Population balance modeling of InP quantum dots: Experimentally enabled global optimization to identify unknown material parameters

Wang Z, Traore N, Schikarski T, Stiegler L, Drobek D, Apeleo Zubiri B, Spiecker E, Walter J, Peukert W, Pflug L, Segets D (2023)

Publication Language: English

Publication Type: Journal article

Publication year: 2023

Journal

Chemical Engineering Science Elsevier

Book Volume: 281

Article Number: 119062

DOI: 10.1016/j.ces.2023.119062

Abstract

Despite great progress in the synthetic chemistry of InP QDs, a predictive model to describe their temporal formation is still missing. In this work, we introduce a population balance model incorporating liquid phase reactions, homogeneous nucleation and reaction-limited growth of InP supported with the highly reproducible and reliable experimental data acquired from an automated robotic synthesis platform. A comparison between experimental kinetic data (different initial concentrations and temperatures) and simulations was made. The proposed model describes the temporal evolution of solid concentration, particle diameter and particle size distribution very well. The quantitative agreement between experiments and simulations was only achieved by global optimization to identify unknown and hardly measurable material parameters and kinetic constants such as surface energy, growth rate constants or activation energies. We see this model rendering the first step towards the development of more refined models that enable rigorous optimization and control of the production process for III-V semiconductors.

Authors with CRIS profile

Nabi Traore Lehrstuhl für Feststoff- und Grenzflächenverfahrenstechnik Tobias Schikarski Lehrstuhl für Feststoff- und Grenzflächenverfahrenstechnik Lisa Stiegler Sonderforschungsbereich 1411 Produktgestaltung disperser Systeme / Design of Particulate Products Dominik Drobek Lehrstuhl für Werkstoffwissenschaften (Mikro- und Nanostrukturforschung) Benjamin Apeleo Zubiri Lehrstuhl für Werkstoffwissenschaften (Mikro- und Nanostrukturforschung) Erdmann Spiecker Lehrstuhl für Werkstoffwissenschaften (Mikro- und Nanostrukturforschung) Johannes Walter Lehrstuhl für Feststoff- und Grenzflächenverfahrenstechnik Wolfgang Peukert Lehrstuhl für Feststoff- und Grenzflächenverfahrenstechnik Lukas Pflug FAU Competence Center Scientific Computing (FAU CSC)

Involved external institutions

Universität Duisburg-Essen (UDE) DE Germany (DE)

How to cite

APA:

Wang, Z., Traore, N., Schikarski, T., Stiegler, L., Drobek, D., Apeleo Zubiri, B.,... Segets, D. (2023). Population balance modeling of InP quantum dots: Experimentally enabled global optimization to identify unknown material parameters. Chemical Engineering Science, 281. https://dx.doi.org/10.1016/j.ces.2023.119062

MLA:

Wang, Zhuang, et al. "Population balance modeling of InP quantum dots: Experimentally enabled global optimization to identify unknown material parameters." Chemical Engineering Science 281 (2023).

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