Dataset Information

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and ¹H NMR Spectroscopy.

ABSTRACT: Molecular dynamics (MD) simulations, density functional theory (DFT) calculations, and ¹H NMR spectroscopy were performed to gain a complementary understanding of the concentrated Li-ion electrolyte system, lithium bis(trifluoromethanesulfonyl)imide (Li[TFSI]) dissolved in tetraglyme. The computational methods provided the concentration dependence of differing solvation structure motifs by reference to changes in the corresponding NMR spectra. By combining both the computational and experimental methodologies, we show that the various solvation structures, dominated by the coordination between the tetraglyme (G4) solvent and lithium cation, directly influence the chemical shift separation of resonances in the ¹H NMR spectra of the solvent. Thus, the ¹H NMR spectra can be used to predict the fraction of tetraglyme involved in the solvation process, with quantitative agreement with solvation fraction predictions from MD simulation snapshots. Overall, our results demonstrate the reliability of a hybrid computational and experimental methodology to understand the solvation structure and hence transport mechanism of LiTFSI-G4 electrolytes in the low concentration region.

SUBMITTER: Im J

PROVIDER: S-EPMC9720717 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and <sup>1</sup>H NMR Spectroscopy.

Im Julia J Halat David M DM Fang Chao C Hickson Darby T DT Wang Rui R Balsara Nitash P NP Reimer Jeffrey A JA

The journal of physical chemistry. B 20221116 47

Molecular dynamics (MD) simulations, density functional theory (DFT) calculations, and <sup>1</sup>H NMR spectroscopy were performed to gain a complementary understanding of the concentrated Li-ion electrolyte system, lithium bis(trifluoromethanesulfonyl)imide (Li[TFSI]) dissolved in tetraglyme. The computational methods provided the concentration dependence of differing solvation structure motifs by reference to changes in the corresponding NMR spectra. By combining both the computational and e ...[more]

PMID: 36383474

Similar Datasets

Project description:Efforts to expand the technological capability of batteries have generated increased interest in divalent cationic systems. Electrolytes used for these electrochemical applications often incorporate cyclic ethers as electrolyte solvents; however, the detailed solvation environments within such systems are not well-understood. To foster insights into the solvation structures of such electrolytes, Ca(TFSI)2 and Zn(TFSI)2 dissolved in tetrahydrofuran (THF) and 2-methyl-tetrahydrofuran were investigated through multi-nuclear magnetic resonance spectroscopy (17O, 43Ca, and 67Zn NMR) combined with quantum chemistry modeling of NMR chemical shifts. NMR provides spectroscopic fingerprints that readily couple with quantum chemistry to identify a set of most probable solvation structures based on the best agreement between the theoretically predicted and experimentally measured values of chemical shifts. The multi-nuclear approach significantly enhances confidence that the correct solvation structures are identified due to the required simultaneous agreement between theory and experiment for multiple nuclear spins. Furthermore, quantum chemistry modeling provides a comparison of the solvation cluster formation energetics, allowing further refinement of the preferred solvation structures. It is shown that a range of solvation structures coexist in most of these electrolytes, with significant molecular motion and dynamic exchange among the structures. This level of solvation diversity correlates with the solubility of the electrolyte, with Zn(TFSI)2/THF exhibiting the lowest degree of each. Comparisons of analogous Ca2+ and Zn2+ solvation structures reveal a significant cation size effect that is manifested in significantly reduced cation-solvent bond lengths and thus stronger solvent bonding for Zn2+ relative to Ca2+. The strength of this bonding is further reduced by methylation of the cyclic ether ring. Solvation shells containing anions are energetically preferred in all the studied electrolytes, leading to significant quantities of contact ion pairs and consequently neutrally charged clusters. It is likely that the transport and interfacial de-solvation/re-solvation properties of these electrolytes are directed by these anion interactions. These insights into the detailed solvation structures, cation size, and solvent effects, including the molecular dynamics, are fundamentally important for the rational design of electrolytes in multivalent battery electrolyte systems.

Dataset Information

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and ¹H NMR Spectroscopy.

Publications

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and <sup>1</sup>H NMR Spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and 1H NMR Spectroscopy.

Publications

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and <sup>1</sup>H NMR Spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Understanding the Solvation Structure of Li-Ion Battery Electrolytes Using DFT-Based Computation and ¹H NMR Spectroscopy.