Predictive modelling of stretchable conductive ink using finite element analysis - Mohd Azli, Daniel Azlan (2024)
Stretchable and flexible printed electronics, which utilize conductive materials made from graphene, have attracted considerable interest due to their cost-effectiveness, flexibility, and impressive ability to conform to various shapes. However, these materials often experience performance failures when subjected to strain, which poses challenges for diagnosing electrical conducting failures and predicting their behaviour. To address these issues, a numerical modelling and simulation method is needed to predict the performance of stretchable conductive ink (SCIs) based on graphene nanoplatelets (GNPs). Furthermore, when the SCI/substrate system is subjected to mechanical loadings like stretching, torsion, and bending, it can affect the functionality of the SCI, leading to electrical failures. To overcome these challenges, finite element analysis (FEA) can be employed to simulate and observe the electrical performance of the printed electronics. However, to the best of our knowledge, predictive modelling to forecast the electrical performance of the printed electronics based on the development of stress and strain energy is yet to be studied. This thesis focuses on predicting the performance of the SCI/substrate system using the FEA method. The main goal of this study was to optimize the geometrical parameters of SCI using design of experiment (DOE) software through incorporation with finite element (FE) method. In an independent study, different shapes of silver conductors (straight, zigzag, square, and sinusoidal) were compared in terms of their impact on stress, strain, and electrical performance. The straight pattern exhibited the highest average von Mises stress and maximum principal strain, while the zigzag pattern showed the lowest stress and strain. These results aligned with experimental findings, indicating that increasing stress and strain decrease the maximum strain before conductivity is lost. To validate the simulation model, input parameters were acquired by subjecting both the thermoplastic polyurethane (TPU) substrate and formulated SCI to uniaxial tensile tests. The simulated results were then compared with the experimental data, and the model exhibiting quasi-static loading with non-linear material behaviour demonstrated the closest fit with the lowest peak stress error. Lastly, the development of equivalent plastic strain was predicted using the DoE method, considering the thickness and width parameters of the conductor. Through the optimization of geometrical parameters, a printed circuit with a thickness of 0.04 mm and width of 2.66 mm was found to produce the lowest maximum equivalent plastic strain. These optimized geometrical parameters enhance the stretchability of the SCI system, allowing for greater strain tolerance and reducing the likelihood of electrical failure when subjected to mechanical deformation. In summary, this research provides insights into the performance prediction and optimization of stretchable and flexible printed electronics based on graphene conductive materials. The combination of numerical modelling, simulation, and experimental validation offers valuable tools for enhancing the reliability and functionality of these systems in various applications.