Autonomous nanoparticle synthesis by design

TL;DR

This paper presents an autonomous method for designing synthesis protocols that match real-time scattering data to target atomic structures, enabling precise and reproducible nanoparticle synthesis without prior knowledge.

Contribution

It introduces ScatterLab, a novel autonomous framework that designs synthesis protocols by matching experimental scattering data to simulated targets, advancing materials synthesis automation.

Findings

Successfully synthesized gold nanoparticles with distinct structures

Demonstrated real-time protocol design without prior synthesis knowledge

Potential to revolutionize materials design and synthesis automation

Abstract

Controlled synthesis of materials with specified atomic structures underpins technological advances yet remains reliant on iterative, trial-and-error approaches. Nanoparticles (NPs), whose atomic arrangement dictates their emergent properties, are particularly challenging to synthesise due to numerous tunable parameters. Here, we introduce an autonomous approach explicitly targeting synthesis of atomic-scale structures. Our method autonomously designs synthesis protocols by matching real time experimental total scattering (TS) and pair distribution function (PDF) data to simulated target patterns, without requiring prior synthesis knowledge. We demonstrate this capability at a synchrotron, successfully synthesising two structurally distinct gold NPs: 5 nm decahedral and 10 nm face-centred cubic structures. Ultimately, specifying a simulated target scattering pattern, thus representing a bespoke atomic structure, and obtaining both the synthesised material and its reproducible synthesis protocol on demand may revolutionise materials design. Thus, ScatterLab provides a generalisable blueprint for autonomous, atomic structure-targeted synthesis across diverse systems and applications.