Microfluidic Machine Learning (MFML) platform

University of Toronto / Canada

Application Areas

nanoparticle synthesis


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.

Research purpose

Lab Equipment

AC Members

Alán Aspuru-Guzik
University of Toronto
Eugenia Kumacheva
University of Toronto


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