The solvation structure, transport properties and reduction behavior of carbonate-based electrolytes of lithium-ion batteries

Hou, Thomas Y.; Fong, Kara D.; Wang, Jingyang; Persson, Kristin A.

doi:10.1039/d1sc04265c

Cited by 53 publications

(44 citation statements)

References 95 publications

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“…This result is consistent with QM calculations that the binding energy of Li + –PC is approximately 10–50 kcal/mol smaller than that of Li + with other carbonate molecules. The alteration of solvation structures caused by solvents can finally result in the modification of electrolyte properties such as salt solubility, ionic transport, and electrochemical stability. , Solvents exhibiting strong coordination to cations favor the salt dissociation but inhibit fast desolvation and reversible reactions, ,,, while solvents with a moderate solvation ability function in the opposite way.…”

Section: Electrolyte Microstructuresmentioning

confidence: 99%

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

et al. 2022

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Rechargeable batteries have become indispensable implements in our daily life and are considered a promising technology to construct sustainable energy systems in the future. The liquid electrolyte is one of the most important parts of a battery and is extremely critical in stabilizing the electrode–electrolyte interfaces and constructing safe and long-life-span batteries. Tremendous efforts have been devoted to developing new electrolyte solvents, salts, additives, and recipes, where molecular dynamics (MD) simulations play an increasingly important role in exploring electrolyte structures, physicochemical properties such as ionic conductivity, and interfacial reaction mechanisms. This review affords an overview of applying MD simulations in the study of liquid electrolytes for rechargeable batteries. First, the fundamentals and recent theoretical progress in three-class MD simulations are summarized, including classical, ab initio, and machine-learning MD simulations (section 2). Next, the application of MD simulations to the exploration of liquid electrolytes, including probing bulk and interfacial structures (section 3), deriving macroscopic properties such as ionic conductivity and dielectric constant of electrolytes (section 4), and revealing the electrode–electrolyte interfacial reaction mechanisms (section 5), are sequentially presented. Finally, a general conclusion and an insightful perspective on current challenges and future directions in applying MD simulations to liquid electrolytes are provided. Machine-learning technologies are highlighted to figure out these challenging issues facing MD simulations and electrolyte research and promote the rational design of advanced electrolytes for next-generation rechargeable batteries.

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Section: Electrolyte Microstructuresmentioning

confidence: 99%

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

et al. 2022

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“…The remaining question is to understand the structure–property relationship. Recently, various studies ,− have attempted to build such correlations for electrolyte transport. However, most of these have limited applicability given the use of self-diffusivities instead of the Stefan–Maxwell diffusivities.…”

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confidence: 99%

Toward Bottom-Up Understanding of Transport in Concentrated Battery Electrolytes

et al. 2022

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Bottom-up understanding of transport describes how molecular changes alter species concentrations and electrolyte voltage drops in operating batteries. Such an understanding is essential to predictively design electrolytes for desired transport behavior. We herein advocate building a structure−property− performance relationship as a systematic approach to accurate bottom-up understanding. To ensure generalization across salt concentrations as well as different electrolyte types and cell configurations, the property−performance relation must be described using Newman's concentrated solution theory. It uses Stefan−Maxwell diffusivity, ij , to describe the role of molecular motions at the continuum scale. The key challenge is to connect ij to the structure. We discuss existing methods for making such a connection, their peculiarities, and future directions to advance our understanding of electrolyte transport.

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“…Such a replacement of water molecules with organic additive molecules and anions is in good agreement with recent reports. 14,15,26–28,37,40–42 Whether this exchange of solvent for anion molecules in the cation solvation shell in aqueous electrolytes follows a mechanism similar to the “ entry – exit ” type pathway proposed for carbonate-based electrolytes 43 will be pursued in future studies. Furthermore, quantum chemical calculations were performed to verify the stability of Zn 2+ –(H 2 O/PC/OTf − ) pairs.…”

Section: Resultsmentioning

confidence: 99%

Two for one: propylene carbonate co-solvent for high performance aqueous zinc-ion batteries – remedies for persistent issues at both electrodes

et al. 2022

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The solvation structure, transport properties and reduction behavior of carbonate-based electrolytes of lithium-ion batteries

Abstract: Despite the extensive employment of binary/ternary mixed-carbonate electrolytes (MCEs) for Li-ion batteries, the role of each ingredient with regards to the solvation structure, transport properties, and reduction behavior is not...

Cited by 53 publications

References 95 publications

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

Toward Bottom-Up Understanding of Transport in Concentrated Battery Electrolytes

Two for one: propylene carbonate co-solvent for high performance aqueous zinc-ion batteries – remedies for persistent issues at both electrodes

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