Effect of water on the behaviour of lithium and superoxide ions in aprotic solvents

Sivakov, Vyacheslav; Павлов, С. В.; Смирнов, В. С.; Kislenko, Sergey A.

doi:10.1039/d1cp03429d

Cited by 4 publications

(15 citation statements)

References 43 publications

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“…To reveal the dynamical properties of solvation shells, we calculated the residence time t res of molecules in the first coordination spheres of different ions as well as the coordination number (CN) of solution components. 45 Residence times were calculated from the initial slope of the autocorrelation function n(t): 30,45 nðtÞ…”

Section: àmentioning

confidence: 99%

“…Data processing methodology is described in more detail in Section 2.2 of our recent work. 30 Additionally, potentials of mean force between Li + and O 2 À ions were obtained for 4 different solutions with volume fractions of Pyr 14 TFSI equal to 0, 0.3, 0.6 and 1 for deeper characterization of association reaction thermodynamics. For this, we used different systems.…”

Section: àmentioning

confidence: 99%

“…Such a rather high value of the potential indicates the activation nature of the exchange of DME molecules in the solvation shell, which is consistent with our recent results. 30 For Pyr 14 + , there are no pronounced barriers on the way to approach the lithium ion; the forces of Coulomb repulsion between like charges bring the main contribution to the potential. At the same time, the TFSI À anion has a barrier of about 3-3.5 kT, which allows us to speak about the activation mode of the association of this anion with the lithium cation.…”

Section: Structures Of Solvation Shellsmentioning

confidence: 99%

“…At the same time, the molecular dynamics (MD) method was shown to be a very effective tool for revealing particular mechanisms of the effects of solvent composition on the solvation processes on a molecular scale. With regard to solvation processes in the context of Li-O 2 batteries, MD was previously used to investigate the behaviour of ions both in bulk [26][27][28][29][30] and at interfaces. [31][32][33][34][35] In the current work, using molecular dynamics simulations, we study the effect of the Pyr 14 TFSI ionic liquid concentration in organic solvent DME on the structure and stability of solvation shells around a number of ions involved in the oxygen reduction reaction (Li + and O 2…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effect of a mixture of an ionic liquid and organic solvent on oxygen reduction reaction kinetics

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et al. 2022

Phys. Chem. Chem. Phys.

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Section: àmentioning

confidence: 99%

Section: àmentioning

confidence: 99%

Section: Structures Of Solvation Shellsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The effect of a mixture of an ionic liquid and organic solvent on oxygen reduction reaction kinetics

Павлов

Danilova

Sivakov

et al. 2022

Phys. Chem. Chem. Phys.

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Decoding Electrochemical Processes of Lithium‐Ion Batteries by Classical Molecular Dynamics Simulations

Tan,

Chen,

Zhang

et al. 2024

Advanced Energy Materials

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Lithium‐ion batteries (LIBs) have played an essential role in the energy storage industry and dominated the power sources for consumer electronics and electric vehicles. Understanding the electrochemistry of LIBs at the molecular scale is significant for improving their performance, stability, lifetime, and safety. Classical molecular dynamics (MD) simulations could directly capture the atomic and molecular motions and thus provide dynamic insights into the electrochemical processes and ion transport in LIBs during charging and discharging that are usually challenging to observe experimentally, which is momentous in developing LIBs with superb performance. This review discusses developments in MD approaches using non‐reactive force fields, reactive force fields, and machine learning potential for modeling chemical reactions and transport of reactants in the electrodes, electrolytes, and electrode‐electrolyte interfaces. It also comprehensively discusses how molecular interactions, structures, transport, and reaction processes affect electrode stability, energy capacity, and interfacial properties. Finally, the remaining challenges and envisioned future routes are commented on for high‐fidelity, effective simulation methods to decode the invisible interactions and chemical reactions in LIBs.

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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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Effect of water on the behaviour of lithium and superoxide ions in aprotic solvents

Abstract: The aprotic lithium-air battery is a promising candidate for the next-generation energy storage system, but its practical performance is still low. The addition of water to an electrolyte can substantially...

Cited by 4 publications

References 43 publications

The effect of a mixture of an ionic liquid and organic solvent on oxygen reduction reaction kinetics

The effect of a mixture of an ionic liquid and organic solvent on oxygen reduction reaction kinetics

Decoding Electrochemical Processes of Lithium‐Ion Batteries by Classical Molecular Dynamics Simulations

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

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