Tailoring aqueous electrolytes based on M = Li, Na and K for the α-MnO2 electrode and its applications for energy storage devices: A DFT approach
Source abstract
Abstract
Manganese oxide (MnO 2 ) as an electrode material in energy storage devices has been used in supercapacitor electrodes because of its high capacitance and its sensitivity to the electrolyte chosen. In this work, density functional theory (DFT) calculations have been performed to understand the influence of the electrolyte MNO 3 with different metal cations ( M =Li, Na, K) and the presence of water molecules on the α -MnO 2 surface. Through exploration of the potential energy surface, the relative energies involved in the diffusion process of M cations were described. The electronic density of states and the charge density differences allowed us to identify that the KNO 3 electrolyte improves charge accumulation in the α -MnO 2 structure. Quantum capacitance was calculated as an additional descriptor to elucidate the influence of the electronic structure properties on α -MnO 2 during the charging process. This theoretical modeling provides a comprehensive framework for understanding the mechanisms behind the ion charge transfer within the electrolyte. In particular, its interaction with the surface of the electrodes and the related pseudocapacitive properties. This work also provides insight into the charge/discharge processes of the electrode at the atomic level and may serve as a tool to tailor novel materials for energy storage devices. • Manganese oxide offers high capacitance and sensitivity to chosen electrolytes. • DFT calculations show KNO 3 electrolyte enhances charge accumulation in α -MnO 2 structure. • Quantum capacitance suggests the electrolyte performance in α -MnO 2 as an electrode. • DFT provides insight into atomic-level charge/discharge processes in electrode α -MnO 2
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Advancements in Battery Materials · Gas Sensing Nanomaterials and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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