Porous electrode charging

In the PoreCharge project, researchers will work to increase supercapacitors' ability to store energy by charging electrodes. Supercapacitors are energy storage devices that can deliver higher power than batteries and degrade more slowly. Now that the world urgently needs to move from fossil to renewable energy sources, supercapacitors can become important components in this transition. They are already used, for example, in electric vehicles and to stabilize the power grid. However, an important limitation of supercapacitors is that the amount of energy that can be stored per volume or weight is low. Attempts to increase the supercapacitors' energy storage have often undermined their power output. To deal with this "energy-power dilemma", the project will develop a multi-scale modeling framework for charging supercapacitor electrodes. The electrodes of supercapacitors contain pores of different sizes and shapes filled with ions. The narrower the pores, the more energy a supercapacitor can store. However, molecular simulations have shown that ions can get trapped when the pores are too narrow, leading to clogged pores. This should be avoided since clogged pores do not contribute to the power output of supercapacitors. The project will therefore build a model that will reproduce pore-clogging to learn how to prevent it. The modeling framework's accuracy will also be tested in experiments on home-built supercapacitors.

A global shift towards renewable energy sources is urgently needed, and as efficient storage devices, supercapacitors may become key components in this transition. Supercapacitors reach higher power densities than batteries and degrade slower. They are already applied, for instance, to accelerate electric vehicles and to stabilize the power grid. However, a key limitation of supercapacitors is their relatively low energy density. Moreover, efforts to increase supercapacitors’ energy storage often hurt their power. To tackle this “energy-power dilemma”, I will develop a multiscale modeling framework for the charging of supercapacitor electrodes. These electrodes contain ion-filled pores of different sizes and shapes. Molecular simulations have shown that ions jam when pores are too narrow, leading to clogged pores. This is bad, as clogged pores do not contribute to a supercapacitor’s power output. Narrow pores, however, are essential to maximizing the energy storage of supercapacitors. I will build a continuum model that captures the pore-clogging known from molecular simulations at a fraction of the computational costs of such simulations. Once we can replicate pore-clogging, we can learn how to prevent it. I will use control theory and Bayesian optimization to identify electrode-electrolyte combinations that maximize an isolated pore’s capacitance and minimize its internal resistance. These single-pore insights will then feed into a device-scale porous electrode model, with macro- and nanopores hierarchically connected. Using the same optimization methods on this larger-scale electrode model, I will identify electrolytes and electrode morphologies that optimize a supercapacitor’s energy and power density. To ensure our modeling framework's accuracy, we will test it against small-scale molecular simulations and experiments on home-built supercapacitors.