Semi-supervised machine learning approach for reaction stoichiometry and kinetic model identification using spectral data from flow reactors

Abstract

The semi-supervised machine learning approach is an integrated calibration-free modelling framework for identifying reaction systems from spectral data using minimal prior information and it is validated with experimental data obtained in a micro-reactor.