Microfluidic Machine Learning (MFML) platform

The MAP (MFML platform) is an integration of machine learning (ML) and microfluidics (MF), which offers accelerated identification and optimization of reaction conditions for nanoparticle (NP) synthesis. The platform utilized multiple recipes and reaction times for the synthesis of NPs with different dimensions, conducted spectroscopic NP characterization, and employed ML approaches to analyze multiple yet prioritized spectroscopic NP characteristics, and identified reaction conditions for the synthesis of NPs with targeted optical properties. The platform is also used to develop an understanding of the relationship between reaction conditions and NP properties, which therefore shows the strong potential of the MLMF platforms in materials science and paves the way for automated NP development. The equipment for this lab is provided by Hamilton company, Thorlabs, Inc, and McMaster-Carr.