(Invited) Modeling at Multiple Scales for Development of Future Energy Storage Technologies

The energy sector is currently undergoing transition, driven by population growth, demand for more and cleaner energy, and increasing customer choice[1]. To facilitate the growth and uptake of renewable energy in a more electrified energy system, developing efficient and economical means of storing and distributing electricity is vital. Next-generation battery technologies and other electrochemical energy storage and conversion technologies have great promise to enable energy transition. Precise control and understanding of electrochemical and other phenomena over multiple length and time scales will play an important role as the energy transition unfolds. Within Shell’s Advanced Energy Storage program, we utilize a framework referred to as Experimental-Modeling Powered Optimization Workflow for Energy StoRage Systems (EMPOWERS). The framework seeks to link phenomena observed at different length scales via experimental and computational means. This talk will share some recent investigation of advanced lithium batteries, with use of DFT, molecular dynamics, and continuum models to investigate advanced battery systems over multiple length and time scales. We will share recent computational investigation into PEO-based polymer systems as electrolytes[2] for lithium metal batteries. We have used molecular dynamics to compute the effect of pressure on key electrolyte parameters, such as density, diffusivity, and transference number. We have also used DFT and ab initio molecular dynamics to study a particular class of cathode material for lithium sulfur batteries. In this case, DFT based on ultrasoft-pseudopotentials was used to calculate the XPS spectra for species present in the cathode in charged and discharged states, which was then validated by experimental XPS data[3]. To complement the electrolyte and electrode-specific component studies, continuum cell models have been used to combine measurements on individual cell components, with an eye towards development of reduced-order models. [1] http://www.shell.com/investor Royal Dutch Shell PLC, Shell: Energy transitions and portfolio resilience (2016) Royal Dutch Shell PLC, 2016 North America Investor Day (2016) Royal Dutch Shell PLC, Barclays CEO Energy Power Conference (2016) [2] D. T. Hallinan Jr. and N. P. Balsara, Annual Review of Materials Research, 43, 503-525 (2013). [3] Experimental work by Guy Verbist (Shell Global Solutions International B.V.), Alexey Deyko and Christina Christova (Polymer Technology Group Eindhoven (PTG/e) BV.)