Dial-A-Particle: Precise Manufacturing of Plasmonic Nanoparticles Based on Early Growth Information—Redefining Automation for Slow Material Synthesis

Abstract

Nanomaterials are at the core of many scientific discoveries in catalysis, energy and healthcare to name a few. However, their deployment is limited by the lack of reproducible and precise manufacturing technologies on-demand. In this work, a precision automated technology is demonstrated for nanoparticles synthesis with wide-range tunable sizes (≈4–100 nm). Dial-a-particle capabilities are achieved by a combination of a fast integrated multipoint particle sizing combined with a “plug-n-play” modular platform with reactors in series, distributed feed and in situ multipoint analysis. Real-time early growth information accurately predicts the resulting particle properties. Such real-time simple feedback control can overcome repeatability and stability issues associated with controllable (e.g., conditions) and uncontrollable (e.g., fouling, ageing, and impurities) variations leading to self-regulated, highly stable multistage systems with no human intervention even with long residence times (from a few minutes to hours). This is a paradigm shift from machine learning (ML) methodologies, which are restricted to trained networks with rich data sets, impractical in non-reproducible processes and limited to short residence times (e.g., within few minutes). The approach is demonstrated for plasmonic silver and gold nanoparticles showing agile control within minutes, opening the door for automation of more complex multistage procedures such as composites, multielement materials, and particle functionalization.