RESUMO
Microfluidic methods for the synthesis of nanomaterials allow the generation of high-quality products with outstanding structural, electronic and optical properties. At a fundamental level, this is engendered by the ability to control both heat and mass transfer in a rapid and precise manner, but also by the facile integration of in-line characterization tools and machine learning algorithms. Such integrated platforms provide for exquisite control over material properties during synthesis, accelerate the optimization of electronic and optical properties and bestow new insights into the optoelectronic properties of nanomaterials. Herein, we present a brief perspective on the role that microfluidic technologies can play in nanomaterial synthesis, with a particular focus on recent studies that incorporate in-line optical characterization and machine learning. We also consider the importance and challenges associated with integrating additional functional components within experimental workflows and the upscaling of microfluidic platforms for production of industrial-scale quantities of nanomaterials.
RESUMO
The highly controlled, microfluidic template-assisted self-assembly of CsPbBr3 nanocrystals into spherical supraparticles is presented, achieving precise control over average supraparticle size through the variation of nanocrystal concentration and droplet size; thus facilitating the synthesis of highly monodisperse, sub-micron supraparticles (with diameters between 280 and 700 nm).