Data-Driven Optimization of Au Nanoparticle Synthesis with Automated Flow Microreaction System

We developed a flow microreaction system automated by a LabVIEW-based program enabling a control of flow rates of four pumps, an in-line UV–visible spectroscopic monitoring, and a process data logging including the pump pressures. The system was applied to the synthesis of gold nanoparticles (NPs) b...

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Bibliographic Details
Published inJournal of chemical engineering of Japan Vol. 56; no. 1
Main Authors Ono, Takumi, Takebayashi, Yoshihiro, Kashiwagi, Tsuneo, Sue, Kiwamu
Format Journal Article
LanguageEnglish
Published Tokyo Taylor & Francis Group 31.12.2023
Subjects
Algorithms
Chloroauric acid
Data driven
Data logging
Decision trees
Flow control
Flow microreaction
Flow rates
Flow velocity
Gold
Logging
Machine learning
Micromixer
Monitoring
Nanoparticle
Nanoparticles
Optimization
Reagents
Sodium citrate
Synthesis
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Summary:We developed a flow microreaction system automated by a LabVIEW-based program enabling a control of flow rates of four pumps, an in-line UV–visible spectroscopic monitoring, and a process data logging including the pump pressures. The system was applied to the synthesis of gold nanoparticles (NPs) by a reduction of hydrogen tetrachloroaurate (III) (HAuCl4) with sodium tetrahydroborate (NaBH4) in the presence of trisodium citrate (Na3C6H5O7). Concentrations of the three reagents were controlled by changing the flow rates and were optimized so that the spectrum of the NPs gave higher peak at shorter wavelength. A gradual change in the concentrations from the dilute condition according to decision-tree algorithm as well as a careful monitoring of the pump pressures were shown to be effective for the optimization without clogging of the particles in the reactor.
ISSN:0021-9592
1881-1299
DOI:10.1080/00219592.2023.2211125