Spring 2018. Andrew Mahler, Stephanie Jones, Arshad Mehmood, Ben Janesko, Amanda Blitch (not shown).



We are a research group developing and applying modern techniques in computational chemistry. Our current research portfolio has four main components.

1: Experimental Collaborations

We collaborate with experimentalists to understand and predict new chemistry. The figure below illustrates our experimentally validated prediction that hydrolyzable drug-dendrimer hydrazone linkages are controlled by the pKa of the adjacent triazine. Other recent collaborations include a systematic study of tautomerization-induced activation of organophosphorus feedstocks and redox behavior of bimetallic complexes. Our Quantum Chemical Fragment Precursor Tests algorithm for assigning fragmentations in tandem mass spectrometry, developed as part of these collaborations, is available at our GitHub repository. My graduate course in Computational Chemistry for Experimentalists, available online, is another important component of these collaborations.

Hydrazone hydrolysis reaction scheme

2: DFT Methods Development

We develop "Rung 3.5" approximations, as a practical route beyond standard DFT's zero-sum game. The figure below shows how our approximations simultaneously improve both the over-delocalization of radicals like H2(+), and the underbinding of covalent bonds like stretched H2. Our approximations are currently implemented in the development version of the Gaussian electronic structure package. Our recent review gives a perspective on these issues' important role in heterogeneous catalysis, nanomaterials, and surface chemistry.

Zero-sum tradeoff between fractional charge and spin errors

3: Interpretive Tools

We have developed the "overlap distance", a new interpretive tool that extrats information about orbital overlap and chemical hardness from electronic structure calculations. The figure below shows the structure, electrostatic potential (red=negative, blue=positive), and overlap distance (red=chemically hard, blue=chemically soft) of an ambident aminophosphine ligand. The electrostatic potential highlights the two lone pairs (center, red). The overlap distance instead distinguishes the chemically "hard", compact nitrogen lone pair (right, red) from the "soft", diffuse phosphorus lone pair (right, blue). We have applied the overlap distance to detect reactive sites in noble metal nanoclusters You can try out the overlap distance in the Gaussian 16, Multiwfn, and NCIplot electronic structure packages. See our guides to evaluating the overlap distance in Gaussian 16 and in Multiwfn.

Aminophosphine ligand structure Aminophosphine ligand electrostatic potential Aminophosphine ligand overlap distance

4: Surface Chemistry and Catalysis

We have an ongoing collaboration with the Brothers group at Texas A&M Qatar applying new DFT methods to heterogeneous catalysis. The cover art below is from our systematic study of catalysis by narrow coinage metal nanoribbons, a model system for catalytic nanorods, nanotubes, and nanoribbons.

IJQC cover art


We are grateful for support from the NSF DMR, the XSEDE, and the Qatar National Research Fund

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