EFFICIENT ORGANIC MOLECULAR CRYSTAL STRUCTURE PREDICTION USING THE DENSITY FUNCTIONAL TIGHT-BINDING METHOD

Over the years, crystal structure prediction (CSP) has thrived as an area of research, spanning various scientific disciplines, and having significant applications in industries such as pharmaceuticals and agrochemicals. Within the field of batteries, redox-active organic materials (ROMs) such as quinones have received increased attention as promising electrode materials for rechargeable batteries. However, experimental determination of the crystal structure of intermediate species formed during the discharge/charge cycle can often be challenging. Incomplete X-ray diffraction patterns can also lead to difficulties in crystal structure determination for ROMs used in batteries. Use of a semiempirical electronic structure method for CSP helps to avoid force field reparameterization for different species, sometimes with complex electronic structure, formed during battery operation. It also helps to significantly lower the computational cost compared to the widely used density functional theory (DFT). The goal of this study is to systematically investigate the ability of a DFT-based semiempirical method, third-order density functional tight-binding (DFTB3), to predict the most stable crystal structures of organic molecules with different kinds of intermolecular interactions ranging from hydrogen bonding to -stacking. Here, DFTB3 in conjunction with the particle swarm optimization (PSO) algorithm, as implemented in the CALYPSO software, is also used to predict the most stable crystal structures of selected quinones relevant to organic batteries. Our findings emphasize the potential of CALYPSO/DFTB as a promising approach for CSP of different classes of organic molecules, including quinones. Additionally, they establish the foundation for future CSP studies of other organic molecules utilized in rechargeable batteries.