Stanford Engineering
Micro and Nano Mechanics Group

Stretchable Elastomers

Yikai Yin, Yanming Wang, Xiaohan Zhang, Lihua Jin, Shaswat Mohanty

Conducting, semiconducting and insulating polymers offer potential to realize intrinsically stretchable electronic devices.  However, existing semiconducting polymers are brittle.  They need to be blended with elastomers to become stretchable but doing so may degrade their electronic properties.  How to make stretchable polymers with satisfactory electronic properties remains a significant challenge.

We use a multiscale modeling approach to understand the relationship between molecular configurations of polymers and their mechanical behavior during stretching.  A major goal is to predict the fracture toughness of an elastomer from the molecular bond properties (bond strength, density, distribution, etc.).

At the smallest length/time scale, we perform coarse-grained molecular dynamics (CGMD) simulations of polymer molecules using the LAMMPS program (see figure below illustrating the simulation procedure).

The following figures show the stress-strain curves and number of broken bonds as a function of strain during loading/unloading cycles.
 

The stress-strain relations from CGMD are used to construct a finite element model for the elastomer containing a crack. We also perform experiments to measure the fracture toughness of elastomers with different cross-linking bond densities. We present the shortest paths (SPs) between distant cross-links in a polymer network as a key microstructural descriptor. It is the shortest paths in the polymer network that carry a majority of the load and are most susceptible to failure, as a result, this microstructural descriptor of the SP between distant cross-links is a novel approach formulated by our group and is vital to explaining the macroscopic response of polymers.
 

More importantly, we see that this descriptor is successful in explaining the behavior of more exotic systems such as dynamic polymer networks (DPNs) which are better known as self-healing polymers. The most unique features of this special class of polymers are their self-healing behavior and rapid stress-relaxation they exhibit due to the presence of dynamic cross-links, which allow the cross-links to break and reform, resulting in significant topological transformations. The SP between distant cross-links is successful in explaining the macroscopic response of DPNs as well.

Having established the SP between distant cross-links as a key microstructural descriptor, we come up with an alternate method of obtaining the average shortest path as a function of the cross-link density as well as the SP distribution. This is because equilibrating the CGMD simulation to obtain equilibrium network statistics is a time-consuming process. To this end, we use a branching random walk model, implemented as PolyBranchX, which successfully reproduces the network statistics.
 

Publications

  • Yikai Yin, Shaswat Mohanty, Christopher B. Cooper, Zhenan Bao and Wei Cai, "Network evolution controlling strain-induced damage and self-healing of elastomers with dynamic bonds", to be submitted (2024). [arXiv]
  • Zhenyuan Zhang, Shaswat Mohanty, Jose Blanchet and Wei Cai, "Modeling Shortest Paths in Polymeric Networks using Spatial Branching Processes", submitted (2023). [arXiv]
  • Yikai Yin, Nicolas Bertin, Yanming Wang, Zhenan Bao and Wei Cai, "Topological origin of strain induced damage of multi-network elastomers by bond breaking", Extreme Mechanics Letters, in press (2020). [arXiv] [DOI]
  • Christopher B. Cooper, Jiheong Kang, Yikai Yin, Zhiao Yu, Hung-Chin Wu, Shayla Nikzad, Yuto Ochiai, Hongping Yan, Wei Cai, and Zhenan Bao, "Multivalent Assembly of Flexible Polymer Chains into Supramolecular Nanofibers", Journal of the American Chemical Society, 142, 16814, (2020).
  • Jie Xu, Sihong Wang, Ging-Ji Nathan Wang, Chenxin Zhu, Shaochuan Luo, Lihua Jin, Yanming Wang, Christian Linder, Wei Cai, Jeffery B.-H. Tok, Jong Won Chung, Zhenan Bao, et al. "Highly Stretchable Polymer Semiconductor Films through Nanoconfinement Effect", Science, 355, 59 (2017).