Utilizing ML techniques for image analysis and characterization
Our research group focuses on designing functional material, encompassing solution synthesis, and understanding structure-property relationships through laboratory and synchrotron characterization. We have a particular interest in hybrid organic-inorganic materials. What excites us is their immense design freedom in chemistry, stoichiometry, geometry, and topology. We navigate through these complex design spaces leveraging lab automation and data science toolkits, aiming to unlock their boundless functional potential.
Related Projects
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Our goal is to use computer vision techniques to analyze the perovskite to identify surface heterogeneity, significantly impacting the material's structural stability and lifespan. To achieve this, we have implemented various computer vision techniques, including GLCM properties, standard deviation, mean and median, pixel variance, as well as line and circle detection features to help characterizing the overall surface heterogeneity of the perovskite within the image.
Understanding Perovskite Thin Film Heterogeneity Using Computer Vision