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We explore the charge transfer events four different classes of N-heterocyclic carbenes (NHCs) with a Pd/Cu(111) single atom alloy surface. We provide a frontier molecular orbital approach to understand similarities and differences between these systems. We demonstrate that this approach can be applied to the PDOS, COHP, and molecular charges to better understand the surface-adsorbate system. Density of This work emphasizes the composition- and geometry-dependent nature of NHC adsorption on SAAs and provides insights into tailoring these systems for catalytic and storage applications. 

We apply non-local density functional theory calculations to determine the impact of backbones and functionalization of different N-heterocyclic carbenes (NHCs) adsorbed to different single atom alloys (SAAs). A frontier molecular orbital approach is applied to these systems to understand the chemistry occurring. The Local Orbital Basis Suite Towards Electronic-Structure Reconstruction (LOBSTER) program was utilized to project an atomic orbital (AO) basis from our PAW simulations to allow for a MO-oriented bonding analysis MOs of the adsorbate molecules were extracted from our planewave VASP calculations utilizing the linear combination of fragment orbitals (LCFO) method implemented in LOBSTER. 

We discuss several different computational chemistry exercises that are appropriate at the undergraduate level. We highlight how computational chemistry can be integrated into the undergraduate chemistry curriculum with topics ranging from carbon nanotubes, catenanes, paramagnetic NMR, resonance, and other topics. 

Molecular corking is a phenomenon where a molecule selectively binds to the catalytic atom of a single-atom alloy (SAA) and prevents the recombination of atomized gas molecules at the surface of a metal, functionally trapping them. A necessary feature of a molecular cork is strong, yet reversible binding and thermal stability. There is active experimental and theoretical research on potential candidates, which rank the viability of molecular corks based on their ability to donate electrons into sigma bonds and accept back-donation from the metal via pi bonding. This is often assessed experimentally and computationally using chemical shifts in NMR of selenium and phosphorus adducts as well as other metal complexes. A prime candidate for this purpose are N-heterocyclic carbenes (NHC). However, there have been few studies that perform bond decomposition analysis of periodic quantum mechanical calculations to qualify if the observed chemical shifts in NMR and binding strengths on metals are in fact due to sigma donation and pi back bonding. Moreover, the role of conformational flexibility plays in reported NMR chemical shifts is relatively unexplored. Using periodic vdW-DFT calculations and localized bonding MOs extracted from periodic plane-wave basis sets, along with molecular calculations, we seek to answer these questions for simple, but representative molecular systems bound to Cu-Pd SAA surfaces. 

This study investigates the integration of generative artificial intelligence (Gen AI) into a General Chemistry II laboratory at St. Bonaventure University to assess its impact on student learning, inquiry, and chemical reasoning. In a redesigned of a common thermodynamics/equilibrium experiment involving cobalt(II) chloride, students used ChatGPT and a retrieval-augmented Gen AI (BonnieChemBot) to assist in calculating equilibrium constants, thermodynamic values, and answering open-ended chemical questions. The lab targeted four key educational goals: (A) mastery of chemical concepts, (B) development of prompt engineering strategies, (C) facilitation of inquiry-driven dialogue with instructors, and (D) critical evaluation of Gen AI outputs by students using chemical intuition. Students attempted all analyses twice: first independently, then with the assistance of Gen AI. Finally, they were asked to reflect on their trust in the Gen AI solutions and generate final answers. Instructor intervention in post-lab analyses was limited to cases where students had clearly attempted the first two steps in this process. While students were encouraged to practice prompt engineering, no grades were assigned to its execution. Instead, grading focused solely on students’ final answers. 

N-Heterocyclic carbenes (NHCs) are an interesting family of molecules that have potential applications in hydrogen storage via the “molecular corking effect”. Benefits of using NHC backbones as molecular corks include their modularity via functionalization and synthetic diversity. Changing the functional groups can lead to new properties depending on their donation or withdrawal of electron density. Additionally, mono- and di-protonation of the carbene on the various backbones was observed to have significant effects on their proton affinity. We hypothesize that proton affinity can be utilized to understand the sigma donation effects of the evaluated molecules, which are expected to be predictive of the bond strength of an NHC to a surface. 

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. 

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. 

We have predicted acid dissociation constants (pKa), octanol-water partition coefficients (KOW), and DPMC lipid membrane-water partition coefficients (Klipid-w) of 150 different 8-carbon containing poly-/per-fluoroalkyl carboxylic acids (C8-PFCAs) utilizing COMSO-RS theory. Different trends associated with functionalization, degree of fluorination, degree of saturation, degree of chlorination, and branching are discussed based upon the predicted values for the partition coefficients. In general, functionalization closest to the carboxylic head group had the greatest impact on the value of the predicted physicochemical properties.