(Keynote) Multiscale Three-Dimensional Modeling to the Rescue of Electrochemical Energy Devices

Monday, 30 May 2016: 14:00
Aqua Salon E (Hilton San Diego Bayfront)
A. A. Franco (LRCS - Université de Picardie Jules Verne & CNRS UMR 7314, LRCS (CNRS & UPJV), France; RS2E & ALISTORE ERI)
In this lecture I provide a comprehensive review on the fundamentals and practical aspects of an in-house computational modeling approach we are developing since 14 years [1-6], for the analysis of physicochemical mechanisms in electrochemical devices for energy conversion and storage such as fuel cells and rechargeable batteries [7-8].

The key feature of this approach is that it allows linking the chemical/microstructural properties of materials and components with their macroscopic efficiency and durability at the cell level, by utilizing a multi-scale framework. Since recently, the approach introduces some new capabilities (Figure):

- the possibility of simulating ionic/electronic and reactants/products transport and elementary reaction steps with an immersive three-dimensional resolution  (e.g. reactions leading to the formation of lithium peroxide during a Li-O2 battery discharge inside a three-dimensional pore network) through spatially-resolved Kinetic Monte Carlo (KMC) models [9-11];

- the possibility of coupling numerically "on the fly" these three-dimensional KMC simulators with continuum models (i.e. based on  a set of coupled partial differential equations) describing the electrochemical operation of a complete cell, by considering relevant mass and energy conservations supported on parameters extracted from the KMC simulations and capturing the microstructural properties of the components materials [12-14].

The resulting multi-paradigm simulation framework is embedded into a single in-house software developed by us in Python/Matlab languages and called MS LIBER-T [15] which permits simulating electrochemical observables (e.g. discharge/charge curves in batteries) by tracking the three-dimensional behavior of the reactions and transport processes in the porous electrodes.

Moreover, by taking into account the on-the-fly feedback between performance models and elementary kinetic models describing materials degradation, our approach is able to predict the cells performance evolution and durability as function of operation conditions (e.g. applied current density or temperature) [9,16].

The analysis and prediction capabilities of our approach is illustrated in this lecture through concrete examples in relation to the R&D on lithium air, lithium sulfur and redox flow batteries, as well as polymer electrolyte membrane fuel cells. More particularly, it is demonstrated that three-dimensional simulations provide useful guidelines for the optimized design of the porous electrodes architectures.

Finally, I discuss remaining methodological and algorithmic challenges in the development of such a type of approaches to stimulate future technology breakthroughs in electrochemical energy devices. 


[1]   A.A. Franco, P. Schott, C. Jallut, B. Maschke, J. Electrochem. Soc.153(6) (2006) A1053.

[2]   A.A. Franco, P. Schott, C. Jallut, B. Maschke, Fuel Cells7 (2007) 99.

[3]   A.A. Franco, RSC Advances3 (32) (2013) 13027.

[4]   R. Ferreira de Morais, D. Loffreda, P. Sautet, A. A. Franco, Electrochim. Acta56 (28) (2011) 10842.

[5]   A.A. Franco, in:  Physical Multiscale Modeling and Numerical Simulation of Electrochemical Devices for Energy Conversion and Storage: From Theory to Engineering to Practice. A.A. Franco, M.L. Doublet, W.G. Bessler (Eds.), Springer (2015).

[6]   A.A. Franco, Multiscale modeling of electrochemical devices for energy conversion and storage, book chapter in: Encyclopedia of Applied Electrochemistry.  R. Savinell, K.I. Ota, G. Kreysa (Eds.), Springer (2014).

[7]   A.A. Franco (Ed.), Rechargeable Lithium Batteries: From Fundamentals to Applications, Woodhead/Elsevier Science (2015).

[8]   A.A. Franco (Ed.), Polymer Electrolyte Fuel Cells: Science, Applications and Challenges, CRC Press/Pan Stanford/Francis & Taylor (2013).

[9]   M.A. Quiroga, K. Malek, A.A. Franco, J. Electrochem. Soc.163 (2) (2016) F59.

[10] M.A. Quiroga, A.A. Franco, J. Electrochem. Soc.162 (7) (2015) E73.

[11] G. Blanquer, Y. Yin, M.A. Quiroga, A.A. Franco, J. Electrochem. Soc., 163 (3) (2016) A329.

[12] K. H. Xue, E. McTurk, L. Johnson, P.G. Bruce,  A.A. Franco, J. Electrochem. Soc.162 (4) (2015) A614.

[13] K.H. Xue, T.K. Nguyen, A.A. Franco, J. Electrochem. Soc.161 (8) (2014) E3028.

[14] A.A. Franco, K.H. Xue, ECS Journal of Solid State Science and Technology2 (10) (2013) M3084.

[15] www.modeling-electrochemistry.com

[16] K. Malek, A.A. Franco, J. Phys. Chem. B115 (2011) 8088.