Raziskovalni projekt (so)financira Javna agencija za raziskovalno dejavnost RS.
Članica UL: Fakulteta za matematiko in fiziko
Šifra projekta: N1-0124
Naziv projekta: Geometric and topological shape morphing of active elastomers
Obdobje: 1. 8. 2019 - 31. 7. 2022
Letni obseg: 2,82 FTE, cenovna kategorija: E
Vodja: Žiga Kos
Veda: Naravoslovje
Vsebinski opis projekta:
Soft robotics is a fascinating field of deformable materials that mimic living matter to perform functional motion. Elastomer materials have been developed for soft robotic functions, such as bending, walking, grabbing and releasing cargo, or performing wave-like motion. However, most of the elastomers today rely on external actuation in the form of temperature or pH change, or applied electric, magnetic, or light fields, and are not necessarily biologically compatible. Instead, imagine a bio-compatible tissue that could spontaneously change shape by taking energy from the environment and could be designed to pump fluid by performing a beating motion or could be formed into a shell and function as a support and driving structure of artificial robotic cells.
This project is a step towards such active shape-changing tissues, where I want to combine elastic deformation of elastomers and spontaneous motion of active matter to design soft robotic materials based on shape deformations of active anisotropic elastomers and gels. In such materials, surface deformation will be naturally coupled to the underlying anisotropic order. Additionally, activity could drive the pattern evolution in the anisotropic order (and topological defects within) and consequentially also the evolution of the geometric shape. Specifically, the control over surface deformations will be achieved by external fields and by using shells of different geometric shapes and arrangements of topological defects. The main methodology will be theory and finite element numerical simulations, which will be combined with collaborative experiments. The developed numerical and theoretical framework will be applied to predict and analyse optimal designs for soft robotic functions.
