Automatisierte Synthese kolloidaler Partikeln zur wissensbasierten Produktgestaltung
Zusammenfassung der Projektergebnisse
We present a comprehensive and extensive study on the automated synthesis of small nanoparticles and is exemplified for CdSe and InP QDs using high-throughput experimentation (HTE). The research revolves around five crucial pillars of HTE, which facilitate efficient experimental planning and process design while providing valuable insights for quantum materials research. The results emphasize the importance of efficient automation, for instance evidenced by fast sampling. Reproducibility is rigorously quantified, revealing convincing results with deviations as low as 0.73 % across 15 reactions. An in-depth exploration of the particle size distribution (PSD) unveils the adaptation of a highly effective method for high-throughput PSD evaluation. Structure-property relationships can be studied through an automated approach for quantum yield (PLQY) determination. The automated method outperforms manual approaches, providing highly accurate results and significantly improved reproducibility. Furthermore, the project explores the critical role of mixing in the evolution of the PSD, revealing invaluable insights into particle formation kinetics that are not attainable through conventional manual experiments. Focusing/defocusing behavior attributed to mixing is studied systematically, yielding essential data to be effectively harnessed for future applications. Efficient experimental planning and process design are achieved through the implementation of design of experiments (DoE) and effective data visualization techniques. The proposed concept of equivalent mixing times (EMT) empowers researchers to predict mixing control under various operating conditions from data obtained at ambient conditions. The approach studied for CdSe can be transferred to other material systems such as InP, enabling the development of a predictive model for InP QD synthesis. In conclusion, this project showcases the advantages of automated synthesis providing enhanced reproducibility and improved efficiency, thereby contributing valuable insights to quantum materials research. The implementation of HTE opens new horizons for the quantitative analysis and optimization of complex processes, thus significantly advancing particle technology research.
Projektbezogene Publikationen (Auswahl)
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Automated synthesis of quantum dot nanocrystals by hot injection: Mixing induced self-focusing. Chemical Engineering Journal, 320, 232-243.
Salaheldin, Ahmed M.; Walter, Johannes; Herre, Patrick; Levchuk, Ievgen; Jabbari, Yasaman; Kolle, Joel M.; Brabec, Christoph J.; Peukert, Wolfgang & Segets, Doris
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Cleaning Matters!. ACS Combinatorial Science, 21(11), 722-725.
Mahmoud, Ahmed Salaheldin & Segets, Doris
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Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine. ACS Combinatorial Science, 22(1), 6-17.
Reinhardt, Elisabeth; Salaheldin, Ahmed M.; Distaso, Monica; Segets, Doris & Peukert, Wolfgang
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Microstructure characteristics of non-monodisperse quantum dots: on the potential of transmission electron microscopy combined with X-ray diffraction. CrystEngComm, 22(21), 3644-3655.
Neumann, Stefan; Menter, Christina; Mahmoud, Ahmed Salaheldin; Segets, Doris & Rafaja, David
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Controlled mixing during colloidal quantum dot synthesis: A proxy-concept based on equivalent parameters. Chemical Engineering Journal, 475, 145393.
Salaheldin, Ahmed M. & Segets, Doris
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Population balance modeling of InP quantum dots: Experimentally enabled global optimization to identify unknown material parameters. Chemical Engineering Science, 281, 119062.
Wang, Zhuang; Traoré, Nabi E.; Schikarski, Tobias; Stiegler, Lisa M.S.; Drobek, Dominik; Zubiri, Benjamin Apeleo; Spiecker, Erdmann; Walter, Johannes; Peukert, Wolfgang; Pflug, Lukas & Segets, Doris
