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Ai-guided microfluidic synthesis of colloidal lead halide perovskite quantum dots

  • North Carolina State University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, an artificial intelligence (AI)-guided modular microfluidic reactor is developed and utilized for autonomous synthesis and formulation discovery of inorganic metal halide perovskite quantum dots (PQDs) using halide exchange reactions. A novel multimodal material diagnostic module is developed and integrated with the modular microfluidic platform to attain accurate in-situ photoluminescence quantum yield (Φ), emission full-width at half maximum (EFWHM), and peak emission energy (EP) of the in-flow synthesized PQDs, simultaneously through in-situ UV-Vis absorption (A) and photoluminescence (IPL) measurements. An ensemble neural network (ENN) modeling algorithm coupled with various decision-making policies and a multiparameter objective function (Z) allow for the simultaneous improvement of Φ and EFWHM at any target EP completely independent of user intervention.

Original languageEnglish
Title of host publicationMicroTAS 2020 - 24th International Conference on Miniaturized Systems for Chemistry and Life Sciences
PublisherChemical and Biological Microsystems Society
Pages1294-1295
Number of pages2
ISBN (Electronic)9781733419017
StatePublished - 2020
Event24th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2020 - Virtual, Online
Duration: Oct 4 2020Oct 9 2020

Publication series

NameMicroTAS 2020 - 24th International Conference on Miniaturized Systems for Chemistry and Life Sciences

Conference

Conference24th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2020
CityVirtual, Online
Period10/4/2010/9/20

Keywords

  • Modular Microfluidics
  • Perovskite Quantum Dots
  • Smart Microfluidic Material Synthesis

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