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Wan S, Ma W, Wang Y, Xiao Y, Chen S. Electrolytes Design for Extending the Temperature Adaptability of Lithium-Ion Batteries: from Fundamentals to Strategies. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2311912. [PMID: 38348797 DOI: 10.1002/adma.202311912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/16/2024] [Indexed: 02/25/2024]
Abstract
With the continuously growing demand for wide-range applications, lithium-ion batteries (LIBs) are increasingly required to work under conditions that deviate from room temperature (RT). However, commercial electrolytes exhibit low thermal stability at high temperatures (HT) and poor dynamic properties at low temperatures (LT), hindering the operation of LIBs under extreme conditions. The bottleneck restricting the practical applications of LIBs has promoted researchers to pay more attention to developing a series of innovative electrolytes. This review primarily covers the design of electrolytes for LIBs from a temperature adaptability perspective. First, the fundamentals of electrolytes concerning temperature, including donor number (DN), dielectric constant, viscosity, conductivity, ionic transport, and theoretical calculations are elaborated. Second, prototypical examples, such as lithium salts, solvent structures, additives, and interfacial layers in both liquid and solid electrolytes, are presented to explain how these factors can affect the electrochemical behavior of LIBs at high or low temperatures. Meanwhile, the principles and limitations of electrolyte design are discussed under the corresponding temperature conditions. Finally, a summary and outlook regarding electrolytes design to extend the temperature adaptability of LIBs are proposed.
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Affiliation(s)
- Shuang Wan
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Electrochemical Process and Technology of Materials, Beijing University of Chemical Technology, Beijing, 10029, China
| | - Weiting Ma
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Electrochemical Process and Technology of Materials, Beijing University of Chemical Technology, Beijing, 10029, China
| | - Yutong Wang
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
| | - Ying Xiao
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Electrochemical Process and Technology of Materials, Beijing University of Chemical Technology, Beijing, 10029, China
| | - Shimou Chen
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Electrochemical Process and Technology of Materials, Beijing University of Chemical Technology, Beijing, 10029, China
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Cortazar E, Usobiaga A, Fernández LA, de DA, Madariaga JM. Automation of a procedure to find the polynomial which best fits (kappa, c1, c2, T) data of electrolyte solutions by non-linear regression analysis using MATHEMATICA software. COMPUTERS & CHEMISTRY 2002; 26:253-64. [PMID: 11868914 DOI: 10.1016/s0097-8485(01)00115-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
A MATHEMATICA package, 'CONDU.M', has been developed to find the polynomial in concentration and temperature which best fits conductimetric data of the type (kappa, c, T) or (kappa, c1, c2, T) of electrolyte solutions (kappa: specific conductivity; ci: concentration of component i; T: temperature). In addition, an interface, 'TKONDU', has been written in the TCL/Tk language to facilitate the use of CONDU.M by an operator not familiarised with MATHEMATICA. All this software is available on line (UPV/EHU, 2001). 'CONDU.M' has been programmed to: (i) select the optimum grade in c1 and/or c2; (ii) compare models with linear or quadratic terms in temperature; (iii) calculate the set of adjustable parameters which best fits data; (iv) simplify the model by elimination of 'a priori' included adjustable parameters which after the regression analysis result in low statistical significance; (v) facilitate the location of outlier data by graphical analysis of the residuals; and (vi) provide quantitative statistical information on the quality of the fit, allowing a critical comparison among different models. Due to the multiple options offered the software allows testing different conductivity models in a short time, even if a large set of conductivity data is being considered simultaneously. Then, the user can choose the best model making use of the graphical and statistical information provided in the output file. Although the program has been initially designed to treat conductimetric data, it can be also applied for processing data with similar structure, e.g. (P, c, T) or (P, c1, c2, T), being P any appropriate transport, physical or thermodynamic property.
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Affiliation(s)
- E Cortazar
- Department of Analytical Chemistry, University of the Basque Country, Bilbao, Spain.
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Kondo K, Sano M, Hiwara A, Omi T, Fujita M, Kuwae A, Iida M, Mogi K, Yokoyama H. Conductivity and Solvation of Li+ Ions of LiPF6 in Propylene Carbonate Solutions. J Phys Chem B 2000. [DOI: 10.1021/jp000142f] [Citation(s) in RCA: 161] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kazutaka Kondo
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Mitsuru Sano
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Akio Hiwara
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Takehiko Omi
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Miho Fujita
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Akio Kuwae
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Masayasu Iida
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Koichi Mogi
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
| | - Haruhiko Yokoyama
- Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan, Functional Materials Laboratory, Mitui Chemicals, Sodegaura 299-0265, Japan, Institute of Natural Sciences, Nagoya City University, Nagoya 467-8501, Japan, Department of Chemistry, Nara Women's University, Nara 630-8506, Japan, Department of Molecular and Material Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan, and Department of Chemistry, Yokohama City University, Yokohama 236-0027, Japan
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