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Lithium-Sulfur Battery: Design, Characterization, and Physically-based Modeling

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Lithium-Sulfur Battery: Design, Characterization, and Physically-based Modeling ( lithium-sulfur-battery-design-characterization-and-physicall )

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[230] [231] [232] [233] [234] [235] [236] [237] [238] [239] [240] [241] [242] A. P. Schmidt, M. Bitzer, A. W. Imre, and L. Guzzella. Model-based distinction and quantification of capacity loss and rate capability fade in Li-ion batteries. Journal of Power Sources 195, 7634–7638 (2010). S. Renganathan, G. Sikha, S. Santhanagopalan, and R. E. White. Theoretical Anal- ysis of Stresses in a Lithium Ion Cell. Journal of The Electrochemical Society 157, A155–A163 (2010). D. G. Goodwin, H. K. Moffat, R. L. Speth, et al. Cantera: An object-oriented software toolkit for chemical kinetics, thermodynamics, and transport processes. Available at http://www.cantera.org (2013). Version 2.0.2. I. Berg et al. muparser - fast math parser library. Available at http://muparser. beltoforion.de/ (2013). Version 2.2.2. Konrad-Zuse-Zentrum für Informationstechnik Berlin. Limex. Available at http://www.zib.de/de/numerik/software/codelib/ivpode.html (2004). Ver- sion 4.3A. P. Deuflhard, E. Hairer, and J. Zugck. One-step and extrapolation methods for differential-algebraic systems. Numerische Mathematik 51, 501–516 (1987). J. H. Ferziger and M. Peric ́. Computational methods for fluid dynamics. Third edition. Springer (2002). W. G. Bessler. Rapid Impedance Modeling via Potential Step and Current Relaxation Simulations. Journal of The Electrochemical Society 154, B1186–B1191 (2007). W. M. Haynes and D. R. Lide (Eds.). CRC Handbook of Chemistry and Physics. 92nd edition. CRC Press (2012). G. B. Less, J. H. Seo, S. Han, A. M. Sastry, J. Zausch, A. Latz, S. Schmidt, C. Wieser, D. Kehrwald, and S. Fell. Micro-Scale Modeling of Li-Ion Batteries: Pa- rameterization and Validation. Journal of The Electrochemical Society 159, A697– A704 (2012). P. R. Bevington and D. K. Robinson. Data Reduction and Error Analysis for the Physical Sciences. Third edition. McGraw-Hill (2002). E. Jones, T. Oliphant, P. Peterson, et al. SciPy: Open source scientific tools for Python. Available at http://www.scipy.org/ (2001–2014). Version 0.13. A. J. Durán, M. Pérez, and J. L. Varona. The Misfortunes of a Trio of Mathematicians Using Computer Algebra Systems. Can We Trust in Them? Notices of the AMS 61, 1249–1252 (2014). 173

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