Transforming Nanomaterial Synthesis with Flow Chemistry

Microfluidic methods for the synthesis of nanomaterials allow generation high-quality products with outstanding structural, electronic and optical properties. At a fundamental level, this is engendered by ability to control both heat mass transfer in rapid precise manner, but also facile integration in-line characterization tools machine learning algorithms. Such integrated platforms provide exquisite over material properties during synthesis, accelerate optimization bestow new insights into optoelectronic nanomaterials. Herein, we present brief perspective on role that microfluidic technologies can play nanomaterial particular focus recent studies incorporate learning. We consider importance challenges associated integrating additional functional components within experimental workflows upscaling production industrial-scale quantities