Asymmetric Nucleophilic Allylation of α-Chloro Glycinate via Squaramide Anion-Abstraction Catalysis: SN1 or SN2 Mechanism, or Both?

Enhancing silicon-nitride formation through ammonolysis of silanes with pseudo-halide substituents

Considering the challenges in reactivity, potential contamination, and substrate selectivity, the ammonolysis of traditional halosilanes in silicon nitride (SiN) thin film processing motivates the exploration of alternative precursors. In this pioneering study, we employed density functional theory calculations at the M06-2X/6-311++G(3df,2p) level to comprehensively screen potential pseudo-halide substituents on silane compounds as substitutes for conventional halosilanes. Initially, we investigated the ammonolysis mechanism of halosilanes, exploring factors influencing activation barriers, with the aid of frontier molecular orbital and charge density analyses. Subsequently, a systematic screening of silane substituents from group 14 to group 16 was conducted to identify pseudo-halides with low reaction barriers. Additionally, we examined the inductive effects on pseudohalide substituents. Using cluster models to represent the silicon surface validates the realistic prediction of ammonolysis barriers with a simplified model. Our findings indicate that pseudo-halide substituents from group 16, particularly those with electron-withdrawing groups, present as practical alternatives to traditional halosilanes in SiN thin film processing, including applications such as low-temperature atomic layer deposition (ALD) techniques.

Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis-Challenges and Opportunities

Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components to calculate or predict catalysis-performance metrics, such as turnover frequency and measurement of stereoselectivity, via computational chemistry. The state-of-the-art tools available to calculate potential energy and, consequently, free energy, together with their caveats, will be discussed via examples from the literature. Through various examples from organocatalysis and phase transfer catalysis, we will highlight the challenges related to the mechanism, transition state theory, and solvation involved in translating calculated barriers to the turnover frequency or a metric of stereoselectivity. Examples in the literature that validated their theoretical models will be showcased. Lastly, the relevance and opportunity afforded by machine learning will be discussed.

In silico characterization and prediction of thiourea-like neutral bidentate halogen bond catalysts

Preorganization is a common strategy to align halogen bond (XB) donors to form two or more halogen bonds simultaneously. Previous approaches have utilized various non-covalent interactions such as steric interactions, ππ stacking, and hydrogen bond interactions. However, some of the introduced aligning interactions may compete with halogen bond interactions if the donors are employed in catalysis. To achieve thiourea-like properties, we have designed in silico several neutral bidentate halogen bond donors in whose structures the donor moieties are connected via covalent bonds. Compared to previous XB catalyst designs, the new design does not involve other potentially competitive non-covalent interactions such as hydrogen bonds. One of the designed XB donors can deliver strong halogen bonds, with a O-I distance as short as 2.64 Å. Density functional theory (DFT) calculations predicted that our designed catalysts may catalyze important organic reactions on their own, particularly for those reactions that involve (developing) soft anions such as thiolates.