Evidence map›Paper›PMID 39922810›Full record

ArticleNature communications2025

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 and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Surface Ligands in Nanocrystal Electrocatalysis: A Double-Edged Sword.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  4. Article
  5. Article
  6. Conundrums of Localized Surface Plasmon Resonance Biosensors.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  7. Article
  8. PredictingACS omega · 2026
    Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Intelligent Systems for Inorganic Nanomaterial Synthesis.Nanomaterials (Basel, Switzerland) · 2025
    Review
  18. Review
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Tianyi WuDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada.ORCID http://orcid.org/0009-0008-7988-6241
Sina KheiriDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, M5S 3G8, Canada.ORCID http://orcid.org/0000-0002-9934-4297
Riley J HickmanDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada.
Huachen TaoDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada.
Tony C WuDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada.
Zhi-Bo YangState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun, 130012, P. R. China.
Xin GeSchool of Materials Science & Engineering, Electron Microscopy Center, Jilin University, Changchun, 130012, P. R. China.
Wei ZhangSchool of Materials Science & Engineering, Electron Microscopy Center, Jilin University, Changchun, 130012, P. R. China.ORCID http://orcid.org/0000-0002-6414-7015
Milad AbolhasaniDepartment of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27606, USA.ORCID http://orcid.org/0000-0002-8863-3085
Kun LiuState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun, 130012, P. R. China.ORCID http://orcid.org/0000-0003-2940-9814
Alan Aspuru-GuzikDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada.ORCID http://orcid.org/0000-0002-8277-4434
Eugenia KumachevaDepartment of Chemistry, University of Toronto, Toronto, ON, M5S 3H6, Canada. eugenia.kumacheva@utoronto.ca.ORCID http://orcid.org/0000-0001-5942-3890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID39922810
PMCPMC11807174

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.