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At least 343 records · Page 19

Evaluation of Density-Functional Tight-Binding Methods for Simulation of Protic Molecular Ion Pairs

In this work, we benchmark the accuracy of the density-functional tight-binding (DFTB) method, namely the long-range corrected second-order (LC-DFTB2) and third-order (DFTB3) models, for predicting energetics of imidazolium-based ionic liquid (IL) ion pairs. We compare the DFTB models against popular density functionals such as LC-ωPBE and B3LYP, using ab initio domain-based local pair-natural orbital coupled cluster (DLPNO-CC) energies as reference. Calculations were carried out in the gas phase, as well as in aqueous solution using implicit solvent methods. We find that the LC-DFTB2 model shows excellent performance in the gas phase and agrees well with reference energies in implicit solvent, often outperforming DFTB3 predictions for complexation energetics. Our study identifies a range of opportunities for use of the LC-DFTB method and quantifies its sensitivity to protonation states and the types of chemical interactions between ion pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Water content of carbon dioxide at hydrate forming conditions

There is an interest to ensure sub-saturated water content in lines containing carbon dioxide in applications such as enhanced oil recovery and carbon sequestration, to reduce risks of hydrate blockage and corrosion. The water content of carbon dioxide at various temperatures and pressures has been measured in the past, but there is no consistent set of measurements that could be used for carbon dioxide storage and transportation design work. The solubility of water in a carbon dioxide rich gas phase at hydrate forming conditions was measured in this work. Pressures ranged from 12.06 to 29.30 bar along two isotherms, 1 °C and -7 °C, all within the gaseous carbon dioxide and hydrate stability zone. For the first time in these types of measurements, the solid phase was also characterized and confirmed to be carbon dioxide hydrate via X-ray computed tomography, simultaneous with water content measurements of the gas phase. Once carbon dioxide hydrate conversion had reached a maximum value (65% estimated by X-ray computed tomography), the equilibrium water content was measured. Prior to reaching this maximum carbon dioxide hydrate conversion, the water content in carbon dioxide was observed to decrease as liquid water converted to carbon dioxide hydrate. Furthermore, this slow conversion to hydrate, metastability of the hydrate phase, or unexpected phases may be responsible for the large discrepancy between prior data sets for similar carbon dioxide water content measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of gas purity on backgrounds of collision reaction cell-equipped MC-ICP-MS

The advent of multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) instruments equipped with collision reaction cells (CRCs) facilitates interference removal/mitigation via online gas phase separations. This approach has proven effective for high intensity ion beams measured on Faraday collectors; however, it has been observed that introduction of gas in the CRC can result in significant background signals relative to the more sensitive ion counters. These backgrounds hinder use of these instruments for low level concentration and isotopic ratio measurements when employing a reaction gas. Here, this work directly evaluates the effect of gas purity on backgrounds of CRC-MC-ICP-MS instruments. Introducing high-purity research grade O 2 (99.999%) into the CRC produces complex background spectra with intensities >10 4 cps observed at most masses across the measured mass range (7-300 m / z ). Some features of the observed spectra (i.e., positive mass defects) can be attributed to molecular compounds comprised of significant hydrogen. Additionally, some specific molecular species can be identified (i.e., MoO x H y + ) and appear to be derived from molybdenum rods comprising the CRC. Further purifying the gas reduces the intensity of these backgrounds by several orders of magnitude, to <10 2 cps in many cases, and reduces complexity of the resulting spectra. This reduction in background appears to be in part driven by removal of impurities (i.e., H 2 O) from the gas. This work demonstrates that additional purification of reaction gases prior to introduction into the CRC significantly reduces backgrounds detected, potentially expanding the utility of CRC-MC-ICP-MS for making low level measurements using inline gas phase ion separations.

Schlieder, Tyler D. [Pacific Northwest National La↗

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗

Direct Study of Changes in Catalyst Structure-Kinetic Properties During Redox Transitions

The Temporal Analysis of Products (TAP) pulse response methodology is a transient technique that provides the time resolution needed to deconvolve reaction steps from the complex networks typical in industrial catalytic processes. Traditionally, TAP measurements observe gas phase dynamics at the reactor exit but lack direct measurements of changes in the catalyst itself. Recently, a new operando technique was developed that couples gas phase transients to dynamic changes in metal centers with the precise TAP methodology for nanomole titration. Using an industrial CrOx/Al2O3 catalyst used for propane dehydrogenation, we demonstrate the capabilities of this unique device to reveal key catalytic processes: 1) total propane oxidation not associated with chromia centers, 2) reduction of Cr6+ to Cr3+ correlated with selective product formation, and 3) subsequent carbon accumulation. By utilizing incremental pulsing in a diffusion-only transport regime, the spectrokinetic device allows us to resolve detailed changes in catalyst structure, composition, and kinetic function that are otherwise indistinguishable in conventional operando devices. The unification of the TAP methodology with time-resolved spectroscopic measurements offers new and unique insights into the complex kinetic phenomena regulated by solid catalyst surfaces.

03 - NATURAL GAS↗

Direct study of changes in catalyst structure-kinetic properties during redox transitions using a new time-resolved technique

Direct study of changes in catalyst structure-kinetic properties during redox transitions using a new time-resolved technique The Temporal Analysis of Products (TAP) pulse response methodology1 is a transient technique offering the time scale needed to deconvolve many reaction steps from the complex network typical to industrial catalytic processes. The traditional TAP measurement observes the gas phase dynamic response but, hereto now, has been devoid of any direct measurement of change in the catalyst itself. The development of an operando technique that couples gas phase transient kinetics to dynamic metal centers and surface species is presented. Significance Unification of the TAP methodology with time-resolved spectroscopic measurement can offer unprecedented insight into the complex kinetic phenomena regulated by the solid catalyst.

03 - NATURAL GAS↗

Effect of ammonia addition on suppressing soot formation in methane co-flow diffusion flames

Due to issues surrounding carbon dioxide emissions from carbon-containing fuels, there is growing interest in ammonia (NH 3 ) as an alternative combustion fuel. One attractive method of burning NH 3 is to co-fire it with hydrocarbons, such as natural gas, and in this case soot formation is possible. To begin understanding the influence of NH 3 on soot formation when co-fired with hydrocarbons, soot volume fractions and mole fractions of gas-phase species were computationally and experimentally interrogated for CH 4 flames with up to 40% NH 3 by volumetric fuel fraction. Mole fractions of gas-phase species, including C 2 H 2 and C 6 H 6 , were measured with on-line electron impact mass spectrometry, and soot volume fractions were obtained via color-ratio pyrometry. The simulations employed a detailed chemical mechanism developed for capturing nitrogen interactions with hydrocarbons during combustion. The results are compared to findings in N 2 -CH 4 flames, in order to separate thermal and dilution effects from the chemical influence of NH 3 on soot formation. Experimentally, C 2 H 2 concentrations were found to decrease slightly for the NH 3 -CH 4 flames relative to N 2 -CH 4 flames, and a stronger suppression of C 6 H 6 was found for NH 3 relative to N 2 additions. The measured results show a strong suppression of soot with the addition of NH 3 , with soot concentrations reduced by over a factor of 10 with addition of up to 20% or more NH 3 by mole fraction. The model satisfactorily captured relative differences in maximum centerline C 2 H 2 , C 6 H 6 , and soot concentrations with addition of N 2 , but was unable to match measured differences in NH 3 -CH 4 flames. Furthermore, these results highlight the need for an improved understanding of fuel-nitrogen interactions with higher hydrocarbons to enable accurate models for predicting particulate emissions from NH 3 /hydrocarbon combustion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Role of the Solvent in the Condensed-Phase Dynamics and Identity of Chemical Bonds: The Case of the Sodium Dimer Cation in THF

When a solute molecule is placed in solution, is it acceptable to presume that its electronic structure is essentially the same as in the gas phase? In this paper, we address this question from a simulation perspective for the case of the sodium dimer cation (Na 2 + ) molecule in both liquid Ar and liquid tetrahydrofuran (THF). In previous work, we showed that when local specific interactions between a solute and solvent are energetically on the order of a hydrogen bond, the solvent can become part of the chemical identity of the solute. Here, using mixed quantum/classical molecular dynamics simulations, we see that for the Na 2 + molecule, solute--solvent interactions lead to two stable, chemically-distinct coordination states (Na(THF) 4 -Na(THF) 5 + and Na(THF) 5 -Na(THF) 5 + ) that are not only stable themselves as gas-phase molecules but that also have a completely new electronic structure with important implications for the excited-state photodissociation of this molecule in the condensed phase. Furthermore, we show through a set of comparative classical simulations that treating the solute's bonding electron explicitly quantum mechanically is necessary to understand both the ground-state dynamics and chemical identity of this simple diatomic molecule; even use of the quantum-derived potential of mean force is insufficient to describe the behavior of the molecule classically. Lastly, we calculate the results of a proposed transient hole-burning experiment that could be used to spectroscopically disentangle the presence of the different coordination states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calibration of the liquid argon ionization response to low energy electronic and nuclear recoils with DarkSide-50

DarkSide-50 has demonstrated the high potential of dual-phase liquid argon time projection chambers in exploring interactions of WIMPs in the GeV=c 2 mass range. The technique, based on the detection of the ionization signal amplified via electroluminescence in the gas phase, allows us to explore recoil energies down to the sub-keV range. We report here on the DarkSide-50 measurement of the ionization yield of electronic recoils down to ~180 eV er , exploiting 37 Ar and 39 Ar decays, and extrapolated to a few ionization electrons with the Thomas-Imel box model. Further, we present a model-dependent determination of the ionization response to nuclear recoils down to ~500 eV nr , the lowest ever achieved in liquid argon, using in situ neutron calibration sources and external datasets from neutron beam experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transferable Water Potentials Using Equivariant Neural Networks

Machine learning interatomic potentials (MLIPs) have emerged as a technique that promises quantum theory accuracy for reduced cost. It has been proposed [J. Chem. Phys. 2023, 158, 084111] that MLIPs trained on solely liquid water data cannot accurately transfer to the vapor–liquid equilibrium while recovering the many-body decomposition (MBD) analysis of gas-phase water clusters. This suggests that MLIPs do not directly learn the physically correct interactions of water molecules, limiting transferability. In this work, we show that MLIPs using equivariant architecture and trained on 3200 liquid water structures reproduces liquid-phase water properties (e.g., density within 0.003 g/cm 3 between 230 and 365 K), vapor–liquid equilibrium properties up to 550 K, the MBD analysis of gas-phase water cluster up to six-body interactions, and the relative energy and the vibrational density of states of ice phases. We show that potentials developed using equivariant MLIPs allow transferability for arbitrary phases of water that remain stable in nanosecond long simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Density functional theory (DFT) study of UF 6 hydrolysis: reaction pathways, spectroscopy, and chemical kinetics

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the gas-phase reaction mechanism and associated chemical kinetics are poorly understood. During the performance period we undertook development of a state-of-the-art ab initio gas-phase chemical kinetics simulation workflow to model the hydrolysis of uranium hexafluroride (UF 6 ). In doing so, we addressed several outstanding issues in the theoretical treatment of uranium-containing systems. At the outset it was unclear how to generate accurate estimates of kinetic and thermodynamic data for U-containing chemical reactions. Generation of such data has been made routine. Prior to our work, the literature associated with UF 6 hydrolysis were disparate and inaccurate. This body of work provides a modern and comprehensive theoretical assessment of the reaction mechanism, molecular clustering towards deposition, and chemical kinetics. New methodological implementations and software integrations resulting from this work are also highlighted. As much as possible, our predictions were validated against experimental data including particle morphologies, vibrational spectroscopy, atomization enthalpies, and kinetic rate constants. Nevertheless, we were unable to reconcile kinetic measurements with high-accuracy simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Synthesis of multicomponent oxygen evolution reaction coatings via block copolymer templating with vapor- and solution-phase precursors

Porous mixed transition metal oxide heterostructures are promising electrocatalysts due to their high surface area. However, achieving conformal multicomponent oxide coatings with controlled nanoscale architectures remains challenging. Here, we report a synthesis strategy that integrates solution-based swelling infiltration (SBI) with gas-phase sequential infiltration synthesis (SIS) in a block copolymer template to fabricate porous, high-surface-area, conformal mixed-oxide electrocatalytic coatings. In this approach, a PS75-P4VP25 block copolymer (BCP) film is first infiltrated with transition metal acetylacetonate precursors via SBI, followed by exposure to gas phase precursors of ZnO via SIS process. Thermal annealing of the infiltrated BCP films converts them into all-inorganic Fe–ZnO, Fe–Co–ZnO, and Fe–Ni–ZnO coatings. Electrochemical testing on 70 nm thick conformal coatings demonstrates promising oxygen evolution reaction (OER) activity in alkaline media, with mass-specific current densities up to 1.0 × 10 5 mA/g at an overpotential of 330 mV (vs. RHE) at ultralow loading (~0.005 g/cm 2 ). Among the compositions, Fe–Co–ZnO and amorphous Fe–Ni–ZnO show the best OER performance, delivering current densities of 2.00 and 3.04 mA/cm 2 , respectively, compared to 1.52 mA/cm 2 for Fe–ZnO.. This work establishes SBI–SIS as a versatile route for fabricating nm-thin, high-performance multicomponent oxide heterostructures on cost-efficient supports, enabling efficient catalyst utilization in electrochemical energy conversion application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective

Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.

collisions↗

Directly imaging the cooling flow in the Phoenix cluster

In the centres of many galaxy clusters, the hot (approximately 10 7 kelvin) intracluster medium can become dense enough that it should cool on short timescales. However, the low measured star formation rates in massive central galaxies and the absence of soft X-ray lines from the cooling gas suggest that most of this gas never cools. This is known as the cooling flow problem. The latest observations suggest that black hole jets are maintaining the vast majority of gas at high temperatures. A cooling flow has yet to be fully mapped through all the gas phases in any galaxy cluster. Here we present observations of the Phoenix cluster using the James Webb Space Telescope to map the [Ne vi] λ 7.652-μm emission line, enabling us to probe the gas at 10 5.5 kelvin on large scales. These data show extended [Ne vi] emission that is cospatial with the cooling peak in the intracluster medium, the coolest gas phases and the sites of active star formation. Taken together, these imply a recent episode of rapid cooling, causing a short-lived spike in the cooling rate, which we estimate to be 5,000–23,000 solar masses per year. As a result, these data provide a large-scale map of gas at temperatures between 10 5 kelvin and 10 6 kelvin in a cluster core, and highlight the critical role that black hole feedback has in not only regulating cooling but also promoting it.

79 ASTRONOMY AND ASTROPHYSICS↗

Reaction process involving capillary condensation within a microporous catalyst

Described herein is a catalytic reaction process including introducing one or more gas-phase reactants into a reactor comprising a microporous catalyst having a pore size less than or equal to 2 nm and adjusting the temperature and/or the pressure of the reactor such that one or more of the gas-phase reactants condense within the micropores of the catalyst thereby causing the catalytic reaction to take place in a liquid phase. Additionally, a process for engineering defects on a carboxylate-based metal organic framework (MOF) catalyst is described. The process includes providing a carboxylate-based MOF catalyst; and heating the carboxylate-based MOF catalyst in an inert gas atmosphere at temperatures between about 150° C. and about 900° C.

Aguirrezabal, Iker↗

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗

Liquid Sorption-Enhanced Haber–Bosch Process

The use of a liquid sorbent in a traditional Haber-Bosch process enables significant improvements in energy efficiency and potential cost savings for arguably the most important chemical process on the planet. The approach presented in this report employs an incompressible liquid sorbent that absorbs and releases ammonia (NH 3 ) under specific conditions. To achieve this, we investigate reactions of ammonia and pure phosphoric acid (H 3 PO 4 , PA), which rapidly neutralize to form an equilibrated solution of monoammonium phosphate (MAP) and diammonium phosphate (DAP) that functions as a reversible and regenerable sorbent. Through intimate contact of the gas-phase Haber-Bosch reaction mixture with this liquid absorbent, complete equilibrium uptake may be achieved in an appropriately sized separator, and facile separation occurs through the use of independent liquid and gas phases. Following depressurization and release of the ammonia product, only the incompressible fluid needs to be repressurized and returned to the reactor. This study documents proof-of-concept absorption and desorption experiments carried out in 75 mL batch reactors, predominantly charged with precise MAP and DAP mixtures that equilibrate at process-relevant temperatures and pressures. We then assemble the first thermodynamic relationships that underlie this advantaged separation strategy, validated by reactive force field (ReaxFF) interatomic potential simulations, and benchmarked with traditional separation routes via process modeling and technoeconomic analysis. The scale of energy consumption in the century-old Haber-Bosch process is massive, and the elegant liquid sorption approach reported here offers opportunities to enhance its energy efficiency for the next frontier of ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗