A COMPUTATIONAL STUDY OF METAL-ORGANIC FRAMEWORKS OXIDATIVE DEGRADATION FOR THE DESIGN OF TUNABLE SMART DRUG DELIVERY SYSTEMS

55-5

The Role of Culture in Business Transaction:Implications for Success in Trans-Geographical Settings

Non-oxidative dehydroaromatization of methane (MDA) is a promising catalytic process for direct valorization of natural gas to liquid hydrocarbons. The application of this reaction in practical technology is hindered by a lack of understanding about the mechanism and nature of the active sites in benchmark zeolite-based Mo/ZSM-5 catalysts, which precludes the solution of problems such as rapid catalyst deactivation. By applying spectroscopy and microscopy, it is shown that the active centers in Mo/ZSM-5 are partially reduced single-atom Mo sites stabilized by the zeolite framework. By combining a pulse reaction technique with isotope labeling of methane, MDA is shown to be governed by a hydrocarbon pool mechanism in which benzene is derived from secondary reactions of confined polyaromatic carbon species with the initial products of methane activation

A COMPUTATIONAL STUDY OF METAL-ORGANIC FRAMEWORKS OXIDATIVE DEGRADATION FOR THE DESIGN OF TUNABLE SMART DRUG DELIVERY SYSTEMS

55-5

Revealing Main Reaction Paths to Olefins and Aromatics in Methanol-to-Hydrocarbons over H-ZSM-5 by Isotope Labeling

The nature of hydrocarbon pool (HCP) intermediates in the methanol-to-hydrocarbons (MTH) process has been thoroughly investigated, especially for BEA- and CHA-type zeolite catalysts like H-β and H-SAPO-34. Herein, we further reveal the dynamic mechanistic details of the MTH process over the H-ZSM-5 catalyst at 400 °C, based on the dual-cycle mechanism and HCP in this medium-pore zeolite. Application of switching sequences of 13C-labeled and unlabeled methanol pulses over a model H-ZSM-5 catalyst combined with on-line MS analysis and a recently reported technique called “fast scanning-pulse GC analysis” provides a direct and quantitative insight into the MTH reactions under quasi-steady-state conditions. The transient product responses showed the almost instant formation of hydrocarbons upon a small pulse of methanol, followed by secondary formation of light aromatics via HCP decomposition and olefin alkylation-dealkylation, especially in a long catalyst bed when methanol is quickly consumed in the initial reaction zone in the catalyst bed. The isotopic analysis of typical aliphatic C3+ product responses after switching 13C-methanol pulses to the unlabeled methanol pulses showed a fast isotope scrambling in the formation of C3+ species. MS analysis of the light aromatics indicates a complete consecutive but slower isotope incorporation process of 12C into 13C-aromatics. Results provide direct experimental confirmation of the kinetically preferred olefin-based cycle over the aromatic-based cycle. The sequential isotopic incorporation strongly suggests that the paring reaction pathway through aromatic ring contraction and re-expansion steps is operative. In the appearance of aromatics upon pulsing methanol over larger catalyst beds, four processes are directly discerned, involving the displacement of adsorbed species by formed water, isotope incorporation yielding directly labeled and unlabeled products through the paring mechanism and direct aromatization, and HCP conversion through secondary reactions.</p

Computational chemistry of zeolite catalysis

This chapter presents an introductory overview of the basic concepts, power, capabilities, and limitations of modern quantum-chemical techniques for studying reactivity and chemical properties of zeolites. The subjects discussed here will include the methodological aspects of computational chemistry crucial for modeling extended chemical systems as well as recent relevant examples of application of computational methodologies for developing new concepts of zeolite reactivity. Emphasis will be made on the use of computational approaches for unraveling molecular-level phenomena underlying catalytic properties of zeolites

Dry reforming of methane to test passivation stability of Ni/ Al₂O₃ catalysts

Catalyst passivation refers to the formation of a protective oxide layer on the active metal particles that prevents their oxidation when exposed to air. Common passivation procedures, when applied to Ni/ Al2O3 catalysts, typically result in a significant decrease of the overall Ni surface area and, accordingly, the catalytic activity. Nevertheless, passivation and reactivation is an attractive pre-treatment option for this system. Ni/ Al2O3 typically requires reduction temperatures much higher than the desired reaction temperature, whereas reactivation of passivated samples is a low-temperature reduction. This can be used to avoid temperature limitations of existing systems. Thus, more insight into the passivation process of this system is desirable. In this work we analyzed the impact of passivation on the catalytic performance of a series of Ni/ Al2O3 catalysts in dry reforming of methane. This approach allows for the elimination of scale effects during passivation. We show that changes in conversion and especially of the coke content can be used to track sintering of Ni particles. These metrics allows to identify an adverse effects of catalyst passivation in excess O2, which gives rise to rapid local overheating and, accordingly, Ni sintering even when operating at tens of mg catalyst scale. Our study demonstrates that such problems are not limited to scaling issues and sufficient care must be taken even on a lab-scale when passivating Ni/ Al2O3 catalysts

Model-based evaluation and data requirements for parallel kinetic experimentation and data-driven reaction identification and optimization

Recently there has been growing interest in implementing the high-throughput approach to access the dynamics of chemical processes across different fields. With an ever-increasing amount of data provided by high-throughput experimentation, the development of fully-integrated workflows becomes crucial. These workflows should combine novel experimental tools and interpretation methods to convert the data into valuable information. To design feasible data-driven workflows, it is necessary to estimate the value of information and balance it with the number of experiments and resources required. Basing this kind of workflow on actual physical models appears to be a more feasible strategy as compared to data-extensive empirical statistical methods. Here we show an algorithm that constructs and evaluates kinetic models of different complexity. The algorithm facilitates the evaluation of the experimental data quality and quantityrequirements needed for the reliable discovery of the rates driving the corresponding chemical models. The influence of the quality and quantity of data on the obtained results was indicated by the accuracy of the estimates of the kinetic parameters. We also show that this method can be used to find correct reaction scenarios directly from simulated kinetic data with little to no overfitting. Well-fitting models for theoretical data can then be used as a proxy for optimizing the underlying chemical systems. Taking real physical effects into account, this approach goes beyond: we show that with the kinetic models, one can make a direct, unbiased, quantitative connection between kinetic data and the reaction scenario.ChemE/Inorganic Systems Engineerin

Solvent-mediated outer-sphere CO2 electro-reduction mechanism over the Ag111 surface

The electrocatalytic CO2 reduction reaction (CO2RR) is one of the key technologies of the clean energy economy. Molecular-level understanding of the CO2RR process is instrumental for the better design of electrodes operable at low overpotentials with high current density. The catalytic mechanism underlying the turnover and selectivity of the CO2RR is modulated by the nature of the electrocatalyst, as well as the electrolyte liquid, and its ionic components that form the electrical double layer (EDL). Herein we demonstrate the critical non-innocent role of the EDL for the activation and conversion of CO2 at a high cathodic bias for electrocatalytic conversion over a silver surface as a representative low-cost model cathode. By using a multiscale modeling approach we demonstrate that under such conditions a dense EDL is formed, which hinders the diffusion of CO2 towards the Ag111 electrocatalyst surface. By combining DFT calculations and ab initio molecular dynamics simulations we identify favorable pathways for CO2 reduction directly over the EDL without the need for adsorption to the catalyst surface. The dense EDL promotes homogeneous phase reduction of CO2via electron transfer from the surface to the electrolyte. Such an outer-sphere mechanism favors the formation of formate as the CO2RR product. The formate can undergo dehydration to CO via a transition state stabilized by solvated alkali cations in the EDL.ChemE/Inorganic Systems Engineerin