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At least 379 records · Page 21

Diffusion and Solvation Dynamics of Ions in Water: Beyond the Brownian Approximation

The coupled dynamics of ions and water molecules in their first hydration shell impact a variety of processes including ion diffusion, selective ion transport in water-filled nanopores, and the kinetics of ion-pairing, ion adsorption, and metal-ligand binding reactions. In this work, we study these coupled dynamics for alkali metals (Li, Na, K, Rb, Cs), alkaline Earth metals (Mg, Ca, Sr, Ba), and chloride through the lens of their dependence on ion isotopic mass. Results are validated against previous measurements of the isotopic mass-dependence of ion diffusion coefficients in water and previous ab initio calculations of ion high-frequency dynamics in water. We find that the vibrational power spectra of ions in water consistently exhibit either two or three peaks, i.e., ions have several rattling frequencies within their solvations shells as previously reported for a subset of the species examined here. These frequencies have different sensititivies to isotopic mass that may serve as signatures of ion solvation processes (such as the tendency of ions to orient their first-shell water molecules) and that also may relate to Hofmeister-like effects including the relative affinity of different metals for ribonucleic acid (RNA).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Co-Adsorption of Carbon Dioxide on Zeolite 13X in the Presence of Preloaded Water

Background: Carbon Dioxide removal is a key aspect of Life Support for long-duration missions - Need to improve Mass, Power, and Volume of systems; Cabin air has three major constituents - Oxygen and Nitrogen, Carbon dioxide (CO2), Water Vapor; The mechanism for strong CO2 adsorption in zeolites (and many sorbents) is also the same mechanism for H2O - Water vapor is selectively adsorbed over CO2.

Cmarik, Gregory E.↗

Carbon Nanostructures in Biological Sensors for Space and Terrestrial Applications

Biosensing devices comprised of carbon nanotubes and nanofibers have been developed for astronaut crew point-of-care. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using carbon nanotube and carbon nanofiber electrodes for biomedical applications. First, a 3x3 electrode device, with each electrode containing 40,000 carbon nanofiber nanoelectrodes was fabricated on silicon using traditional microfabrication processing. The device was demonstrated as a multiplexed immunosensor for simultaneous, label-free detection of cardiac troponin-I, C-reactive protein and myoglobin. Antibodies specific to cardiac troponin-I, C-reactive protein and myoglobin were covalently bound to the CNF surface and were characterized using electrochemical impedance spectroscopy and differential pulse voltammetry. Each step of the modification process resulted in changes in resistance to charge transfer due to the changes at the electrode surface upon antibody immobilization and binding to the specific cardiac protein. The real-time label free detection of the three cardiac markers from pure components and mixtures was demonstrated with high sensitivity, down to 0.2 ng/mL, and good selectivity. Detection in human blood serum did not present false positives from non-specific protein adsorption. More recently, this detection scheme has been applied to inkjet printed carbon nanotube electrodes on Kapton and paper. Printed devices have several unique advantages including simple and inexpensive fabrication. The results demonstrate that these sensors can serve a miniaturized, low cost device for detection of proteins in complex mixtures making this platform a good candidate for early stage diagnosis of myocardial infarction. Future inkjet printed devices can be fabricated have the added advantage in their suitability to be manufactured in an in-space, microgravity environment.

carbon nanotubes↗

Carbon Nanomaterials for Biosensing Applications

Biosensing devices comprised of carbon nanotubes and nanofibers have been developed for astronaut crew point-of-care. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using carbon nanotube and carbon nanofiber electrodes for biomedical applications. First, a 3x3 electrode device, with each electrode containing 40,000 carbon nanofiber nanoelectrodes was fabricated on silicon using traditional microfabrication processing. The device was demonstrated as a multiplexed immunosensor for simultaneous, label-free detection of cardiac troponin-I, C-reactive protein and myoglobin. Antibodies specific to cardiac troponin-I, C-reactive protein and myoglobin were covalently bound to the CNF surface and were characterized using electrochemical impedance spectroscopy and differential pulse voltammetry. Each step of the modification process resulted in changes in resistance to charge transfer due to the changes at the electrode surface upon antibody immobilization and binding to the specific cardiac protein. The real-time label free detection of the three cardiac markers from pure components and mixtures was demonstrated with high sensitivity, down to 0.2 ng/mL, and good selectivity. Detection in human blood serum did not present false positives from non-specific protein adsorption. More recently, this detection scheme has been applied to inkjet printed carbon nanotube electrodes on Kapton and paper. Printed devices have several unique advantages including simple and inexpensive fabrication. The results demonstrate that these sensors can serve a miniaturized, low cost device for detection of proteins in complex mixtures making this platform a good candidate for early stage diagnosis of myocardial infarction. Future inkjet printed devices can be fabricated have the added advantage in their suitability to be manufactured in an in-space, microgravity environment.

carbon nanotubes↗

Atomically Dispersed Dual‐Metal Site Catalysts for Enhanced CO 2 Reduction: Mechanistic Insight into Active Site Structures

Abstract Carbon‐supported nitrogen‐coordinated single‐metal site catalysts (i.e., M−N−C, M: Fe, Co, or Ni) are active for the electrochemical CO 2 reduction reaction (CO 2 RR) to CO. Further improving their intrinsic activity and selectivity by tuning their N−M bond structures and coordination is limited. Herein, we expand the coordination environments of M−N−C catalysts by designing dual‐metal active sites. The Ni‐Fe catalyst exhibited the most efficient CO2RR activity and promising stability compared to other combinations. Advanced structural characterization and theoretical prediction suggest that the most active N‐coordinated dual‐metal site configurations are 2N‐bridged (Fe‐Ni)N 6 , in which FeN 4 and NiN 4 moieties are shared with two N atoms. Two metals (i.e., Fe and Ni) in the dual‐metal site likely generate a synergy to enable more optimal *COOH adsorption and *CO desorption than single‐metal sites (FeN 4 or NiN 4 ) with improved intrinsic catalytic activity and selectivity.

Li, Yi↗

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

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

74 ATOMIC AND MOLECULAR PHYSICS↗

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗

Multimodal Nanoscale Mapping of Local Structure and CO 2 Adsorption in Metal–Organic Frameworks

Diamine functionalization of the metal−organic framework Mg 2 (dobpdc) (dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) significantly enhances its selectivity for CO 2 capture from flue gases and air. The structure and CO 2 capacity of such materials are typically assessed using bulk techniques that rely on averaging signal over large ensembles of unit cells, obscuring local heterogeneities, such as variations in CO 2 occupancy across individual nanocrystals. To resolve this limitation, we demonstrate a multimodal, nanoscale characterization of Mg 2 (dobpdc) appended with 1,3-diaminopropane. By employing recently developed characterization techniques at progressively smaller length scales, we uncover insights from correspondingly smaller populations of unit cells. First, we use parallel-beam 3D electron diffraction (3D ED) to identify a prominent expansion in lattice parameters upon desorption of CO 2 , as observed at the level of single nanocrystals. Second, we use convergent-probe 4D scanning transmission electron microscopy (4D-STEM) to quantify associated differences in lattice strain as a function of gas loading and diamine appending. These measurements sample small subvolumes within individual nanocrystals. Finally, we apply infrared scattering scanning near-field optical microscopy (IR s- SNOM) to confirm variable CO 2 chemisorption across adsorption sites at the surface of single nanocrystals. This multimodal, multiscale approach allows us to map heterogeneity within individual nanocrystals. Collectively, these findings emphasize the importance of local, nanoscale characterization of metal−organic frameworks in revealing previously unresolvable features that impact their performance.

Karstens, Sarah L. [University of California, Berk↗

Gold-in-copper at low *CO coverage enables efficient electromethanation of CO 2

The renewable-electricity-powered CO 2 electroreduction reaction provides a promising means to store intermittent renewable energy in the form of valuable chemicals and dispatchable fuels. Renewable methane produced using CO 2 electroreduction attracts interest due to the established global distribution network; however, present-day efficiencies and activities remain below those required for practical application. Here we exploit the fact that the suppression of *CO dimerization and hydrogen evolution promotes methane selectivity: we reason that the introduction of Au in Cu favors *CO protonation vs. C-C coupling under low *CO coverage and weakens the *H adsorption energy of the surface, leading to a reduction in hydrogen evolution. We construct experimentally a suite of Au-Cu catalysts and control *CO availability by regulating CO 2 concentration and reaction rate. This strategy leads to a 1.6× improvement in the methane:H 2 selectivity ratio compared to the best prior reports operating above 100 mA cm -2 . We as a result achieve a CO 2 -to-methane Faradaic efficiency (FE) of (56 ± 2)% at a production rate of (112 ± 4) mA cm -2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A modular chemo-selective oxygen production unit to deliver oxygen for advanced combustion systems

Commercial oxygen generation technologies deploy either cryogenic air separation or vacuum pressure swing adsorption (VPSA). These technologies can provide nearly pure oxygen but are only economically viable at oxygen production rates of 100-7,000 tonnes/day. The state-of-theart cryogenic air separation plants are impending the theoretical limits of thermodynamic efficiency but cannot be scaled down to cater future needs. Therefore, there is great incentive to develop a new approach for oxygen separation that can accommodate the upcoming demands. Our proposed research approach address to find novel methodologies to provide energy efficient modular O 2 on demand systems for modular gasification and other applications. Small scale modular systems for O 2 production offer certain benefits including enhanced energy efficiency, reduced operating costs and flexibility to tailor location specific needs. Our hypothesis is that a small modular system could be engineered using solvent-based capture and thermal release of oxygen, to enable “oxygen on demand” for any combustion-related technology.

42 ENGINEERING↗

The Impact of 5-Hydroxymethylfurfural (HMF)-Metal Interactions on the Electrochemical Reduction Pathways of HMF on Various Metal Electrodes

5-Hydroxymethylfurfural (HMF), which can be derived from lignocellulosic biomass, is an important platform molecule that can be used to produce valuable biofuels and polymeric materials. Electrochemical reduction of HMF is of great interest as it uses water as the hydrogen source and achieves desired reduction reactions at room temperature and ambient pressure. Hydrogenation and hydrogenolysis are two important reactions for reductive HMF conversion. Therefore, elucidating key characteristics of electrocatalysts that govern the selectivity for hydrogenation and hydrogenolysis is critical in rationally developing efficient and selective electrocatalysts. Here in this study, combined experimental and computational investigations are used to demonstrate how the adsorption energy of HMF on metal surfaces and the resulting changes in the intramolecular bond lengths of adsorbed HMF directly impact the reduction pathways of HMF. These results make it possible to rationally understand a general trend in the behaviors observed when using various metal electrodes for HMF reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Role of the Support in Acetic Acid Hydrodeoxygenation Selectivity on Pt/TiO2

To produce drop-in quality biofuels following the thermochemical conversion of biomass via catalytic fast pyrolysis (CFP), hydrodeoxygenation (HDO) reactions can be performed to remove excess oxygen and create a more stable bio-oil product. HDO reactions involve co-feeding the CFP vapor-phase product and H2 gas over bi-functional catalysts, such as noble-metal catalysts supported on reducible metal oxides (e.g., Pt/TiO2). Recent model-compound studies, focusing on important classes of species in the CFP vapor mixture, have sought to determine the role of the various Pt/TiO2 actives sites (i.e., Pt-metal, TiO2-support, Pt-TiO2-interfacial sites) in producing the observed desired deoxygenation and undesired decarboxylation/decarbonylation products. One important class of compounds in the CFP vapor-phase product is carboxylic acids (e.g., acetic acid). Prior experimental work on acetic acid HDO (AA-HDO) found that Pt/C and Pt/TiO2 catalysts favored the formation of undesired C-C and desired C-O bond-dissociation products; however, the fundamental surface chemistry driving this shift in selectivity has not been established. This presentation employs atomic-scale modeling to determine, through comparisons of adsorption and reaction energetics, how Pt-metal, Pt-TiO2-interface, and interfacial-vacancy sites catalyze the competing reaction pathways for AA-HDO. Our analysis indicates that hydroxyl vacancies at the Pt-TiO2 interface are critical for lowering barriers for C-O bond-cleavage steps, such that they become favorable/competitive with respect to C-C bond-dissociation steps.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Case Study: Calorimetry

This chapter presents the use of adsorption microcalorimetry to study acid-base catalysis over mixed metal oxides. Understanding the acid-base properties of catalysts is of paramount importance for steering product selectivity in a wide variety of catalytic industrial processes. In particular, catalytic conversion of biomass into biofuels and chemicals demands comprehensive understanding of the acid-base properties of the catalyst to selectively convert functional groups. Herein, the use of probe molecules to measure the strength and density of acid and basic sites on mixed metal oxide surfaces is introduced. Further, the challenges when characterizing mixed metal oxides, presenting surface reconstruction, are explained. An example displays how combining adsorption calorimetry with ab initio calculations explains the activation of a reactant on the surface of a mixed metal oxide. Acid-base catalysis over nanoshapes is studied to unveil that different nanoshapes lead to different extents of surface reconstruction, which ultimately affect acid-base catalysis. The use of steady-state isotopic transient kinetic analysis (SSITKA), in combination with adsorption microcalorimetry, unveils that surface reconstruction of a set of perovskites impacts the density of active sites to a greater extent than the intrinsic reactivity of the active site. At the end of this chapter, fundamental insights into catalyst transient behavior during isomerization of n-butane, and the reaction mechanism for conversion of 4-methylpentan-2-ol, are presented.

Polo Garzon, Felipe↗

Zirconium‐Based Metal–Organic Frameworks with Free Hydroxy Groups for Enhanced Perfluorooctanoic Acid Uptake in Water

Perfluorooctanoic acid (PFOA) is a highly recalcitrant organic pollutant, and its bioaccumulation severely endangers human health. While various methods are developed for PFOA removal, the targeted design of adsorbents with high efficiency and reusability remains largely unexplored. Here, in this work, the rational design and synthesis of two novel zirconium‐based metal‒organic frameworks (MOFs) bearing free ortho ‐hydroxy sites, namely noninterpenetrated PCN‐1001 and twofold interpenetrated PCN‐1002, are presented. Single crystal analysis of the pure ligand reveals that intramolecular hydrogen bonding plays a pivotal role in directing the formation of MOFs with free hydroxy groups. Furthermore, the transformation from PCN‐1001 to PCN‐1002 is realized. Compared to PCN‐1001, PCN‐1002 displays higher chemical stability due to interpenetration, thereby demonstrating an exceptional PFOA adsorption capacity of up to 632 mg g −1 (1.53 mmol g −1 ), which is comparable to the reported record values. Moreover, PCN‐1002 shows rapid kinetics, high selectivity, and long‐life cycles in PFOA removal tests. Solid‐state nuclear magnetic resonance results and density functional theory calculations reveal that multiple hydrogen bonds between the free ortho ‐hydroxy sites and PFOA, along with Lewis acid‐base interaction, work collaboratively to enhance PFOA adsorption.

36 MATERIALS SCIENCE↗

Solution and Active Site Speciation Drive Selectivity for Electrocatalytic Reactive Carbon Capture in Diethanolamine over Ni–N–C Catalysts

Direct conversion of captured forms of carbon, or reactive carbon capture (RCC), presents an opportunity to reduce the energy intensity and cost of direct CO 2 utilization from dilute sources. While amine-based sorbents effectively capture CO 2 , their use for RCC presents numerous challenges with typical pure metal catalysts used for electrochemical CO 2 reduction (CO 2 R). Here, using both theory and experiments, we find that Ni–N–C single atom catalysts are effective for RCC conversion to CO using a diethanolamine sorbent, in contrast to pure metal catalysts. Computational analysis reveals that RCC can proceed directly through direct reduction of the sorbent-CO 2 adduct or indirectly by C–N bond breaking facilitating CO 2 adsorption and subsequent reduction. We find that the latter mechanism is most prevalent at low overpotentials where we experimentally observe RCC selectivity. We also find experimentally that the rate of CO production for RCC with Ni–N–C catalysts can exceed pure bicarbonate solutions at intermediate sorbent concentration (0.1–0.5 M DEA) under dilute (10–25%) streams of CO 2 at low overpotentials. The coordination environment of Ni sites and the solution speciation influence their RCC activity, with changes in protonation to coordinating N/C atoms resulting in changing the RCC mechanism and consequent activity. In situ X-ray absorption spectroscopy and computational analysis reveal restructuring under RCC conditions due to hydrogen coadsorption with DEA that limits the stability of Ni–N–C catalysts. This work highlights the importance of carefully controlling the catalyst and solution environment to achieve active and stable RCC electrocatalysis.

Chemistry↗

Heavy Versus Light Lanthanide Selectivity for Graphene Oxide Films is Concentration Dependent

Rare earths are important materials in various technologies such as catalysis and optoelectronics. Graphene oxide (GO) is a promising material for separation applications, including the isolation of lanthanides from complex mixtures. Previous works using fatty acid monolayers have demonstrated preferential heavy versus light lanthanide adsorption, which has been attributed to differences in lanthanide ion size. In this work, we used interfacial X-ray fluorescence measurements to reveal that GO thin films at the air/water interface have no lanthanide selectivity for dilute subphases. However, at high subphase concentrations, ~8 times more Lu is adsorbed than La. By comparing the GO results with an ideal monolayer with a carboxylic acid headgroup, arachidic acid (AA), we demonstrate that the number of Lu ions adsorbed to GO is significantly higher than the number expected to compensate for the surface charge. Vibrational sum frequency generation (SFG) spectroscopy results on both GO thin films and AA monolayers reveal a red-shifted SFG signal in the OH region, which we attribute to partial dehydration of the adsorbed ions and carboxylic acid headgroups. Liquid surface X-ray reflectivity data show that the GO thin film structure does not significantly change between the very dilute and concentrated subphases. We speculate that the functional groups of both GO and AA facilitate cation dehydration, which is essential for ion adsorption. Heavy lanthanide Lu has stronger ion–ion correlations that can overcome the electrostatic repulsion between cations at higher concentrations compared to light lanthanide La, meaning GO and AA can exhibit apparent overcharge with Lu. Lastly, the layered structure of the GO films and reactive chemical nature of GO itself can accommodate ion adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites

Zeolites are one of the most widely used materials in the chemical industry due to their nanometer-sized pores that can adsorb and react upon molecules selectively. With hundreds of known framework topologies and hundreds of thousands of computationally predicted structures, the ability to rapidly predict zeolite performance allows researchers to prioritize their efforts on the most promising structures for a given application. Although the accuracy of forcefield-based atomistic simulations has advanced significantly in the past two decades, these simulations can be computationally expensive, especially for long-chain, complex molecules. Here, we present ZeoNet, a representation learning framework using convolutional neural networks (ConvNets) and 3D volumetric representations for predicting adsorption in zeolites. ZeoNet was trained on the task of predicting Henry's constants for adsorption, k H , of n-octadecane in more than 330 000 known and predicted zeolite materials. Employing a 3D grid based on the distances to solvent-accessible surfaces, a volumetric representation that can be generated efficiently, the best-performing ZeoNet achieved a correlation coefficient r 2 = 0.977 and a mean-squared error MSE = 3.8 in ln k H , which corresponds to an error of 9.3 kJ mol -1 in adsorption free energy. In comparison, a model based on hand-designed geometric features has values of r 2 = 0.783 and MSE = 35.7. ZeoNet is also relatively efficient and can process ≈8 structures per second on an Nvidia RTX 2080TI GPU, orders of magnitude faster than forcefield-based simulations. A systematic analysis was conducted to investigate how the choice of ConvNet architectures, the linear dimension (L) and spatial resolution (Δd) of the distance grids, batch size, optimizer, and learning rate impact the model performance. We found that ConvNets based on the ResNet architecture offer the best tradeoff between expressiveness and efficiency. The performance for all models reaches a plateau at L = 30–45 Å and depends less sensitively on grid resolution, with a small benefit around Δd = 0.30–0.45 Å. Finally, saliency maps were visualized to identify which regions of the materials contributed the most to model predictions. It was found, interestingly, that the predictions are driven primarily by the accessible pore volume rather than the region occupied by the framework atoms.

36 MATERIALS SCIENCE↗