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. Here, we systematically investigate the ability of the third-order density functional tight binding method (DFTB3) in conjunction with the particle swarm optimization (PSO) algorithm, as implemented in the CALYPSO software, to predict the crystal structures of different classes of organic molecules chosen from the X23 data set. We also apply this approach to predict the crystal structures of selected quinones. 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.

Organic materials with controllable molecular design and sustainable resources are promising electrode materials. Crystalline quinones have been investigated in a variety of rechargeable battery chemistries due to their ubiquitous nature,...