Projects
Post Doc Project
I aim to advance programmable mechanical metamaterials for adaptive shape morphing in energy-autonomous material systems. By categorizing existing unit cell designs and validating them through simulations and experiments, I will develop an AI-driven design process to optimize shape-morphing capabilities. The goal is to create a toolbox that accelerates the design of complex, functional metamaterials for applications like soft robotics and precision motion control.
*Project Outcome**
We established a constitutive modeling framework for 3D-printed polymers to enable predictive FEM analysis of manufacturing-induced defects. Material parameters calibrated in MCalibration® showed strong agreement with experimental data but limited convergence in ANSYS®, whereas ANSYS-calibrated models provided reliable convergence, with Mooney–Rivlin identified as the most suitable hyperelastic representation. For plasticity, both Bilinear and Power-Law hardening formulations captured the material response, with the Power-Law model selected to best represent observed nonlinearity. We applied calibrated models to predict the mechanical role of FFF filament seams, which were identified as a dominant structural factor. Seam placement was found to strongly influence strain localization: controlled seam paths reduced strain amplification, whereas uncontrolled or randomly accumulated seams intensified stress concentrations and triggered premature failure. These findings demonstrated that seams can be reinterpreted from manufacturing defects into programmable design features for fracture-guided metamaterials.
In a complementary research direction, a new class of interlocking metasurfaces for reversible mechanical joining was developed. The influence of unit-cell geometry on locking and unlocking behavior was systematically evaluated through finite-element simulation and validated using 3D-printed prototypes. Tunable asymmetry between locking and release forces was demonstrated, and scalability from individual unit cells to 2D and 3D metasurface assemblies was confirmed, highlighting potential for adaptive interfaces and reconfigurable mechanical systems."
Supervisor
Prof. Dr. Chris Eberl
PhD Project
Self-sealing by orchestrating chemical and mechanical mechanisms and processes as basis for self healing in livMatS
In a living materials system, the essential requisite for initiating the self-healing process is that the two parts of a crack or cut come into close contact without external factors. This prerequisite is called the self-sealing capability of the material. Mechanical metamaterials can be programmed to adapt automatically to changing conditions such as alteration in stress and strain state. In my research, I investigate programmable mechanical metamaterials to design and develop the appropriate unit cells with mechanical crack closure and self-sealing ability.
Project Outcome
In my cumulative dissertation, I systematically investigated self-sealing mechanisms in biological and engineered materials, introducing a structured approach to transfer plant-inspired self-sealing strategies into programmable mechanical metamaterials. This includes the development of a pressure-dependent metamaterial inspired by Delosperma cooperi, utilizing chiral unit cells and curved permeable walls to generate a localized squeezing effect for global shape morphing required for crack closure (Ghavidelnia et al., 2024, Advanced Materials). To facilitate the transfer of biological self-sealing mechanisms into engineering, a novel methodology using flowcharts and control flows was proposed, enabling a systematic deconstruction of complex biological processes into actionable design principles (Cao and Ghavidelnia et al., 2023, Programmable Materials). Additionally, a new design of bistable and monostable curly beams in metamaterials was introduced, optimizing their structural characteristics for energy storage and controlled deformation (Ghavidelnia et al., 2023, Materials & Design).
Supervisor and dissertation
Prof. Dr. Chris Eberl