Presenter 1: Amir Farokh (PhD, Bernhardt Group, AIBN)

Title: Enhancement of the Performance of Rechargeable Batteries by Proposing New Materials

Abstract: The selection of a suitable material for the anode and cathode of a rechargeable battery has a direct effect on the battery performance. Two important aspects of this issue are the charge storage capacity and the battery discharge time. In the first year of the PhD candidature, we have considered an anode composed of a recently synthesized carbon allotrope, graphdiyne (GDY), in conjunction with sodium (Na) as a charge transfer agent. A comprehensive theoretical study has been carried out by applying first principle calculations based on density functional theory (DFT). This study determines the binding energy of Na atoms on GDY layers, as well as energy barriers for Na diffusion throughout the layers. For this purpose, the VASP (Vienna ab initio simulation package) has extensively been applied to evaluate these values. According to the results, Na intercalates on the GDY layers with maximum capacity of NaC2.57 and NaC5.14 for GDY single layer and bulk layers, respectively (equivalent to 497 and 316 mAh/g, respectively). Moreover, the energy barrier for in-plane movement of Na from one pore to another pore in GDY bulk layers is found to be 0.819 eV. Furthermore, the barrier of energy for continuous zigzag movement of Na through centroids of the pores is found to be only 0.029 eV. Therefore, the combination of GDY with Na atoms is proposed as an alternative anode material for rechargeable batteries.

Presenter 2: Bertrand Caron (PhD, MD Group, SCMB)

Title: Improved Force Fields for Biomolecular Simulation: Analysis of the extent of transferability of bonded and non-bonded terms

Abstract: Computational methods can offer unique insight at an atomic level into the structure and dynamics of biomolecules. While ideally described quantum-mechanically, in practice simpler empirical “force field” descriptions are needed to describe inter-particle interactions. The predictive ability of any force field is only as good as the underlying model. Parametrising empirical force-fields is tedious, error-prone and often arbitrary. The talk will focus on novel approaches using molecular graphs and large molecular datasets to identify the minimum number of parameters required to represent specific classes of biomolecules. Specifically, I have examined chemical equivalence between atoms within molecules, and developed a symmetry-corrected RMSD metric to compare the structure of molecular fragments regardless of their representation. This is being used to identify transferable dihedral fragments and develop an associated set of torsion parameters. Common biopolymers such as proteins and nucleic acids can be represented with as few as 80 dihedrals. As few as 200 dihedral terms would be sufficient to describe the torsional potential required to parametrise 4,000 small molecules, many of them found interacting with biomolecules in the Protein Data Bank.