Automated synthesis and processing of functional nanomaterials: Advances and perspectives

Abstract

Integration of nanotechnology and information technology has seen an enormous leap in growth with the invention of automated systems capable of synthesizing and processing nanomaterials, thus presenting notable advantages over traditional techniques, particularly improved accuracy, reproducibility, and scalability. Automated systems minimize human errors, and nanomaterials can also be produced on a large scale at a speedy rate while controlling material properties in great detail, hence giving rise to specific functionalities that may not be realized through manual methods. Here, the most recent advancements in automated synthesis and processing of nanomaterials will be discussed, covering various types of nanomaterials which can be categorized as either coordinated or non-coordinated including metal-organic frameworks (MOFs), MXenes, quantum dots (QDs), nanocomposites, carbon-based nanomaterials, and others. Additionally, we will address the technological breakthroughs that have led to automation, from microfluidic synthesis to robots coupled with artificial intelligence (AI) and machine learning. In a new age of synthetic approaches, advanced developments within automation provide the controllable and predictable production of high-quality known nanomaterials while also providing the catalyst for generating novel nanomaterials. The primary object of this review is to provide a comprehensive and critical assessment of the current trends and breakthroughs in automated nanomaterial synthesis and processing, which brings out the research principles and the advantages of different automated platforms. It is equally important to address some limitations of current approaches to ignite a discussion about future research directions.