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Computational chemistry is no longer seen as just an academic exercise. Researchers in academia and industry are now aware of the benefits associated with theoretical predictions of molecules. However, there is a skills-gap associated with teaching/learning the basics and the applications of computational chemistry. Herein, we describe the development and utilization of several quantum chemical exercises for educational purposes. 

An in-silico exercise was developed for a general chemistry laboratory course at St. Bonaventure University in which students examined potential energy surfaces, molecular orbital diagrams, and how bond orders and Lewis structures are connected. Pre- and post-assessment data suggests that, though students learned from the exercise, they are not connecting the concepts of bond order, Lewis structures, and resonance. There was a statistically significant improvement in the assessment scores before and after the laboratory experiment, and there was no statistical difference between the post-assessment and the follow-up assessment, which occurred after students completed the lab report 1 week after the initial experiment. The data suggest an improved understanding of computational chemistry concepts as well as improvement in the individual concepts of resonance, Lewis structures, and bond orders. However, an assessment question connecting these concepts did not show an improvement. An additional questionnaire was conducted to explore this discrepancy. This study indicates that more investigation is necessary with regard to students’ ability to make logical connections among bond orders, Lewis structures, and resonance. 

Despite the prominence of orbitals throughout the undergraduate chemistry curriculum, high-quality visualization of atomic orbitals is out of reach for most scientists. Rigorously visualizing the atomic orbitals even for simple hydrogen-like atoms and ions is rather challenging due to the complex 3-D structure and geometric variability of the orbitals across three distinct quantum numbers. In this work, a graphical user interface (GUI)-based tool for visualizing 3-D volumetric density plots of hydrogen atomic orbitals is introduced. This tool is written in Python, and a Jupyter notebook version with explanatory blocks interspersed in the code is included for pedagogical purposes. The user can manipulate a large number of features using the GUI, which allows customization of the orbital illustrations. Because this visualizer is capable of visualizing orbitals with any quantum numbers and showing their nodal surfaces, it can serve as a supplement to students’ lecture and textbook education on this topic. 

N-heterocyclic carbenes(NHCs) have garnered the attention of material scientists and chemists for their tunable electronic properties. NHCs anchored to surfaces have attractive features and may provide new applications that traditional self-assembled monolayers (SAMs) have yet to be employed. In-fact, NHCs have been utilized to functionalize surfaces to tune reactivity and/or selectivity. However, the underlying mechanisms to control the surface-adsorbate interaction is still in its infancy, especially for SAAs. Herein we utilize periodic non-local density functional theory (DFT) calculations to better understand how changing the NHC backbone influences the bonding between the surface and the adsorbate with the end goal to utilize a relatively new mechanism to store hydrogen. 

N-heterocyclic carbenes (NHCs) have grown in popularity in recent years due to their superior surface stability on metal nanoparticles and surfaces. This stability is often characterized experimentally by studying the σ-donation and π-backbonding as measured through NHC-selenium adduct NMR and the Huynh Electronic Parameter (HEP), respectively. However, recent work with NHCs on metal clusters suggests that the ligands can adopt a variety of orientations on the surface. Thus, the surface may have a pronounced impact on the σ-donation and π-backbonding observed for these NHCs. In this work, we aim to determine how well these experimental characterizations compare to trends observed via bond decomposition analysis. 

Density functional theory (DFT) calculations of 57 iron bis(dithiolene)-N-heterocyclic carbene adducts were conducted to determine what parameters predict, and possibly influence, the coordination of these aforementioned adducts. The parameters considered...