Evgenii O. Fetisov

Ultra-selective high-flux membranes from directly synthesized zeolite nanosheets

A zeolite with structure type MFI is an aluminosilicate or silicate material that has a three-dimensionally connected pore network, which enables molecular recognition in the size range 0.5–0.6 nm. These micropore dimensions are relevant for many valuable chemical intermediates, and therefore MFI-type zeolites are widely used in the chemical industry as selective catalysts or adsorbents. As with all zeolites, strategies to tailor them for specific applications include controlling their crystal size and shape. Nanometre-thick MFI crystals (nanosheets) have been introduced in pillared and self-pillared (intergrown) architectures, offering improved mass-transfer characteristics for certain adsorption and catalysis applications. Moreover, single (non-intergrown and non-layered) nanosheets have been used to prepare thin membranes that could be used to improve the energy efficiency of separation processes. However, until now, single MFI nanosheets have been prepared using a multi-step approach based on the exfoliation of layered MFI, followed by centrifugation to remove non-exfoliated particles. This top-down method is time-consuming, costly and low-yield and it produces fragmented nanosheets with submicrometre lateral dimensions. Alternatively, direct (bottom-up) synthesis could produce high-aspect-ratio zeolite nanosheets, with improved yield and at lower cost. Here we use a nanocrystal-seeded growth method triggered by a single rotational intergrowth to synthesize high-aspect-ratio MFI nanosheets with a thickness of 5 nanometres (2.5 unit cells). These high-aspect-ratio nanosheets allow the fabrication of thin and defect-free coatings that effectively cover porous substrates. These coatings can be intergrown to produce high-flux and ultra-selective MFI membranes that compare favourably with other MFI membranes prepared from existing MFI materials (such as exfoliated nanosheets or nanocrystals).

Structure and Phase Behavior of Mixed Self-Assembled Alkanethiolate Monolayers on Gold Nanoparticles: A Monte Carlo Study

Configurational-bias Monte Carlo (CBMC) simulations are carried out to investigate the structure and phase behavior of self-assembled monolayers consisting of equimolar alkanethiolate mixtures chemisorbed on the surface of gold nanoparticles. The simulations probe the effects of variations in the chain length, nanoparticle curvature, and exchange of alkanethiolates between nanoparticles. The TraPPE-UA force field is used for the alkanethiolates, whereas the nanoparticle is represented by gold atoms placed on the surface of a sphere. CBMC identity exchange moves are used to enhance sampling of the spatial distribution of the different ligands and to ensure that thermodynamic equilibrium is reached. At a temperature of 298 K, mixtures differing in length by four methylene units exhibit some degree of local segregation. In contrast, the hexanethiolate/tetradecanethiolate mixture yields Janus-like arrangement when the ligands are confined to a single nanoparticle but global demixing when the ligands are allowed to distribute between two nanoparticles.

Supersaturated calcium carbonate solutions are classical

Ions and ion pairs are the species that lead to CaCO3 nucleation. Mechanisms of CaCO3 nucleation from solutions that depend on multistage pathways and the existence of species far more complex than simple ions or ion pairs have recently been proposed. Herein, we provide a tightly coupled theoretical and experimental study on the pathways that precede the initial stages of CaCO3 nucleation. Starting from molecular simulations, we succeed in correctly predicting bulk thermodynamic quantities and experimental data, including equilibrium constants, titration curves, and detailed x-ray absorption spectra taken from the supersaturated CaCO3 solutions. The picture that emerges is in complete agreement with classical views of cluster populations in which ions and ion pairs dominate, with the concomitant free energy landscapes following classical nucleation theory.

First-Principles Molecular Dynamics Study of a Deep Eutectic Solvent: Choline Chloride/Urea and Its Mixture with Water

First-principles molecular dynamics simulations in the canonical ensemble at temperatures of 333 and 363 K and at the corresponding experimental densities are carried out to investigate the behavior of the 1:2 choline chloride/urea (reline) deep eutectic solvent and its equimolar mixture with water. Analysis of atom-atom radial and spatial distribution functions and of the H-bond network reveals the microheterogeneous structure of these complex liquid mixtures. In neat reline, the structure is governed by strong H-bonds of the trans- and cis-H atoms of urea to the chloride ion. In hydrous reline, water competes for the anions, and the H atoms of urea have similar propensities to bond to the chloride ions and the O atoms of urea and water. The vibrational spectra exhibit relatively broad peaks reflecting the heterogeneity of the environment. Although the 100 ps trajectories allow only for a qualitative assessment of transport properties, the simulations indicate that water is more mobile than the other species and its addition also fosters faster motion of urea.

First-Principles Monte Carlo Simulations of Reaction Equilibria in Compressed Vapors

Predictive modeling of reaction equilibria presents one of the grand challenges in the field of molecular simulation. Difficulties in the study of such systems arise from the need (i) to accurately model both strong, short-ranged interactions leading to the formation of chemical bonds and weak interactions arising from the environment, and (ii) to sample the range of time scales involving frequent molecular collisions, slow diffusion, and infrequent reactive events. Here we present a novel reactive first-principles Monte Carlo (RxFPMC) approach that allows for investigation of reaction equilibria without the need to prespecify a set of chemical reactions and their ideal-gas equilibrium constants. We apply RxFPMC to investigate a nitrogen/oxygen mixture at T = 3000 K and p = 30 GPa, i.e., conditions that are present in atmospheric lightning strikes and explosions. The RxFPMC simulations show that the solvation environment leads to a significantly enhanced NO concentration that reaches a maximum when oxygen is present in slight excess. In addition, the RxFPMC simulations indicate the formation of NO2 and N2O in mole fractions approaching 1%, whereas N3 and O3 are not observed. The equilibrium distributions obtained from the RxFPMC simulations agree well with those from a thermochemical computer code parametrized to experimental data.

Understanding the Reactive Adsorption of H2S and CO2 in Sodium-Exchanged Zeolites

Purifying sour natural gas streams containing hydrogen sulfide and carbon dioxide has been a long-standing environmental and economic challenge. In the presence of cation-exchanged zeolites, these two acid gases can react to form carbonyl sulfide and water (H2 S+CO2 ⇌H2 O+COS), but this reaction is rarely accounted for. In this work, we carry out reactive first-principles Monte Carlo (RxFPMC) simulations for mixtures of H2 S and CO2 in all-silica and Na-exchanged forms of zeolite beta to understand the governing principles driving the enhanced conversion. The RxFPMC simulations show that the presence of Na+ cations can change the equilibrium constant by several orders of magnitude compared to the gas phase or in all-silica beta. The shift in the reaction equilibrium is caused by very strong interactions of H2 O with Na+ that reduce the reaction enthalpy by about 20 kJ mol-1 . The simulations also demonstrate that the siting of Al atoms in the framework plays an important role. The RxFPMC method presented here is applicable to any chemical conversion in any confined environment, where strong interactions of guest molecules with the host framework and high activation energies limit the use of other computational approaches to study reaction equilibria.

DFT study of dihydrogen addition to molybdenum π-heteroaromatic complexes: a prerequisite step for the catalytic hydrodenitrogenation process

The range of molybdenum hydride complexes that are sought to participate in the important catalytic hydrodenitrogenation process (HDN) of nitrogen containing polycyclic aromatic hydrocarbons were evaluated by DFT studies. The previously synthesized stable (η6-quinoline)Mo(PMe3)3 complex 1N, in which molybdenum is bonded to the heterocyclic ring, was chosen as a model. The hydrogenation of the quinone heterocycle, which was postulated as the initial step in the overall HDN reaction, is found to occur via three consecutive steps of the oxidative addition of dihydrogen to Mo in 1N. Successive transfer of hydrogen atoms from the metal to the heterocycle leads to the ultimate formation of the tetrahydrido molybdenum intermediate Mo(PMe3)4H413 and 2,2,3,3-tetrahydroquinoline C9H11N 14. All the involved intermediates and transition states have been fully characterized by DFT. This computational modeling of the hydrogenation of quinoline, as a part of extended HDN catalytic processes, provides a fundamental understanding of such mechanisms.

C2 adsorption in zeolites: in silico screening and sensitivity to molecular models

Efficient separation of ethane and ethylene has been a long-standing challenge for the chemical industry. In this study, we use molecular modeling to identify zeolite and zeotype frameworks that have the potential to be the next-generation solution for the separation of these C2 compounds. Using two different united-atom versions of the transferable potentials for phase equilibria (TraPPE) force field, the zeolitic structures in the database of the International Zeolite Association are screened for the separation of ethane and ethylene. A detailed analysis, with regards to accessibility of favorable sites and sensitivity to molecular models (also considering the explicit-hydrogen TraPPE model for ethane), is carried out on the top-performing structures. This study provides insights on the performance and limitations of molecular models for predicting mixture adsorption in zeolites.