Artificial neural network-enabled approaches toward mass balancing and cell optimization of lithium dual ion batteries

Pattavathi, Bibin; Surendran, Vishnu; Palani, S.; Shaijumon, Manikoth M.

doi:10.1016/j.est.2023.107878

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…Among the advanced energy storage systems, dual-ion batteries (DIBs) show great promise for grid-scale energy storage. − Graphite, the most extensively researched cathode material for nonaqueous DIBs, demands high operating voltage. Nevertheless, using nonaqueous electrolytes and ionic liquids raises concerns regarding flammability and cost. , By expanding the ESW with WiSE electrolytes, we, for the first time, report an aqueous organic dual ion battery with PDI-Urea-as anode along with a graphite cathode.…”

Section: Introductionmentioning

confidence: 99%

Polyimide-Based Aqueous Potassium Energy Storage Systems Using Concentrated WiSE Electrolyte

Vardhini,

Dilip,

Kumar

et al. 2024

ACS Appl. Mater. Interfaces

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Aqueous batteries are considered as promising alternative power sources due to their eco-friendly, cost-effective, and nonflammable attributes. Employing organic-based electrode materials offers further advantages toward building greener and sustainable systems, owing to their tunability and environmental friendliness. In order to enhance the energy and power densities, superconcentrated aqueous electrolytes, such as water-in-salt electrolytes (WiSE), have renewed the interest in aqueous batteries due to their enhanced stability and much wider electrochemical stability window (>1.23 V) compared with the traditional aqueous electrolytes. Here, we present a perylene diimide-based electrode material (PDI-Urea) as an appealing anode for aqueous potassium energy storage systems and investigate their electrochemical performance in three WiSE electrolytes, namely, 30 M potassium acetate, 40 M potassium formate and 30 M potassium bis(fluorosulfonyl)imide (KFSI). To explore the potential of PDI-Urea for potassium-based electrochemical energy systems, we fabricated full cell devices such as aqueous potassium dual-ion battery (APDIB) and aqueous K-ion battery (AKIB) and studied their electrochemical properties with 30 M KFSI electrolyte. The full cell K-ion battery, using a PBA cathode, exhibited excellent electrochemical performance with good rate capability and impressive capacity retention of 91% upon 1000 cycles. Further, the reaction mechanism of the electrodes is systematically analyzed using ex-situ studies.

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Section: Introductionmentioning

confidence: 99%

Polyimide-Based Aqueous Potassium Energy Storage Systems Using Concentrated WiSE Electrolyte

Vardhini,

Dilip,

Kumar

et al. 2024

ACS Appl. Mater. Interfaces

Self Cite

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“…25,33 The artificial neural network was employed in the prediction of a charge−discharge profile at any given current density for DIBs. 34 We have also carried out an efficient and accurate screening of polyaromatic hydrocarbon cathode materials and salts considering voltage and volume change prediction. 35 Moreover, we have also shown the accurate prediction of the electrochemical window potential for ionic liquid electrolytes for DIB applications using ML.…”

Section: Introductionmentioning

confidence: 99%

Integration of Density Functional Theory and Machine Learning for Electrolyte Optimization in High-Voltage Dual-Ion Battery Design

Paul,

Das,

Manna

et al. 2024

ACS Appl. Mater. Interfaces

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Designing dual-ion batteries (DIBs) by using various electrolytes through experiments or computationally is highly time-consuming and needs high-cost sophisticated resources. Here, we have utilized the ultrafast screening capability of machine learning (ML) to search for suitable salt-electrolytes toward the design of DIBs, choosing voltage as the desirable descriptor. Considering 50 different salts and their suitable staging mechanisms, the XGBoost Regressor ML model has been found to perform with remarkable accuracy. This is further validated by density functional theory, cross-validation, and experimental findings. An interpretable ML technique has been employed for local and global feature analysis to interpret the ML predicted results, underscoring the importance of choosing input features. This ML assisted DIB design approach has the potential to explore unknown salt-electrolytes that have yet to be tested in DIBs. Finally, we introduce the predicted voltages for all of the salt-electrolyte combinations as well as their probable staging mechanism. We signify the absence of a general trend in the predicted voltages, as various combinations of cations and anions are found to deliver unique voltages. Our study can guide researchers toward tuning constituent salts as well as staging mechanisms for the design of efficient DIBs.

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A Review of Anode Materials for Dual-Ion Batteries

Wu,

Luo,

Wang

et al. 2024

Nano-Micro Lett.

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Distinct from "rocking-chair" lithium-ion batteries (LIBs), the unique anionic intercalation chemistry on the cathode side of dual-ion batteries (DIBs) endows them with intrinsic advantages of low cost, high voltage, and eco-friendly, which is attracting widespread attention, and is expected to achieve the next generation of large-scale energy storage applications. Although the electrochemical reactions on the anode side of DIBs are similar to that of LIBs, in fact, to match the rapid insertion kinetics of anions on the cathode side and consider the compatibility with electrolyte system which also serves as an active material, the anode materials play a very important role, and there is an urgent demand for rational structural design and performance optimization. A review and summarization of previous studies will facilitate the exploration and optimization of DIBs in the future. Here, we summarize the development process and working mechanism of DIBs and exhaustively categorize the latest research of DIBs anode materials and their applications in different battery systems. Moreover, the structural design, reaction mechanism and electrochemical performance of anode materials are briefly discussed. Finally, the fundamental challenges, potential strategies and perspectives are also put forward. It is hoped that this review could shed some light for researchers to explore more superior anode materials and advanced systems to further promote the development of DIBs.

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Artificial neural network-enabled approaches toward mass balancing and cell optimization of lithium dual ion batteries

Cited by 4 publications

References 51 publications

Polyimide-Based Aqueous Potassium Energy Storage Systems Using Concentrated WiSE Electrolyte

Polyimide-Based Aqueous Potassium Energy Storage Systems Using Concentrated WiSE Electrolyte

Integration of Density Functional Theory and Machine Learning for Electrolyte Optimization in High-Voltage Dual-Ion Battery Design

A Review of Anode Materials for Dual-Ion Batteries

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