[SY-F12] Multiscale mean-field modelling of mechanochemical processes in heterogeneous materials for energy storage
Performance enhancement of energy storage devices, e.g. batteries, requires careful selection of materials. The microstructure of such materials can undergo a complex electro-chemo-mechanical cycling during battery exploitation, which involves extreme volumetric expansion of the active material during the chemical reaction. The expansion is causing mechanical stress, which, in turn, influences the kinetics of chemical reactions even up to their arrest [3]. Thus, to predict the mechanochemical behaviour of a multi-material battery electrode, both the multi-physics phenomena and microstructure must be taken into account.
Up to now, the major focus has been on development of coupling models between mechanics, diffusion and chemical reactions, e.g. [4], particularly, chemical reactions, such as lithiation and oxidation, that take place at a surface, e.g. [1-2]. When localised reactions are modelled, the thermodynamic consistency has to be maintained and the velocity of the chemical reaction front should not violate the entropy production inequality and the balance laws. One such model is based on the chemical affinity tensor [2]. This model was used to predict the kinetics and the arrest of the reaction front in free-standing Si particles of a battery anode [5].
The model presented in this talk builds on [5] and accounts for the lithiation kinetics of a collection of particles inside an effective matrix material. The battery microstructure is modelled using the multiscale mean-field framework based on the incremental Mori-Tanaka method. This is the first application of a multiscale mean-field technique to modelling lithiation reaction front kinetics in a complex anode microstructure within the finite-strain framework, and to linking the intraparticle kinetics with the macroscopic response of the battery.
Acknowledgements
Financial support from the EU H2020 project Sintbat (685716) is gratefully acknowledged.
References
[1] ZW Cui, F Gao, JM Qu (2013) J Mech Phys Solids 61:293-310
[2] AB Freidin, EN Vilchevskaya, IK Korolev (2014) Int J Eng Sci 83:57-75
[3] K van Havenbergh, S Turner, N Marx, G van Tendeloo (2016) Energy Technol 4:1005-1012
[4] VI Levitas, H Attariani (2014) J Mech Phys Solids 69:84-111
[5] M Poluektov, AB Freidin, L Figiel (2018) Int J Eng Sci accepted
Up to now, the major focus has been on development of coupling models between mechanics, diffusion and chemical reactions, e.g. [4], particularly, chemical reactions, such as lithiation and oxidation, that take place at a surface, e.g. [1-2]. When localised reactions are modelled, the thermodynamic consistency has to be maintained and the velocity of the chemical reaction front should not violate the entropy production inequality and the balance laws. One such model is based on the chemical affinity tensor [2]. This model was used to predict the kinetics and the arrest of the reaction front in free-standing Si particles of a battery anode [5].
The model presented in this talk builds on [5] and accounts for the lithiation kinetics of a collection of particles inside an effective matrix material. The battery microstructure is modelled using the multiscale mean-field framework based on the incremental Mori-Tanaka method. This is the first application of a multiscale mean-field technique to modelling lithiation reaction front kinetics in a complex anode microstructure within the finite-strain framework, and to linking the intraparticle kinetics with the macroscopic response of the battery.
Acknowledgements
Financial support from the EU H2020 project Sintbat (685716) is gratefully acknowledged.
References
[1] ZW Cui, F Gao, JM Qu (2013) J Mech Phys Solids 61:293-310
[2] AB Freidin, EN Vilchevskaya, IK Korolev (2014) Int J Eng Sci 83:57-75
[3] K van Havenbergh, S Turner, N Marx, G van Tendeloo (2016) Energy Technol 4:1005-1012
[4] VI Levitas, H Attariani (2014) J Mech Phys Solids 69:84-111
[5] M Poluektov, AB Freidin, L Figiel (2018) Int J Eng Sci accepted