Recent Developments in Process Digitalisation for Advanced Nanomaterial Syntheses

Abstract

Digitalisation and industry 4.0 are set to profoundly change the way chemical and materials discovery and development work. The integration of multiple enabling technologies such as flow synthesis, automation, analytics, and real-time reaction control lead to highly efficient, productive, data-driven discovery and synthetic protocols. For instance, the development of flow chemistry enables the fine control and automation of process parameters such as flow rates, temperature, and pressure, which inherently enhances process efficiency. Flow chemistry presents a more sustainable means of manufacturing in terms of waste minimisation, as it enables the integration of synthetic processes with downstream processing. Furthermore, it allows the integration of analytical techniques to provide in situ process monitoring of large amounts of process and product data. The application of Artificial Intelligence (AI) and/or Machine Learning (ML) techniques allows rapid decision making that can optimise existing processes, and it has also been applied in the discovery of novel materials, synthetic pathways and chemicals. All this is contributing to an effective digitalisation of chemical and material synthetic processes from the laboratory to large-scale industrial deployment. This paper presents recent developments in the effective digitalisation of chemical synthetic processes which integrates continuous flow synthesis, analytics and artificial intelligence technologies. Specifically, this paper illustrates the emerging trend of process digitalisation through the advanced syntheses of materials with catalytic, optical and optoelectronic applications.

Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery

“…Therefore, communicating intensified process descriptors could provide valuable insights at molecular and meso‐ and macroscales while increasing the volume, reliability, and variety of data. [ 75 ] For example, synthesis and processing of colloidal nanocrystals, with an experimental space ranging from 10 5 to 10 10 possible experimental conditions, are time‐ and material‐intensive tasks, using manual experimentation and batch reactors. In one example, Abdel‐Latif et al [ 76 ] reported intensification of the synthesis and bandgap tuning of inorganic metal halide perovskite nanocrystals using two integrated microfluidic reactors.…”