Electric batteries, Vol. 7, Pages 71: Evaluation of Computational Hormone balance Techniques for Predicting Redox Possibilities of Quinone-Based Cathodes for the purpose of Li-Ion Batteries
Batteries doi: 10. 3390/batteries7040071
Authors: Xuan Zhou Abhishek Khetan Süleyman Er
High-throughput computational screening (HTCS) is a good effective tool to speed up the discovery of energetic materials for Li-ion batteries. For the evaluation of organic cathode materials, the potency of HTCS depends on the accuracy of the employed chemical substance descriptors and their computing cost. This work had been focused on evaluating the performance of computational biochemistry methods, including semi-empirical mess mechanics (SEQM), density-functional tight-binding (DFTB), and density functional theory (DFT), for your conjecture of the redox possibilities of quinone-based cathode materials for Li-ion batteries. In addition , we evaluated the accuracy of three energy-related descriptors: (1) the redox reaction energy, (2) the lowest unoccupied molecular orbital (LUMO) energy of reactant substances, and (3) the best occupied molecular orbital (HOMO) energy of lithiated product molecules. Among them, the LUMO energy of the reactant compounds, regardless of the level of theory used for the calculation, showed the greatest performance as being a descriptor for the purpose of the prediction of trial and error redox potentials. This uncovering contrasts with our earlier results on the calculation of quinone redox potentials in aqueous media for redox flow batteries, for which the redox response energy was the best descriptor. Furthermore, the combination associated with geometry optimization using low-level methods (e. g., SEQM or DFTB) followed by energy calculation with DFT produced accuracy as good because the full optimization of angles using the DFT calculations. So, the proposed calculation scheme is useful for both the particular optimum use of computational resources and the organized generation of robust calculation data on quinone-based cathode compounds for the exercising of data-driven material breakthrough discovery models.
