Anker, Andy S.Quinson, Jonathan2026-04-092026-04-092026-02-18Anker, A. S.; Jensen, J. H.; González-Duque, M.; Moreno, R.; Smolska, A.; Juelsholt, M.; Hardion, V.; Jørgensen, M. R. V.; Faíña, A.; Quinson, J.; Støy, K.; Vegge, T. Autonomous Synthesis of Nanoparticles with Target Scattering Patterns. ACS Nano 2026, 20 (8), 6767–6782. https://doi.org/10.1021/acsnano.5c15488.1936-08511936-086Xhttps://hdl.handle.net/2183/47910[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,1–5 are particularly challenging to synthesize due to numerous tunable parameters. Here, we introduce an autonomous approach that explicitly targets atomic-scale structure through scattering patterns. 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 embedded synthesis knowledge. We demonstrate this capability at a synchrotron by targeting two structurally distinct gold NP scattering patterns: 5 nm decahedral and 10 nm face-centered cubic structures. Ultimately, specifying target scattering patterns and autonomously approaching synthesis protocols that reproduce them experimentally may enable on-demand, atomic structure-informed materials design. ScatterLab thus provides a generalizable blueprint for autonomous, atomic structure-targeted synthesis across diverse systems and applications.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Self-driving laboratoriesAutonomous laboratoriesRobotic synthesisNanomaterialsX-ray scatteringMachine learningSynchrotronsjournal articleopen access10.1021/acsnano.5c15488