Computational Modeling of Carboxylic-based Organic Molecules for Li-ion Battery Anode Materials
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As clean-energy driven electric vehicles, devices, and other renewabletechnologies are progressing towards full-scale commercializationthere exists some impediments in the efficacy of energy storage technology.This need to be addressed for them to become more attractiveand replace conventional energy sources. In this regard, Li-ion batterywith organic anode materials can play a vital role, since theyare cheap to produce, easy to tailor with desirable functional groups,and have seen shown wide acceptance as an electrode material in thepast. In this present work, we look at carboxylic group-based 1,4,5,8Naphthalenetetracarboxylic Anhydride (NTCDA) as an anode material.Recent experiments found NTCDA to have a specific chargecapacity of 1800 mAg/h, with steady performance over a large numberof charge/discharge cycles. Our methodology involves placing Li ionsand atoms on a pre-optimized NTCDA geometry, where the locationof each Li species is chosen based on a potential energy surface studyof NTCDA. We carried out the process for 1-24 Li atoms, and 1-5 Liions, by generating 100 conformers of each NTCDA and Li/Li+ configuration. We conducted DFT calculations employing PBE0 methodand def2-SVP basis set along with dispersion correction, to find theabsorption energy and natural population analysis data of the moststable conformer. We repeated such geometry optimization calculationsfor the 5 most stable conformers with TZVP basis sets. Afterwards, we scanned the trends of binding energy and visualized theleast-energy structures to find the number of Li ions and atoms thatcan attach to the NTCDA surface. We also calculated Fukui indicesfor NTCDA, which revealed the number of covalent bond-formingsites. We thus predicted the charge capacity of a NTCDA-based anodebased on the total number of Li ions shuttling between the twoelectrodes, and compared with experimental data.