A Virtual Laboratory: Using Computational Chemistry to “See” What Cannot Be Seen
In many chemical processes, we desire an atom-level understanding of the transformations occurring in our systems. Ideally, this understanding will us allow for design better chemical processes. Computational approaches can overcome limitations in the ability of experimental methods to “see” atoms in action and provide precious insights to design processes with improved performances. In this talk, I will discuss two specific examples, one in the field of catalysis and one related to mass spectrometry, as showcases of the power of computational methods in interpreting, predicting and designing selective and efficient chemical processes. In the first case, we will be investigating complexes competent for ammonia oxidation, as part of an emerging strategy for energy storage and energy production. Various metal complexes are screened for their ability to cleave N–H bonds homolytically and lead to eventual N–N bond formation. I will present a detailed computational analysis of the electronic determinants that regulate the N-H bond dissociation free energies (BDFEs), and show how, moving from late to early transition metals, it is possible to facilitate the N-H dissociation, and how, for selected metals, it is possible to achieve equiergic breaking of the three N-H bonds. I will also discuss how to promote N-N coupling, a step previously found to be difficult in early metals. In the realm of mass spectrometry, I focus on soft ionization processes, such as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI), for detection of moderately polar and nonpolar analytes. I will discuss how computational methods provide precious insights on how the nature of parent condensed phase influences the fate of an analyte in the gas phase (the so-called matrix effects). Specifically, I will show how microsolvated phases, or small clusters of solute and solvent, can change what species enter the mass spectrometer.