Self-driving lab for the photochemical synthesis of plasmonic nanoparticles with targeted structural and optical properties

Tianyi Wu, Sina Kheiri, Riley J. Hickman, Huachen Tao, Tony C. Wu, Zhi-Bo Yang, Xin Ge, Wei Zhang, Milad Abolhasani, Kun Liu, Alan Aspuru-Guzik and Eugenia Kumacheva ()
Additional contact information
Tianyi Wu: University of Toronto
Sina Kheiri: University of Toronto
Riley J. Hickman: University of Toronto
Huachen Tao: University of Toronto
Tony C. Wu: University of Toronto
Zhi-Bo Yang: Jilin University
Xin Ge: Electron Microscopy Center
Wei Zhang: Electron Microscopy Center
Milad Abolhasani: North Carolina State University
Kun Liu: Jilin University
Alan Aspuru-Guzik: University of Toronto
Eugenia Kumacheva: University of Toronto

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Many applications of plasmonic nanoparticles require precise control of their optical properties that are governed by nanoparticle dimensions, shape, morphology and composition. Finding reaction conditions for the synthesis of nanoparticles with targeted characteristics is a time-consuming and resource-intensive trial-and-error process, however closed-loop nanoparticle synthesis enables the accelerated exploration of large chemical spaces without human intervention. Here, we introduce the Autonomous Fluidic Identification and Optimization Nanochemistry (AFION) self-driving lab that integrates a microfluidic reactor, in-flow spectroscopic nanoparticle characterization, and machine learning for the exploration and optimization of the multidimensional chemical space for the photochemical synthesis of plasmonic nanoparticles. By targeting spectroscopic nanoparticle properties, the AFION lab identifies reaction conditions for the synthesis of different types of nanoparticles with designated shapes, morphologies, and compositions. Data analysis provides insight into the role of reaction conditions for the synthesis of the targeted nanoparticle type. This work shows that the AFION lab is an effective exploration platform for on-demand synthesis of plasmonic nanoparticles.

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-56788-9 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56788-9

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-56788-9

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().