(Invited) 3D Printing of 2D Materials for Optimized Electrochemical Performance

Electrochemical energy storage (EES) and conversion devices (e.g. batteries, supercapacitors, and reactors) are emerging as primary methods for global efforts to shift energy dependence from limited fossil fuels towards sustainable and renewable resources. These devices, while showing great potential for meeting some key metrics set by conventional technologies, still face significant limitations. For example, an EES device tends to exhibit large energy density (e.g. lithium-ion battery) or power density (e.g. supercapacitor), but not both. This inability of a single device to simultaneously achieve both metrics represents a major obstacle to widespread adoption of EES devices. Similarly, many catalytic processes depend on expensive platinum group metals (PGM) because non-PGM materials have poor performance or durability. Though the integration of 2D materials (e.g. graphene, dichalcogenides, MXene, etc.) into electrochemical devices has yielded some exciting results towards tackling these issues, significant improvements are still needed. One approach to optimizing the performance of these devices is to focus on one of the fundamental processes that occur in these systems: mass (or charge) transport. The efficient transport of ions within EES and conversion devices is critical to realizing better performance and durability. The pore structure of the electrode is a key factor in determining this transport phenomena, but in many cases, engineering the pore structure in a highly deterministic fashion can be challenging. In this work, we explore a number of additive manufacturing methods (e.g. direct ink write, projection microstereolithography, etc.) to engineer the pore structure of device electrodes. We also determine effective electrode geometries using both simple theory and topology optimization techniques. The topology optimization couples the solution of the forward electrochemical problem over the full electrode domain with gradient-based optimization. The output of our code is a three-dimensional CAD representation which optimizes over specific performance metrics and which can be used to print functional electrodes. This work provides a systematic path toward automated design and fabrication of engineered electrodes with precise control over the fluid and species distribution. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.