The micro-supercapacitors (MSCs) serve as efficient power sources in miniaturized electronics e.g. wearable/portable gadgets. However, fabrication of greener MSCs remains one of the main challenges in developing effective miniaturized electronics; a market of $ 42.2 billion in 2022 projected to grow at a rate of 9% by 2029. In this research, we produce conductive inks and present new insights into the fabrication of green printed MSCs. We will employ advance printing methods which enable us to fabricate high resolution MSCs with complex design while minimizing material wastage. We will link the MSC performance to the biomass-derived carbon’s structure, and ink properties.
Our research develops sustainable, high-performance materials for flexible supercapacitors using electrospun lignin-derived carbon fiber mats. Lignin, a renewable biopolymer from plant biomass, is first electrospun into ultrafine fiber networks and then carbonized to form conductive, nanoporous carbon structures. These mats serve as lightweight electrodes with excellent flexibility, high surface area, and good electrical conductivity. The resulting supercapacitors combine mechanical durability with strong electrochemical performance, offering stable energy storage even under bending or folding. This approach demonstrates how renewable materials and nanotechnology can converge to create next-generation, eco-friendly power sources for wearable and flexible electronics.
Understanding the complex structural dynamics of MSC components in their three-dimensional configurations is critical to advancing high-performance energy storage systems. In this regard, X-ray computed tomography (X-ray CT), a non-destructive, multi-scale imaging technique, has emerged as an advanced tool to visualize, quantify, and optimize MSC architectures. We use X-ray CT not just as a visualization technique, but as a powerful analytical tool for evaluating post-synthesis structures, quantifying morphological parameters such as porosity, and pore size distribution, monitoring degradation processes, and generating high-quality data to inform modeling and simulation studies.