Computational Chemistry

Many organic molecules are efficient light emitters used for optoelectronic devices such as OLEDs, due to their advantages over metallic counterparts, including lower toxicity, simpler disposal, and sustainability. However, the methodologies commonly used in organic synthesis to obtain these molecules often rely on harsh conditions and generate large amounts of waste, making them both ineffective and inefficient. This work aligns with some of the principles of green chemistry across different stages.

Ice formation remains a critical challenge across multiple industries, posing safety risks, economic burdens, and, in extreme cases, fatalities. Effective anti-icing strategies are essential to mitigate these issues, yet the demand for environmentally friendly, cost-effective, and efficient solutions persists. Natural deep eutectic solvents (NADES) have emerged as a promising low-toxicity alternative for addressing ice formation.

The efficient design and synthesis of emitters for organic light-emitting diodes (OLEDs) is a critical area of research, driven by the demand for cost-effective, sustainable, and high-performance blue emitters. This study presents the design and synthesis of 3,3’-bicarbazole-triazine derivatives as potential thermally activated delayed fluorescence (TADF) emitters. Using computational modeling, donor-acceptor (D-A) structures were rationally designed to exhibit blue emission and low singlet-triplet energy gaps.

The application of quantum-based NMR methods for the structural elucidation of natural and unnatural products has grown significantly. However, accurately calculating the conformational landscape of flexible molecules with intricate intramolecular hydrogen bonding (IHB) networks continues to be a major challenge. Previous studies have shown that to solve biased systems with strong IHB interactions, it is necessary to calculate the Boltzmann contributions using Gibbs free energies computed with at least a triple-ξ basis set and the SMD solvation model.

Neglected tropical diseases, such as Chagas disease caused by Trypanosoma cruzi, remain a critical global health problem, particularly in underprivileged communities. Our research aims to develop potential therapeutic agents by synthesizing and characterizing analogues of aureothin, a polyketide with known antiparasitic activity.

The use of NMR methods based on quantum mechanics to complement and guide the assignment of connectivity and stereochemistry of natural and artificial products has grown significantly. One of the unresolved challenges relates to the incorrect calculation of the conformational map of flexible molecules containing functional groups capable of generating a complex network of intramolecular hydrogen bond (IHB) interactions.

A novel statistical correlation method, MM-DP4+, was developed to enhance NMR-based molecular structure elucidation by significantly reducing computational costs through the use of MM-optimized geometries. A comprehensive evaluation of 36 theory levels identified SMD/ωB97XD/6-31+G**//MMFF as the most accurate and cost-effective approach, achieving 91% accuracy in stereochemical assignments. A Python-based software, DP4+App, was created to streamline the implementation of DP4+, MM-DP4+, and customizable DP4+ calculations via a user-friendly interface.