Data-driven designs and multi-scale simulations of enhanced ion transport in low-temperature operation for lithium-ion batteries

Chang, Hongjun; Park, Yoojin; Kim, Ju-Hee; Park, Seowan; Kim, Byung Gon; Moon, Janghyuk

doi:10.1007/s11814-022-1364-0

Cited by 4 publications

(4 citation statements)

References 55 publications

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“…Similarly, Chang and colleagues used MD simulation and machine learning methods to design the electrolyte working at temperatures below freezing point water. [ 175 ] They also discovered that some ternary compositions with additives like MA, MF, Bn, and Pn showed higher conductivity than binary electrolytes, especially at low temperatures. After the theoretical screening, experimental characterizations are conducted at −10 °C and a discharge rate of 4 C, showing that LIBs based on EC/EMC/MA/MF electrolytes have a higher capacity retention rate than those with only EC/EMC electrolytes.…”

Section: Molecular Interactions and Atomic Scale Behaviors Of Electro...mentioning

confidence: 99%

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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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Section: Molecular Interactions and Atomic Scale Behaviors Of Electro...mentioning

confidence: 99%

“…The voltage polarization of batteries with EC/EMC/MA/MF electrolytes was found lower than those using EC/EMC electrolytes. [ 175 ]…”

Section: Molecular Interactions and Atomic Scale Behaviors Of Electro...mentioning

confidence: 99%

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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“…However, the SEI layer may trap Li + ions, resulting in irreversible capacity loss simultaneously . Recently, several computational modeling approaches, ranging from the electronic level to the atomic/molecular scale, have been widely applied in various fields including catalysis and energy materials. , Table summarizes various computational methods with respect to the simulation time/length scale, key features, and limitations. − Each computational method with a different simulation time and length scale focuses on its distinctive features, and consequently, limitations are also evident. In this Perspective, we present the history of strategies used to model the anode/electrolyte interface structure in the field of atomic and molecular simulations and propose a perspective for interface modeling in the anode materials in lithium-ion batteries.…”

Section: Introductionmentioning

confidence: 99%

“…4 Recently, several computational modeling approaches, ranging from the electronic level to the atomic/molecular scale, have been widely applied in various fields including catalysis 5 and energy materials. 6,7 Table 1 summarizes various computational methods with respect to the simulation time/length scale, key features, and limitations. 8−10 Each computational method with a different simulation time and length scale focuses on its distinctive features, and consequently, limitations are also evident.…”

Section: Introductionmentioning

confidence: 99%

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries

You,

Yoon,

et al. 2024

Langmuir

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A key issue in lithium-ion batteries is understanding the solid electrolyte interphase (SEI) resulting from a reductive reaction on the anode/ electrolyte interface. The presence of the SEI layer affects the transport behavior of the ions and electrons between the anode and electrolyte. Despite the influence on interfacial properties, the formation and evolution mechanism of the SEI layer are unclear owing to their complexity and dynamic nature. Atomistic-scale simulations have promoted the understanding of the reaction mechanism on the anode/ electrolyte interface, the formation and evolution of the SEI layer, and their fundamental properties. This Perspective discusses the modeling and interpretations of anode/SEI/electrolyte interfaces through computational methods at the atomicscale and highlights interfacial modeling techniques for a realistic interface design, which can overcome the limited time and length scale with high accuracy.

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Solid Electrolyte: Strategies to Address the Safety of All Solid‐State Batteries

Park

Han

Chaudhary

et al. 2023

Adv Energy and Sustain Res

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Lithium metal batteries (LMBs) are in the spotlight as a next‐generation battery due to their high theoretical capacity. However, LMBs still suffer from inferior cycle stability owing to dendritic lithium (Li) growth during Li plating and stripping, leading to battery explosion. To solve this problem, solid electrolytes have emerged as a promising candidate by suppressing the dendritic Li growth. Despite numerous efforts, however, many challenges, such as low ionic conductivity, air stability, space charge layer, and contact loss issues, have been encountered. This review aims to provide the current challenges and new insights of solid electrolytes and then explore optimal solutions for next‐generation solid electrolytes.

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Data-driven designs and multi-scale simulations of enhanced ion transport in low-temperature operation for lithium-ion batteries

Cited by 4 publications

References 55 publications

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

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

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries

Solid Electrolyte: Strategies to Address the Safety of All Solid‐State Batteries

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