Computational Chemistry

"Computational chemistry is also used to study the fundamental properties of atoms, molecules, and chemical reactions, using quantum mechanics and thermodynamics "

American Chemical Society

Computational session has been scheduled for Monday Afternoon.

If you find any errors in our listing please let us know at chemistrybuffalogss@gmail.com

Monday Afternoon

Session 2B - Room NSC 218 - Moderator: Md Saiful Chowdhury

1:30 p.m. - 1:50 p.m.

Theoretical Prediction of Superhard Materials with the XtalOpt Evolutionary Algorithm

Xiaoyu Wang, Patrick Avery, Davide Proserpio, Cormac Toher, Stefano Curtarolo, Eva Zurek

The State University of New York at Buffalo, Department of Chemistry

The XtalOpt evolutionary algorithm for crystal structure prediction has been extended to enable the prediction of superhard stable materials. The hardness is calculated via a linear relationship with the shear modulus (originally discovered by Teter) as reported by Chen. The shear modulus is obtained via AFLOW-ML (Automatic FLOW for Materials Discovery - Machine Learning). A new fitness function has been implemented wherein the user can denote the percent contribution that hardness and enthalpy have on the fitness function. We have used XtalOpt to search for hard and stable carbon allotropes and found 44 hitherto unpredicted phases whose Vickers Harnesses were calculated to be greater than 45 GPa. The structural motifs in these phases were analyzed. We also discuss the thermodynamic and kinetic stability of the predicted structures, and potential ways in which they can be synthesized under pressure.

1:50 p.m. - 2:10 p.m.

Computational Drug Repurposing with CANDO

Jim Schuler, William Mangione, Matt Hudson, Zackary Falls, Ram Samudrala

The State University of New York at Buffalo, Department of Biomedical Informatics

It takes $2 billion and over 10 years to bring a new medicine to the market. For the high resource and time costs, we get drugs which do not always work and come with terrible side effects. As a solution to these problems we have developed the Computational Analysis of Novel Drug Opportunities (CANDO) shotgun drug repurposing platform. Drug repurposing simply means using a new or previously approved medicine in a new way. The first version of CANDO implemented a structure-based pipeline that modeled interactions between compounds and proteins on a large scale, generating compound-proteome interaction signatures used to infer similarity of drug behavior and make predictions of new drug use. Using a leave-one-out benchmarking protocol, we obtained scores in our three performance metrics, average indication accuracy, pairwise accuracy, and coverage, an order of magnitude higher than expected by random chance. In our most recent work, we have included ligand-based, data fusion, and decision tree pipelines. The new pipelines incorporate molecular fingerprints and the Tanimoto coefficient. Using CANDO we have the ability to generate putative therapeutic repurposing candidates and increase drug discovery efficiency and efficacy.

2:10 pm - 2:30 p.m.

Effect of Graphene Surface Ripples and Thermal Vibrations on Motion of C60 as a Nanocar Wheel

S. Mahsa Mofidi, Alexey V. Akimov, Hossein Nejat Pishkenari, Mohammad Reza Ejtehadi

The State University of New York at Buffalo, Department of Chemistry

Nanocars are synthesized molecular machines with chassis, axels and wheels for nanoscale transporting through surface motion. The first step in better understanding and designing nanocars is to run them on different substrates. Graphene is a flexible 2D material with intrinsic ripples on its surface. The effect of these ripples on the surface motion is not studied yet. Here we compare different modes of motion of C60, as nanocars wheel, on graphene structures based on surface ripples and thermal fluctuation of atoms. Through conducting potential energy surface analysis and molecular dynamics simulations at temperature ranges from 5K to 900K on surfaces with different ripples magnitudes, the effect of ripples is studied. It is found that surface ripples on the substrate, increase vertical oscillation of C60 which lead to decreased desorption temperature from 650 K on double layer graphite system with less ripples to 550 K for single layer graphene with more ripples. For lateral motion, ripple changes the anomaly parameter, especially at low temperatures. However, in the case of rotational motion ripples have no major effect, and only the temperature plays the role. These outcomes help for understanding the mechanism of surface motion on a flexible substrate and open the doors to better design of thermally driven fullerene-based nanocars.

2:30 p.m. - 2:50 p.m.

Theoretical Prediction of Sulfides Under Pressure

Nisha Geng, Tiange Bi, Niloofar Zarifi, Eva Zurek

The State University of New York at Buffalo, Department of Chemistry

Inspired by the discovery of high temperature superconductivity in the hydrogen/sulfur system, the XtalOpt evolutionary algorithm has been used to predict the structures of binary sulfides under pressure. A number of stable and metastable phases with novel stoichiometries are found at pressures attainable in diamond anvil cells. The electronic structure properties of these phases are analyzed.