Material Networks Analyzer (MANA)
Material-by-design made possible
Material networks analyzer (MANA) was developed in 2018. It is a tool for rapid characterization that identifies critical topological features of complicated material networks directly from microscopic images and provides visualized statistics.
MANA enables in-depth investigation of structure-property relationship of materials and facilitates the development of accurate physical-based models that assist the progress of material-by-design. It also learns features from images to potentially discover intriguing properties within or shared by materials.
It takes only seconds to process millions of pixels, reveal network structure, identify topological features, and generate all the statistical reports - no technical skills required.
MANA outperforms commercial software on the market with algorithms that accurately restore and reconstruct the target.
Features
Know the route
The animated visualization allows users to have a better understanding of the network structure and facilitates the study of connectivity and percolation paths.
Matters don't matter
MANA adapts to various types of materials, including carbon nanotubes, copper/silver nanowires, synthetic nanofibers, polymers, cells, tissues, scaffolds, etc.
Work with the imperfection
Even with unsatisfactory inputs which are quite common in practice, MANA can still recognize the pattern and provide a general description of the data.