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Garashchuk, Sophya

Publications and source records attributed to Garashchuk, Sophya.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Theoretical Examination of the Hydroxide Transport in Cobaltocenium-Containing Polyelectrolytes

Polymers incorporating cobaltocenium groups have received attention as promising components of anion-exchange membranes (AEMs), exhibiting a good balance of chemical stability and high ionic conductivity. In this work, we analyze the hydroxide diffusion in the presence of cobaltocenium cations in an aqueous environment based on the molecular dynamics of model systems confined in one dimension to mimic the AEM channels. In order to describe the proton hopping mechanism, the forces are obtained from the electronic structure computed at the density-functional tight-binding level. We find that the hydroxide diffusion depends on the channel size, modulation of the electrostatic interactions by the solvation shell, and its rearrangement ability. Hydroxide diffusion proceeds via both the vehicular and structural diffusion mechanisms with the latter playing a larger role at low diffusion coefficients. The highest diffusion coefficient is observed under moderate water densities (around half the density of liquid water) when there are enough water molecules to form the solvation shell, reducing the electrostatic interaction between ions, yet there is enough space for the water rearrangements during the proton hopping. Furthermore, the effects of cobaltocenium separation, orientation, chemical modifications, and the role of nuclear quantum effects are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Metal‐Organic Framework (MOF)‐Based Multifunctional Cargo Vehicle for Reactive‐Gas Delivery and Catalysis

Abstract The efficient delivery of reactive and toxic gaseous reagents to organic reactions was studied using metal‐organic frameworks (MOFs). The simultaneous cargo vehicle and catalytic capabilities of several MOFs were probed for the first time using the examples of aromatization, aminocarbonylation, and carbonylative Suzuki–Miyaura coupling reactions. These reactions highlight that MOFs can serve a dual role as a gas cargo vehicle and a catalyst, leading to product formation with yields similar to reactions employing pure gases. Furthermore, the MOFs can be recycled without sacrificing product yield, while simultaneously maintaining crystallinity. The reported findings were supported crystallographically and spectroscopically (e.g., diffuse reflectance infrared Fourier transform spectroscopy), foreshadowing a pathway for the development of multifunctional MOF‐based reagent‐catalyst cargo vessels for reactive gas reagents as an attractive alternative to the use of toxic pure gases or gas generators.

Kittikhunnatham, Preecha↗
DOE OSTI2021

A Metal-Organic Framework (MOF)-Based Multifunctional Cargo Vehicle for Reactive-Gas Delivery and Catalysis

The efficient delivery of reactive and toxic gaseous reagents to organic reactions was studied using metal-organic frameworks (MOFs). The simultaneous cargo vehicle and catalytic capabilities of several MOFs were probed for the first time using the examples of aromatization, aminocarbonylation, and carbonylative Suzuki–Miyaura coupling reactions. These reactions highlight that MOFs can serve a dual role as a gas cargo vehicle and a catalyst, leading to product formation with yields similar to reactions employing pure gases. Furthermore, the MOFs can be recycled without sacrificing product yield, while simultaneously maintaining crystallinity. Our reported findings were supported crystallographically and spectroscopically (e.g., diffuse reflectance infrared Fourier transform spectroscopy), foreshadowing a pathway for the development of multifunctional MOF-based reagent-catalyst cargo vessels for reactive gas reagents as an attractive alternative to the use of toxic pure gases or gas generators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗