A robotic platform for the synthesis of colloidal nanocrystals

Haitao Zhao, Wei Chen, Hao Huang, Zhehao Sun, Zijian Chen, Lingjun Wu, Baicheng Zhang, Fuming Lai, Zhuo Wang, Mukhtar Lawan Adam, Cheng Heng Pang, Paul K. Chu, Yang Lu, Tao Wu, Jun Jiang, Zongyou Yin, Xue Feng Yu

Research output: Journal PublicationArticlepeer-review

21 Citations (Scopus)

Abstract

Morphological control with broad tunability is a primary goal for the synthesis of colloidal nanocrystals with unique physicochemical properties. Here we develop a robotic platform as a substitute for trial-and-error synthesis and labour-intensive characterization to achieve this goal. Gold nanocrystals (with strong visible-light absorption) and double-perovskite nanocrystals (with photoluminescence) are selected as typical proof-of-concept nanocrystals for this platform. An initial choice of key synthesis parameters was acquired through data mining of the literature. Automated synthesis and in situ characterization with further ex situ validation was then carried out and controllable synthesis of nanocrystals with the desired morphology was accomplished. To achieve morphology-oriented inverse design, correlations between the morphologies and structure-directing agents are identified by machine-learning models trained on a continuously expanded experimental database. Thus, the developed robotic platform with a data mining–synthesis–inverse design framework is promising in data-driven robotic synthesis of nanocrystals and beyond. [Figure not available: see fulltext.]

Original languageEnglish
Pages (from-to)505-514
Number of pages10
JournalNature Synthesis
Volume2
Issue number6
DOIs
Publication statusPublished - Jun 2023

ASJC Scopus subject areas

  • Chemistry (miscellaneous)
  • Inorganic Chemistry
  • Organic Chemistry
  • Materials Chemistry

Fingerprint

Dive into the research topics of 'A robotic platform for the synthesis of colloidal nanocrystals'. Together they form a unique fingerprint.

Cite this