Liquid Crystalline Polymers: Opportunities to Shape Neural Interfaces Academic Article uri icon

abstract

  • OBJECTIVES: Polymers have emerged as constituent materials for the creation of microscale neural interfaces; however, limitations regarding water permeability, delamination, and material degradation impact polymeric device robustness. Liquid crystal polymers (LCPs) have molecular order like a solid but with the fluidity of a liquid, resulting in a unique material, with properties including low water permeability, chemical inertness, and mechanical toughness. The objective of this article is to review the state-of-the-art regarding the use of LCPs in neural interface applications and discuss challenges and opportunities where this class of materials can advance the field of neural interfaces. MATERIALS AND METHODS: This review article focuses on studies that leverage LCP materials to interface with the nervous system in vivo. A comprehensive literature search was performed using PubMed, Web of Science (Clarivate Analytics), and Google Scholar. RESULTS: There have been recent efforts to create neural interfaces that leverage the material advantages of LCPs. The literature offers examples of LCP as a basis for implantable medical devices and neural interfaces in the form of planar electrode arrays for retinal prosthetic, electrocorticography applications, and cuff-like structures for interfacing the peripheral nerve. In addition, there have been efforts to create penetrating intracortical devices capable of microstimulation and resolution of biopotentials. Recent work with a subclass of LCPs, namely liquid crystal elastomers, demonstrates that it is possible to create devices with features that deploy away from a central implantation site to interface with a volume of tissue while offering the possibility of minimizing tissue damage. CONCLUSION: We envision the creation of novel microscale neural interfaces that leverage the physical properties of LCPs and have the capability of deploying within neural tissue for enhanced integration and performance.

author list (cited authors)

  • Rihani, R., Tasnim, N., Javed, M., Usoro, J. O., D'Souza, T. M., Ware, T. H., & Pancrazio, J. J.

citation count

  • 0

publication date

  • January 2021

publisher