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An intuitive and efficient method for cell voltage prediction of lithium and sodium-ion batteries

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  • M. Saubanère

    (Institut Charles Gerhardt, CNRS—Université Montpellier 2, Place Eugène Bataillon, 34095 Montpellier, France
    Réseau Français sur le Stockage Electrochimique de l'Energie)

  • M. Ben Yahia

    (Institut Charles Gerhardt, CNRS—Université Montpellier 2, Place Eugène Bataillon, 34095 Montpellier, France
    Réseau Français sur le Stockage Electrochimique de l'Energie)

  • S. Lebègue

    (Réseau Français sur le Stockage Electrochimique de l'Energie
    Laboratoire de Cristallographie, Résonance Magnétique et Modélisations, Institut Jean Barriol, CNRS—Université de Lorraine, BP 239, Boulevard des Aiguillettes, 54506 Vandoeuvre-lès-Nancy, France)

  • M. -L. Doublet

    (Institut Charles Gerhardt, CNRS—Université Montpellier 2, Place Eugène Bataillon, 34095 Montpellier, France
    Réseau Français sur le Stockage Electrochimique de l'Energie)

Abstract

The voltage delivered by rechargeable Lithium- and Sodium-ion batteries is a key parameter to qualify the device as promising for future applications. Here we report a new formulation of the cell voltage in terms of chemically intuitive quantities that can be rapidly and quantitatively evaluated from the alkaliated crystal structure with no need of first-principles calculations. The model, which is here validated on a wide series of existing cathode materials, provides new insights into the physical and chemical features of a crystal structure that influence the material potential. In particular, we show that disordered materials with cationic intermixing must exhibit higher potentials than their ordered homologues. The present method is utilizable by any solid-state chemist, is fully predictive and allows rapid assessement of material potentials, thus opening new directions for the challenging project of material design in rechargeable batteries.

Suggested Citation

  • M. Saubanère & M. Ben Yahia & S. Lebègue & M. -L. Doublet, 2014. "An intuitive and efficient method for cell voltage prediction of lithium and sodium-ion batteries," Nature Communications, Nature, vol. 5(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6559
    DOI: 10.1038/ncomms6559
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