Abstract
Hard carbons are the primary candidate for the anode of next-generation sodium-ion batteries for large-scale energy storage, as they are sustainable and can possess high charge capacity and long cycle life. These properties along with diffusion rates and ion storage mechanisms are highly dependent on nanostructures. This work uses reactive molecular dynamics simulations to examine lithium and sodium ion storage mechanisms and diffusion in lignin-based hard carbon model systems with varying nanostructures. It was found that sodium will preferentially localize on the surface of curved graphene fragments, while lithium will preferentially bind to the hydrogen dense interfaces of crystalline and amorphous carbon domains. The ion storage mechanisms are explained through ion charge and energy distributions in coordination with snapshots of the simulated systems. It was also revealed that hard carbons with small crystalline volume fractions and moderately sized sheets of curved graphene will yield the highest sodium-ion diffusion rates at ∼10-7 cm2/s. Self-diffusion coefficients were determined by mean square displacement of ions in the models with extension through a confined random walk theory.
| Original language | English |
|---|---|
| Pages (from-to) | 19883-19892 |
| Number of pages | 10 |
| Journal | ACS Omega |
| Volume | 6 |
| Issue number | 30 |
| DOIs | |
| State | Published - Aug 3 2021 |
| Externally published | Yes |
Funding
This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. This work used the XSEDE COMET at the San Diego Supercomputer Center through allocations TGDMR190050 and TG-DMR190098. This work used the resources of Infrastructure for Scientific Applications and Advanced Computing (ISAAC) at The University of Tennessee, Knoxville. This work used models created with the aid of structural information obtained through use of the Spallation Neutron Source at Oak Ridge National Laboratory and sponsored by was sponsored by the U.S. Department of Energy, Office of Basic Energy Sciences. This research was supported by a grant from the U.S. Department of Agriculture National Institute of Food and Agriculture Nanotechnology Program award number 2017-67021-26599. David P. Harper acknowledges support from the USDA National Institute of Food and Agriculture, Hatch Project 1012359.
