Multiscale Modeling of Electrochemical Energy Conversion and Storage

Research activities

Professor Franco's research activities are mainly devoted to the deep understanding of the operation principles of electrochemical devices for energy storage and conversion, such as rechargeable batteries, supercapacitors, fuel cells and electrolyzers. In strong interaction with experimentalists, his approach consists in developing novel multiphysics, multiscale and multiparadigm models describing the materials, components and devices behavior in conditions representative of real applications.

This approach is articulated in two strongly connected axes (see links on the right of this page or the button below for more details):

- specific modeling and simulation techniques are used to calculate activity, stability, selectivity, physico-chemical and structural properties of the materials towards electrochemical reactions and transport processes which are relevant for the devices operation. These techniques include:

ab initio approach (Density Functional Theory) to predict the electrochemical pathways and associated elementary energetics of the single reaction steps;
Monte Carlo approach to predict the morphology of multimetallic nanoparticles, particulary in relation with degradation and adsorbates-induced reconstruction phenomena;
mean-field elementary kinetics approach to predict experimental observables (e.g. electrode potential) as function of the nanostructural and chemical properties of the materials (via the DFT-generated data);
Statistical Mechanics approach / nanoscale electrified interface theory, developed by Prof. Franco himself, to describe the structure under non equilibrium conditions of the electrochemical double layer at the vicinity of active materials;
mesoscopic techniques (e.g. based on Monte Carlo approach) to predict ("reconstruct") the mesoscale structural properties of the electrodes;

- novel algorithms and computational software are developed by integrating the ingredients extracted from the atomistic and molecular approaches in macroscopic electrochemical device models allowing to predict the impact the physico-chemical and structural properties of the used materials and components onto the overall cell response (observables). Prof. Franco is the inventor of two generations of simulation packages doing this:

MEMEPhys (from the French spelling Modèle Electrochimique MultiEchelle Physique) a simulation package he invented in 2002, and which is mainly devoted to the simulation of PEM Fuel Cells and PEM Water Electrolyzers. This pioneering model in the field of multiscale simulation of electrochemical energy conversion devices and extensively published by Prof. Franco since 2003, allowed progressing on the understanding of competitions and synergies between detailed electrochemical reactions, transport phenomena and materials degradation mechanisms. MEMEPhys capabilities are however penalized by its dependence on commercial toolboxes and numerical solvers (Matlab/Simulink) as well as its not "open" software (freeware) character.
MS LIBER-T (Multiscale Simulator of Lithium Ion Batteries and Electrochemical Reactor Technologies) devoted to the numerical simulation of both electrochemical devices for energy conversion (fuel cells, electrolyzers) and storage (batteries, supercapacitors). This software constitutes a breakthrough compared to MEMEPhys, as it is coded on an independent C + Python programming language basis, highly flexible, modular and portable (it can eventually be coupled to commercial software such as Matlab/Simulink). MS LIBER-T is designed to support direct multiparadigm calculations, for instance, simulations coupling on the fly the numerical resolution of continuum models (e.g. describing charge transport in the porous electrode volume) with discrete models (e.g. Monte Carlo module describing the elementary reaction kinetics). Another novelty introduced by MS LIBER-T is its capability of integrating phase field models describing multiphases formation, separation and evolution.

Atomistic Modeling

Nanoscale Modeling

Microscale Modeling

Mesoscale Modeling

Multiscale Modeling