Team 2: Integration of Vector Graphics to Enhance StructuralGT’s Graph Extraction and Processes

Daisy Kiptoo, North Carolina State University
Shixuan Li, University of Southern California

The goal of this project is to enhance Structural-GT, a software for graph analysis, by integrating advanced vector graphics techniques. These include Bézier curves and Non-Uniform Rational B-Splines (NURBS), which enable precise, scalable, and high-fidelity graph outputs. By refining node and edge detection, the project ensures adaptability across diverse image datasets, such as SEM and TEM images, and improves the software’s utility for materials science and other disciplines.

Currently, Structural-GT relies on raster-based methods (e.g., thresholding, filtering, skeletonization) for structural analysis. However, these approaches face several limitations like redundant nodes, low information density and no curvature measurement, which limits the ability to analyze complex structures.

By addressing these challenges, the enhanced Structural-GT will significantly improve the precision and efficiency of graph analysis.

Team 4: 3D printing using acoustically tuned “viscosity metamaterials”

Omkar Roy, University of Michigan
Chia-Pei Chu, University of Michigan
Hongju Jung, University of Michigan
Abhi Shetty, Anton Parr USA

Small orthogonal perturbations normal to the principal flow direction in dense particle suspensions can change the material properties (e.g. viscosity, yield stress) on the fly. This can be helpful in DIW 3D printing and material reuse post extrusion, ensuring circular and sustainable material use.

Team 6: CdS Quantum Dot Pt Nanoparticle Aerogel Composites for Photocatalytic Water Reduction: Consequences of Composite Preparation Method on Network Connectivity and Photocatalytic Activity

Vinicius Alevato, Wayne State University
Alex Niculescu, Wayne State University
Chansong Kim, University of Illinois at Urbana-Champaign
Kody Whisnant, University of Michigan

Photocatalytic water splitting produces hydrogen using solar energy and photocatalysts. This reaction has the potential to efficiently produce hydrogen fuel and propel clean and renewable energy production. The major component that influences the reaction efficiency is the photocatalyst. Pt-CdS composites are promising photocatalysts for the water splitting reaction. Thus, our goal is to prepare Pt-CdS quantum dot aerogels composites and evaluate the influence of their production method on photocatalytic activity. Our hypothesis is that understanding the connectivity of the particles of both materials related to the synthetic method of the composite will enable the production of materials with optimized photocatalytic activity. The rationale is that the nature of the Pt-CdS interaction (chemisorption vs. physisorption), and the number of nanoparticles of CdS connected to Pt are derived from the production method; and controlling all these aspects is essential to enable optimized electron transfer between the materials. Different composites will be prepared using co-gelation, impregnation and photodeposition techniques, to obtain materials with different sorption modes and Pt nanoparticles positioning in the CdS gel matrix. We will analyze the structure of the materials using 3D electron tomography and use graph theory calculations to evaluate the connections between CdS and Pt nanoparticles, exploring the relationship of the interactions between particles to the photocatalytic activity.

Team 8: Exploiting Capillary Bond Networks for Collective Sensing

Yvonne Amaria, University of Michigan
Sungwan Park, University of Michigan
Trevor Teague, University of Michigan

Colloidal-scale robots can communicate via networks of particle interactions. Using particle tracking experiments, agent-based modeling, and insights from interfacial assembly, we study systems’ ability to transmit information as a material property, unlocking paradigms for adaptive materials.