Publication Date
2025
Document Type
Dissertation/Thesis
First Advisor
Li, Tao
Degree Name
Ph.D. (Doctor of Philosophy)
Legacy Department
Department of Chemistry and Biochemistry
Abstract
The solvation structure of water-in-salt electrolytes was thoroughly studied, and two competing structures, anion solvated structure and anion network, were well-defined in recent publications. To further reveal the solvation structure in those highly concentrated electrolytes, particularly the influence of solvent, methanol was chosen as the solvent for this proposed study. In this work, small-angle X-ray scattering, small-angle neutron scattering, Fourier-transform infrared spectroscopy, and Raman spectroscopy were utilized to obtain global and local structural information. With the concentration increment, the anion network formed by TFSI became the dominant structure. Meanwhile, the hydrogen bonds among methanol were interrupted by the TFSI anion and formed a new connection with them. Molecular dynamic simulations with two different force fields (GAFF and OPLS-AA) are tested, and GAFF agreed with synchrotron small-angle X-ray scattering/wide-angle X-ray scattering (SAXS/WAXS) and provided insightful information about molecular/ion scale solvation structure. This article not only deepens the understanding of the solvation structure in highly concentrated solutions, but more importantly, it provides additional strong evidence for utilizing SAXS/WAXS to validate molecular dynamics simulations.To further understand the solvation structure of different solvents in those highly concentrated electrolytes, molecular dynamics simulations and SAXS/WAXS were combined to study the solvation structures of LiTFSI in acetonitrile, methanol, and water. Hydrogen bonding in water and methanol encourage the anion to form clusters, while methyl groups in methanol and acetonitrile disrupt the nanoscale ordering of TFSI anions. Those could explain the phenomenon that the LiTFSI’s acetonitrile electrolyte only has one peak while the methanol and water electrolyte have two peaks. Understanding the solvation structure of a specific electrolyte alone is insufficient, the overarching objective is to correlate structural attributes with performance metrics. Machine learning can be employed to analyze, predict, and optimize the selection of future electrolytes. Given its data-driven nature, machine learning requires large and high-quality datasets for robust training. Consequently, access to reliable data is important to ensure its efficacy. Meanwhile, the sample preparation took too much time and was not cost-friendly. A High-Throughput Electrolyte Data Collection (HEDC) system was developed to meet this requirement. With the proper set-up, HEDC could obtain more than 600 SAXS/WAXS data within three hours, which will accelerate the speed of data collection. The final part of this dissertation presents the SAXS measurements using a flow cell setup, where reduced flux and shorter exposure times minimized radiation damage. SAXS results confirmed a clear concentration dependent structural evolution: high concentration electrolytes exhibited large aggregates which in nanometer scale, while low concentration electrolyte remained homogeneous. To further validate these findings, TEM with liquid cell provided direct real-space imaging, confirming the presence of aggregates in concentrated electrolyte. The strong agreement between SAXS and TEM reinforces the understanding of solvation structure evolution in imide-based electrolytes. Moreover, molecular dynamic simulations based on Cahn-Hilliard equation confirmed the phase separation is preferred to happen in high concentrations, where lower concentrations electrolyte remain the homogeneous.
Recommended Citation
Lyu, Xingyi, "Understanding the Solvation Structure of Electrolytes Using Advanced Synchrotron Small-Angle X-Ray Scattering" (2025). Graduate Research Theses & Dissertations. 8074.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/8074
Extent
121 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
