Personal web page : https://iramis.cea.fr/Phocea/Membres/Annuaire/index.php?uid=grizza
Laboratory link : https://portail.polytechnique.edu/lsi/fr/page-daccueil
More : https://www.linkedin.com/in/giancarlo-rizza-phd-48338410a/
This PhD research project explores the cutting-edge field of 4D printing, a field that integrates smart materials into additivemanufacturing processes. The aim is to create nanocomposite objects with multifunctional capabilities, enabling them to change shapeand properties in response to external stimuli.
In this PhD project, we will primarily focus on liquid crystal elastomers (LCEs) as the active matrix. LCEs are a versatile class ofprogrammable polymer materials that can undergo reversible deformation under various stimuli, such as light, heat, electric fields, andmagnetic fields, transitioning from disordered to oriented phases. Because of their actuation properties, LCEs are promising candidatesin applications like artificial muscles in medicine and soft robotics.
Consequently, the project's first objective is to devise a method for 3D printing LCE resins using light-driven printing processes, includingdigital light processing (DLP), direct ink writing (DIW), and two-photon polymerization. The project also explores the possibility of co-printing using two laser sources with different wavelengths. This will result in designed objects capable of programmed deformationsand reversibility. To further enhance the actuation capabilities of the LCE matrices, magnetic particles will be incorporated into thethermoresponsive LCE resin. Thus, the second objective of the project is to develop a strategy for self-assembling and spatiallyorienting embedded magnetic nanoparticles in LCE resins during light-driven printing processes (DLP, DIW, 2PP). Ultimately, the thirdobjective of this project is to combine these two strategies to create sophisticated multifunctional soft machines and devices suitable forcomplex environments. Experiments will follow an incremental trial-and-error research approach, with the aim of improving machinelearning models by designing purpose-built objects.
The envisioned research work can be summarized into the following macro-steps:
- Specification of target shape-changes depending on the multiple stimulation scenarios
- Selection of active particles, formulation of the LCE, and synthesis of the particles
- Development of hybrid additive manufacturing strategies with possible instrumentation
- Printing proofs-of concept and conducting mechanical and actuation tests
- Characterization of composite structures
- Development of simulation models
- Realization of a demonstrator (e.g., crawling robot, actuators for the automotive sector…)