Eckstein U, Kuhfuß M, Fey T, Webber KG (2024)
Publication Type: Journal article
Publication year: 2024
Recent advances in machine learning capabilities have increased interest in materials research to improve the efficiency of materials discovery and optimization as well as to better understand the underlying phenomena responsible for the observed physical properties. While combinatorial chemistry and compositional engineering is well established in the development of pharmaceutical and chemical products, its use in the field of bulk functional polycrystalline ceramics is far from mature. In this work, a critical review of a high-throughput powder-based dispensing system is provided and the challenges involved with the transition from a conventional, human resources intensive workflow to a fully automated process are highlighted. Based on the lead-free piezoelectric BiFeO
APA:
Eckstein, U., Kuhfuß, M., Fey, T., & Webber, K.G. (2024). Feasibility of Powder-Based High-Throughput Synthesis for Ceramics Development: Case Study on the Influence of Calcination Temperature in BiFeO3-BaTiO3. Advanced Engineering Materials. https://doi.org/10.1002/adem.202302126
MLA:
Eckstein, Udo, et al. "Feasibility of Powder-Based High-Throughput Synthesis for Ceramics Development: Case Study on the Influence of Calcination Temperature in BiFeO3-BaTiO3." Advanced Engineering Materials (2024).
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