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Published September 6, 2018 | Submitted
Journal Article Open

Free Energy Landscape of Sodium Solvation into Graphite

Abstract

Na is known to deliver very low energy capacity for sodium intercalation compared to lithium. In this study, we use quantum mechanics based metadynamics simulations to obtain the free energy landscape for sodium ion intercalation from dimethyl sulfoxide (DMSO) solvent into graphite. We find that the lowest free energy minima from the metadynamics are associated with sodium solvated by 3 or 4 DMSO. The free energy minima of these states are activated by a free energy of solvation computed to be 0.17 eV (ΔG(Na^+@(DMSO)_4) – ΔG(Na^+@(DMSO)_3 ≈ 6.6k_BT), which in turn are the most thermodynamically stable. We observe weak interactions of sodium with graphite sheets during the unbiased and biased molecular dynamics simulations. Our simulation results suggest that solvent plays an important role in stabilizing the sodium intercalation into graphite through shielding of the sodium as well as from the interaction of the solvent with the graphite sheets. This suggests that the poor performance of Na is because the nonbonding and maybe partial covalent bonding of Na^+ to the DMSO is too strong compared to insertion into the graphite. This suggests that we consider solvents containing oxygen groups that might interact with Na that are more compatible with the bonding of Na in the graphite intercalation compound (GIC), but with negative charges (i.e., charge carrier nature) attached to these groups. To facilitate this intercalation, we propose solvents with negatively charged groups and aromatic cores (e.g., cyclic ethers) that could allow a greater rate of anion exchange to increase Na^+ mobility.

Additional Information

© 2018 American Chemical Society. Received: May 20, 2018; Revised: July 10, 2018; Published: July 24, 2018. A.K. thanks his institution for the support to visit the Materials and Process Simulation Center, California Institute of Technology, Pasadena, CA. Warm thanks are due to Marcella Iannuzzi for stimulating discussions. The HPC resources and services used in this work were provided by the Research Computing group in Texas A&M University at Qatar. Research computing is funded by the Qatar Foundation for Education, Science, and Community Development. W.A.G. thanks Bosch Energy Research Network (BERN) for a Grant to support battery research. The authors declare no competing financial interest.

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August 19, 2023
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