At COMPASS, we’re proud to see our junior scientists at the forefront of materials innovation. Recently, Alain Kadar and Wenbing Wu were featured in MRS Bulletin for their insightful work applying graph theory (GT) to better understand and predict the behavior of nanowire networks created through electrostatically frustrated layer-by-layer (LBL) assembly.
LBL assembly has long been valued for its affordability, scalability, and ability to coat even the most complex surfaces. Yet, one of its biggest challenges has been accurately modeling the resulting nanostructures to predict conductivity and performance. Traditional computational models often fall short.
That’s where Kadar and Wu made their mark. By using graph theory—commonly applied to fields like social networks—they reduced experimental nanowire structures into node-and-edge representations. This allowed them to uncover surprising organizational patterns and explain the nonlinear conductivity behaviors observed in their coatings.
The significance of their work extends well beyond the lab. When tested on large-scale structures such as a carbon fiber composite drone wing, their graph theory-informed coating enhanced conductivity and even provided protection against lightning strikes. As outside experts noted, this research could signal a paradigm shift in how multifunctional coatings are modeled and engineered, paving the way for scalable, real-world applications across industries from aerospace to biomedical engineering.
We celebrate Alain and Wenbing’s achievement, which demonstrates not only their ingenuity but also COMPASS’s commitment to advancing science at the intersection of mathematics, materials, and engineering.
Read the full article in MRS Bulletin.