Description:

Speaker: Rachel Watson, Notestein Lab
Title: Ethylene Carbonylation Over MoS2 and PdS
Abstract
Carbonylation is an important class of reactions in the synthesis of many fine chemicals, although relatively few catalysts exist for the conversion of C2 species into the corresponding C3 carboxylic acids and esters. Of these systems, metal sulfide catalysts may be promising, especially for promoter-free carbonylation. Metal sulfides have many uses in hydrotreating and homologation reactions but have been studied minimally for carbonylation. In this work, we discuss a promoter-free ethylene carbonylation route to propionates over transition metal sulfide catalysts in water.
Ethylene carbonylation in water over sulfide catalysts is very clean, in most cases giving only propionic acid and its anhydride, ethanol, and propanaldehyde. In general, noble metal sulfides are very active towards propanaldehyde, while the MoS2 catalysts are relatively selective to propionic acid. MoS2, and PdS have been investigated. In addition to reporting basic catalyst performance metrics, reactivity will be correlated with specific surface area, catalyst reducibility, and other properties. This work presents a fresh approach to the long standing and heavily studied C2 carbonylation challenge.

Speaker: Ying Yu, Broadbelt Lab
Title: Mechanistic study of regioselective ring-opening reactions of mono-substituted epoxides using Lewis acid catalysts

Abstract
Polyether polyols are important intermediates in the polyurethane industry and are typically made by reacting mono-substituted epoxides with polyalcoholic initiators in the presence of a catalyst.1 While conventional catalysts such as potassium hydroxide and double metal cyanide catalysts result in less reactive polyols terminated with secondary hydroxyl groups, Lewis acid catalysts, aryl boranes, has been found to achieve high regioselectivity towards the desired primary alcohol functionality.2 In addition, recent experiments revealed significant water effects on retarding the ring-opening rate and additive effects in enhancing the regioselectivity towards primary alcohol products. However, the detailed catalytic mechanism is not fully understood. In addition, the catalytically active species is still unclear based on existing experimental methods that are unable to monitor the in situ speciation of this complex reaction system.

In this study, a novel catalytic mechanism was proposed for a model system using tris (pentafluorophenyl) borane (FAB) as catalyst and was validated by an ab initio study together with comprehensive microkinetic modeling. Density functional theory (DFT) was used to investigate two classes of possible reactions: competitive binding reactions of ligands to the catalyst, and the catalytic ring-opening reactions. We identified several possible catalyst forms that contribute to ring-opening reactions with different regioselectivities. The microkinetic model validated the proposed mechanism against experimental results and was used to generate accurate predictions under other reaction conditions. Analysis of speciation and net reaction rates elucidated the effects of water concentration on reactivity through a catalyst deactivation mechanism, and the effects of additives on regioselectivity as co-catalysts. Ultimately, this study facilitates greater understanding of catalyzed regioselective ring-opening reactions and provides a basis for the design of new catalytic systems to modulate ring-opening kinetics and the overall regioselectivity.

References:
(1) Chinn, H. K., A.; Loechner, U. SRI Consulting 2006.

(2) (a) Satake, M. US6531566B1, 2003. (b) Chakraborty, D.; Rodriguez, A.; Chen, E. Y. X. Macromolecules 2003, 36, 5470-5481. (c) Chandrasekhar, S.; Reddy, C. R.; Nagendra Babu, B.; Chandrashekar, G. Tetrahedron Lett. 2002, 43, 3801-3803. (d) Raghuraman, A.; Babb, D.; Miller, M.; Paradkar, M.; Smith, B.; Nguyen, A. Macromolecules 2016, 49, 6790-6798.

Speaker: Jennifer Greene, Broadbelt and Tyo Labs
Title: Optimizing Ensemble Modeling Framework to Generate Kinetic Models of Metabolism

Abstract
Developing reliable, predictive kinetic models of metabolism is a difficult yet necessary priority toward understanding and deliberately altering cellular behavior. However, many of the in vivo kinetic parameters and rate laws governing individual enzymes are unknown. Ensemble Modeling (EM) was developed to circumnavigate this challenge and effectively sample the large kinetic parameter solution space using consistent experimental datasets. Unfortunately, EM, in its current form, requires long solve times to complete and often leads to unstable kinetic model predictions. Furthermore, these limitations scale prohibitively with increasing model size. As larger metabolic models are developed with increasing genetic information and experimental validation, the demand to incorporate supplemental kinetic information increases. Therefore in this work, we have begun to tackle the challenges of EM by introducing additional steps to the existing method framework specifically through reducing computation time and optimizing parameter sampling. We first reduce the structural complexity of the network by removing dependent species, and second we sample locally stable parameter sets to reflect realistic biological states of cells. Lastly, we presort the screening data to eliminate the most incorrect predictions in the earliest screening stages, saving further calculations in later stages. Our complementary improvements to the current EM framework are easily incorporated into concurrent EM efforts and broaden the application opportunities and accessibility of kinetic modeling across the field.