Suche nach kompatiblen Zirkonoxid-basierten Formgedächtniskeramiken
Zusammenfassung der Projektergebnisse
Shape memory ceramics represent a promising class of materials that exhibit reversible phase transformations, enabling them to recover from a mechanically deformed, to their original shape upon heating. Among these, zirconia-based ceramics have gained significant attention due to their unique phase transition behavior, mechanical robustness, and potential applications in various high-performance environments. The tetragonal-to-monoclinic martensitic transformation observed in the oxides zirconia (ZrO2) and hafnia (HfO2) is of particular interest for shape memory and superelasticity applications, similar to those observed in metallic shape memory alloys like NiTi. This research focuses on identifying and optimizing zirconia-based ceramic compositions that exhibit crystallographic compatibility, a critical factor influencing the transformation reversibility and functional performance of a material. By using various oxides as dopants (Y2O3, Ta2O5, Nb2O5, Er2O3 and HfO2) the phase transformation behavior can be tailored to enhance the shape memory properties of a sample and influence the mechanical response during phase transformation. Our research revealed, among other findings, a strong correlation between sample composition and phase transformation such that minor changes to the composition can change a material from transforming without much change, to falling apart at the grain boundary or jumping due to the release of stress building within the material. The project builds upon previous research on crystallographically compatible shape memory ceramics by extending the compositional range and investigating new oxides to improve performance and extend the knowledge regarding the intricacies of monoclinic to tetragonal phase transitions in ceramic materials. Research has been performed to combine experimental synthesis, advanced characterization techniques and machine learning models to predict and potentially optimize the transformation characteristics of zirconia-based ceramics. The research includes: • The collection of a robust dataset encompassing a wide range of material compositions and phase transformation properties, such as temperature dependent lattice parameters. • Theoretical analysis of crystallographic compatibility conditions to identify optimal compositions and discover the importance of special relations between lattice parameters. • Machine learning-driven predictive modeling to accelerate the search for compatible ceramics and reduce reliance on experimental parameter iterations. • Experimental validation through X-ray diffraction (XRD), differential scanning calorimetry (DSC), and focused-ion beam (FIB) assisted scanning electron microscopy (SEM) to assess phase stability and transformation behavior. The insights gained from this study contribute to the broader field of shape memory materials, offering a pathway to designing high-performance zirconia-based ceramics with enhanced functional properties for applications in structural, harsh chemical, and high-temperature environments.
Projektbezogene Publikationen (Auswahl)
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Exploding and weeping ceramics. Nature, 599(7885), 416-420.
Gu, Hanlin; Rohmer, Jascha; Jetter, Justin; Lotnyk, Andriy; Kienle, Lorenz; Quandt, Eckhard & James, Richard D.
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Composition Design of Shape Memory Ceramics based on Gaussian Processes
Pandey, A.; Jetter, J.; Gu, H.; Quandt, E. & James, R.D.
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In-Situ compression and shape recovery of Ceramic single grain micro-pillar
Jetter, J. & Quandt, E.
