressing need for the development of efficient methods for the separation of noble gases. Using mild fluorographene chemistry, nitrogen‐doped graphene (GNs) materials are synthesized with abundant aromatic regions and extensive nitrogen doping within the vacancies and holes of the aromatic lattice. Due to the organized interlayer “nanochannels”, nitrogen functional groups, and defects within the two‐dimensional (2D) structures, GNs exhibits effective selectivity for Xe over Kr at low pressure. This enhanced selectivity is attributed to the stronger binding affinity of Xe to GN compared to Kr. The adsorption is governed by London dispersion forces, as revealed by theoretical calculations using symmetry‐adapted perturbation theory (SAPT). Investigation of other GNs differing in nitrogen content, surface area, and pore sizes underscores the significance of nitrogen functional groups, defects, and interlayer nanochannels over the surface area in achieving superior selectivity. This work offers a new perspective on the design and fabrication of functionalized graphene derivatives, exhibiting superior noble gas storage and separation activity exploitable in gas production technologies.

Šedajová, Veronika

Synthesis and Characterization of Methacrylamide-Based Block Random Copolymers via Amine Functionalization of Polystyrene- Block -Poly(Pentafluorophenyl Methacrylate) Toward Enhanced Amenability to Manufacturing Criteria in Nanolithography

Recent interest in manipulating the chemistry of block copolymers (BCPs) to manage the covarying properties necessary to meet manufacturing criteria in nanolithography has resulted in the development and expansion of the A-block-(B-random-C) BCP architecture, where the random block allows for the decoupling of thermodynamic and wetting properties. Previous reports of such BCPs have used click chemistry to create the desired random block, but all such instances possess additional functional groups that are susceptible to undesirable side reactions upon annealing, such as cross-linking and surface grafting. This study reports the substitution reaction of polystyrene-block-poly(pentafluorophenyl methacrylate) (PS-b-PPFMA) with primary amines. The resulting methacrylamide structure of the functionalized random block has only an amide linkage between the attached functional group and the polymer backbone, thereby omitting any sources of side reactions within the BCP. The outcomes of this report also demonstrate the enhanced thermal stability of these materials by virtue of their stable amide bonds. A range of random copolymer compositions is assessed to develop BCPs in which the random block has approximately the same surface energy as the PS block. These BCPs can self-assemble into perpendicular lamellae and are therefore promising candidates for directed self-assembly.

block copolymers

First-Principles Calculations of the Electrical Conductivity of Carbon Nanotubes Functionalized with Copper and Nitrogen: Implications for Electronics, Energy Storage, and Nanodevices

In this work, we investigate the electrical conductivity of carbon nanotubes (CNTs), with a particular focus on the effects of doping. Using first-principles-based approaches, we study the electronic structure, phonon dispersion, and electron–phonon scattering to understand the finite-temperature electrical transport properties in CNTs. Our study covers both prototypical metallic and semiconducting CNTs, with special emphasis on the influence of typical defects such as vacancies and the incorporation of copper or nitrogen, such as pyridinic N, pyrrolic N, graphitic N, and oxidized N. Our theoretical study shows significant improvements in the electrical conduction properties of copper-CNT composites, especially when semiconducting CNTs are functionalized with nitrogen. Doping is found to cause significant changes in the electronic density of states near the Fermi level, which affects the electrical conductivity. Calculations show that certain types of functional groups, such as N-pyrrolic, result in more than 30-fold increase in the conductivity of semiconducting CNTs compared to Cu-incorporated CNTs alone. For metallic CNTs, the conductivity is in agreement with existing experimental data, and our prediction of significant increases in conductivity with N-pyrrolic functional group is consistent with recent experimental results, demonstrating the effectiveness of doping in modifying conductivity. In conclusion, our study provides valuable insight into the electronic properties of doped CNTs and contributes to the development of ultrahigh conductivity CNT composites.

36 MATERIALS SCIENCE

Composition, Growth, Succession, and Function in the Cladophora Microbiome: Insights From Quantitative Stable Isotope Probing and NanoSIMS Imaging

The branching green macroalga Cladophora glomerata and its epiphytic microbiome dominate summer biomass in the Eel River, a Northern California river under Mediterranean (summer drought, winter rain) seasonality. Green Cladophora streamers proliferate in early summer, then change to yellow and then red-brown as epiphyte loads increase. Here, we characterised successional changes in epiphytic bacteria on Cladophora, examining both community composition and growth rates, using quantitative Stable Isotope Probing (qSIP) and 16S rRNA gene amplicon sequencing. The number of bacterial taxa increased with succession while growth rates peaked in the middle stage. NanoSIMS imaging confirmed high sulphur (S) concentrations in Cladophora cell walls relative to surrounding biomass, coinciding with a bloom of sulphur bacteria (bacteria that reduce or oxidise sulphur/sulphates). In general, relative abundances and growth rates were independent, indicating that either metric alone is insufficient for understanding how taxonomy and functional groups affect ecosystem processes. For instance, the relative abundance of nitrogen fixers peaked in the late summer when their relative growth rates were slowest. Such patterns may be driven by space competition limiting growth. Together, changes in abundance and relative growth rates suggest different limiting factors for different functional groups in the Cladophora microbiome at multiple successional stages.

Biological and medical sciences

Electrostatically Enhanced Buried Interface Binding of Self‐Assembled Monolayers for Efficient And Stable Inverted Perovskite Solar Cells

Inverted p‐i‐n structure perovskite solar cells (PSCs) have outperformed traditional n‐i‐p PSCs in recent years. A key advancement is the use of self‐assembled monolayers (SAMs) as hole transport layers. One class of widely used SAMs is carbazole‐based phosphonic acids. However, it is found that these SAMs lack strong binding with transparent conducting oxides (TCO) and perovskite. The weak binding strength results in suboptimal interfacial adhesion of the buried interface, which limits the device's stability. Here, interfacial binding is enhanced by increasing the dipole moment that creates a strong interfacial electric field that enhances electrostatic interactions at the TCO/perovskite interface, while incorporating tailored functional groups in SAMs to improve chemical anchoring to TCO and binding to perovskite. Specifically, the donor‐acceptor SAM molecule 4‐(7‐(4‐(bis(4‐methoxyphenyl)amino)‐2,5‐difluorophenyl)benzo[c][1,2,5]thiadiazol‐4‐yl)benzoic acid (PAFTB) is employed, which features an enhanced dipole moment along with electron‐donating and electron‐withdrawing functional groups to optimize interfacial interactions. Compared to extensively used [2‐(9H‐carbazol‐9‐yl)ethyl]phosphonic acid (2PACz), PAFTB enhances total interfacial adhesion by 2.8 times, thereby improving the thermal stability of the layer. Using this approach, PSCs are demonstrated with a certified quasi‐steady‐state power conversion efficiency of 24.9% and maintain 80% of the initial efficiency after 900 h of maximum power point tracking at 85 °C.

Interfacial adhesion

Neural Network Analysis of Nuclear Magnetic Resonance and Infrared Spectra

Nuclear magnetic resonance (NMR) spectroscopy and infrared (IR) spectroscopy are powerful chemical characterization techniques with broad general usage. However, the manual evaluation of the resulting spectra is time-consuming and requires significant expertise, preventing insights from being used in real-time applications. With recent advances in computation and artificial intelligence (AI), new tools are available for automating spectral interpretation. In this work, machine learning (ML) algorithms using 1-dimensional convolutional neural networks (CNNs) were applied to identify common functional groups from spectral information. Raw spectra were collected virtually from the Human Metabolome Database (HMDB) and National Institute of Standards and Technology (NIST) Chemistry WebBook and processed into a suitable standard. Algorithm design was tailored to best fit the nature of the problem, with built-in flexibility to accommodate relevant parameters beyond the raw spectral input, specifically solvent identity and magnetic frequency for NMR. The predictive capability of the algorithm in identifying functional groups is displayed in several examples. This methodology has been compiled into a code repository and could easily be modified to adapt alternative data sources, including other spectrum types. To mitigate overfitting, a common problem in mathematical modeling where overfamiliarity with training data produces trends that are not representative of the general data, a novel metric was developed, referred to as Accufit. Accufit includes a parameter that penalizes substantial differences in the training accuracy and the accuracy of an independent validation set. Examples are presented showing the effectiveness of Accufit in maintaining the model’s predictive capability while controlling the overfitting when used as a custom metric for hyperparameter tuning.

Sturgill, James

Probing the Mechanism of Selective Phosphate Adsorption from Wastewater Using Aqueous and Synchrotron X-ray Characterization

Ion exchange shows promise for recovering phosphate from wastewater as value-added products, but requires high phosphate selectivity to compete with conventional treatment. Hybrid anion exchange (HAIX) resins, which contain non-selective basic functional groups and selective iron oxide nanoparticles (FeOnp), can effectively remove phosphate from wastewater. However, knowledge gaps remain regarding the mechanisms of phosphate selectivity and influence of competing ions, hindering needed efforts to model adsorption dynamics and design scalable adsorption processes for varying wastewaters. To address these gaps, we integrated aqueous-phase adsorption analysis with solid-phase, synchrotron-based X-ray characterization; this integration facilitated elucidation of the distribution and speciation of iron, phosphate, and competing anions on HAIX resins. We compared a quaternary ammonium-functionalized HAIX resin (SBA) to a tertiary amine version (WBA) to determine the role of functional groups. X-ray radiography revealed differences in FeOnp speciation (goethite vs. ferrihydrite) and distribution (peripheral vs. homogeneous) between the resins, resulting in varied phosphate affinity and intraparticle diffusion resistance. Using micro-X-ray fluorescence (μ-XRF) and micro-X-ray absorption near-edge structure (μ-XANES) spectroscopy, we identified differences in where and how phosphate binds across resin types and wastewaters. Across wastewater compositions, FeOnp sites in WBA contribute more to phosphate adsorption than in SBA, possibly due to variations in Fe distribution and speciation. Phosphate adsorption densities calculated from quantitative μ-XRF maps matched those from aqueous analysis, demonstrating the effectiveness of this integrated approach. Altogether, results demonstrate the use of synchrotron-based X-ray characterization for investigating adsorption mechanisms and advance HAIX as a phosphate recovery technology from complex wastewaters.

Nutrient recovery

Bipolar Organic Cathodes for Stable and Sustainable Na‐Ion and Rechargeable Al Batteries

Bipolar organic materials have emerged as promising cathode materials for rechargeable batteries because of their high voltage and high capacity. However, they suffer from poor cyclic stability and slow reaction kinetics. In this work, we designed and synthesized two bipolar organic cathode materials, containing carbonyl (n‐type) and amine (p‐type) functional groups, as well as extended conjugation structures, for Na‐ion batteries (NIBs) and rechargeable aluminum batteries (RABs). As universal electrode materials, bipolar organic materials exhibited exceptional electrochemical performance in terms of high capacity, high voltage, long cycle life, and fast rate capability. Further, the extended conjugation structures in backbones of the bipolar organic materials facilitate the π–π stacking with graphene, playing a critical role in the high performance. Furthermore, the formation of a stable and robust NaF‐rich cathode electrolyte interphase was shown to stabilize the bipolar organic cathode in NIBs. Electrochemical kinetic measurements reveal that both functional groups undergo reversible redox reactions. Specifically, the electron transfer rate constant of the p‐type amine group is one order of magnitude higher than that of the n‐type carbonyl group. These results highlight the efficacy of developing bipolar organic materials for achieving high‐performance organic cathode in NIBs and RABs.

25 ENERGY STORAGE

Polyhalohydrins: Investigating Vicinal Functionalities by Ring-Opening of Epoxides on Polyolefins

Halohydrins are functional groups that are underexplored in polymer science. This study synthesized and examined structure–property relationships of halohydrin-functionalized polymers derived from polycyclooctene (PCOE), which was obtained via ring-opening metathesis polymerization (ROMP). The polyhalohydrins, including polychlorohydrin, polybromohydrin, and polyiodohydrin, were produced through a two-step process involving epoxidation of PCOE followed by epoxide ring-opening using hydrochloric, hydrobromic, or hydroiodic acid. These stereoirregular and regioirregular polymers are amorphous as measured by differential scanning calorimetry and X-ray scattering. Lap joint shear testing revealed an enhanced adhesive performance in polychlorohydrin and polybromohydrin, with the former demonstrating nearly three times the ultimate shear stress compared to a model polyethylene, hydrogenated PCOE. Additionally, contact angle measurements and surface free energy analysis showed an increase in hydrophilicity and polarity from iodine- to bromine- to chlorine-functionalized polyhalohydrins, aligning with trends in adhesion strength. Furthermore, these results underscore the potential of halohydrin functionalization as a versatile approach for tuning surface properties, offering new opportunities for polymer-to-polymer transformations.

Functional groups

Enhanced Ion Transport and Molecular Packing Stability in Asymmetric 2D Nanostructured π‐Conjugated Thieno[3,2‐b]Thiophene‐Based Liquid Crystal

Organic semiconductors based on liquid crystal (LC) molecules have attracted increasing interest. Here, in this work, two linear LCs based on 2,5‐bis(thien‐2‐yl)thieno[3,2‐b]thiophene (BTTT) mesogen are designed and synthesized, including BTTT/dEO3 with two symmetrically attached tri(ethylene oxide) groups and BTTT/mEO6 with one asymmetrically attached hexa(ethylene oxide) group. These two molecules have comparable functional‐group compositions but different molecular geometries, leading to their moderately different material performances. Both LCs show smectic mesophases with relatively low transition temperatures as confirmed by differential scanning calorimetry and polarized optical microscopy. A combination of experimental grazing incidence wide‐angle X‐ray scattering and molecular dynamics (MD) simulations reveals a herringbone packing motif of BTTT segments in both LCs while a smaller molecular tilt angle in BTTT/mEO6. Ionic conductivities are measured by doping LCs with different amounts of ionic dopants, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). BTTT/mEO6 shows better smectic phase stability to higher LiTFSI doping ratios. Both LCs exhibit similar ionic conductivities in the smectic phases, but BTTT/mEO6 outperforms BTTT/dEO3 by a factor of three in the amorphous phase at higher temperatures. MD simulations, performed to examine the ion solvation environment, reveal that BTTT/mEO6 is more efficient in coordinating Li‐ions and screening their interactions with TFSI‐ions which further promote ionic transport.

grazing incidence wide-angle X-ray scattering

Stability of Metal–Organic Framework-Supported Amines under Exposure to Ozone Generated from Air

Amine compounds supported on porous materials such as metal–organic frameworks (MOFs) have shown promising performance for direct air capture (DAC) due to their enhanced affinity for CO 2 . Although features such as adsorption capacity and selectivity are paramount in these composites, their long-term stability has a major impact on the operating cost of DAC systems. In this work, changes in carbon capture performance, crystallinity, porosity and chemical environment of the constituting atoms of MOF-amine composites are explored after exposure to ozone and NOx impurities generated from corona discharge applied to air. From the obtained results, the stabilities of Mg 2 (dobpdc) (dobpdc 4– = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) grafted with ethylenediamine (en), N-methylethylenediamine (men), and N,N-dimethylethylenediamine (dmen), as well as MIL-101(Cr) MOF impregnated with polyethylenimine (PEI), are compared. A negative effect in the overall CO 2 adsorption capacity is observed for all MOF composites after exposure, as well as a decrease in the adsorption step pressure of CO 2 for Mg 2 (dobpdc) amine-grafted composites, as shown via dynamic gravimetric adsorption experiments. Spectroscopic analyses indicate that oxidation of amine groups through the formation of nitro functional groups occurs as well as a decrease in the electron-donation interaction between the supported amines and the metal nodes of the MOFs.

adsorption

Microstructure of amide-functionalized polyethylenes determined by NMR relaxometry

Amidation of polyethylenes creates a range of amide-containing materials with enhanced properties, but the effect of these functional groups on the microstructure of these new materials is not known. Here we employ solid-state nuclear magnetic resonance (NMR) techniques to analyze the microstructure of amide-modified polyethylenes. While a decrease in crystallinity was observed with increasing amounts of functionalization, we found by measuring the chain mobility of the crystalline, amorphous, and interphasial regions of the polyethylenes with NMR relaxation techniques that the grafted amidyl groups partition into the rigid amorphous fraction (RAF) between the crystalline and amorphous regions. The chemical specificity of these NMR experiments creates precise assessments of the location of functional groups within the materials. Together, these insights into the microstructure and morphology of amide-containing polyethylenes lay a foundation for a deeper understanding of the structure and properties of functional polyolefins.

Haber, Shira [Lawrence Berkeley National Laborator