Back to results

University of Illinois at Urbana-Champaign

3D biohybrid muscle electronics systems

Abstract

dc:description

Biohybrid systems consisting of biological components and artificial materials facilitate a better understanding of biological systems by recapitulating the functions and structures of native tissues. Biological machines using biohybrid systems with muscle cells or tissues and soft materials, can sense, respond, and adapt to environmental cues dynamically with biological/biomedical implications, useful for soft robotics and tissue-on-a-chip (TOC) applications. Integrating bioelectronics with such systems has a great potential to enhance its functionality such as electrical actuation of muscle, sensing of strain, and wireless communications. This thesis focuses on the integration of bioelectronics with in-vitro three-dimensional (3D) engineered skeletal muscle systems for muscle-on-a-chip and soft robotics applications. Given their similarity to biological systems in structure and function, 3D biohybrid tissue systems are more attractive than two-dimensional (2D) cell sheets-based models. However, 3D integration of electronics and soft tissue is challenging due to mechanical mismatch and planar geometry of conventional electronics systems. To overcome these limitations, novel materials fabrication approaches are introduced in the thesis. Graphene offers significant mechanical flexibility, electrical characteristics, and biocompatibility. A soft polyethylene glycol diacrylate (PEGDA) substrate was used to make a conformal integration of the graphene sheet with a millimeter-scale of 3D printed soft hydrogel structure instead of using a rigid poly (methyl methacrylate) (PMMA), a conventional supportive layer for graphene wet transfer. Such a 3D graphene electrode was integrated with 3D engineered skeletal muscle tissue, showing biocompatibility and muscular functionality with electrical stimulations via the graphene electrode. For electrical muscle strain sensing platform, a 3D framework capable of electrical strain sensing is introduced to integrate with 3D engineered optogenetic skeletal muscle tissue. The compliant 3D framework was fabricated using a polyimide backbone with metal trace patterns on a pre-strained soft elastomer. The 3D engineered optogenetic muscle tissue was integrated with the two pillars of the 3D framework that come out after the buckling process. The full Wheatstone bridge circuits integrated into each post enabled the electrical measurement and quantification of the muscle active contractile forces supported by quantitative simulations. Electrical sensing using the 3D framework instrument provided higher accuracy and temporal resolution than the conventional optical microscopy tracking method for measuring muscle force. Furthermore, the biohybrid muscle electronics system showed long-term sensing stability and biocompatibility when monitored over a month. In addition, its sensing capability enabled the drug and chemical dose-response studies of skeletal muscle tissue, demonstrating the potential for drug screening systems, disease modeling, and medical countermeasures. While the above two platforms are tethered for muscle-on-a-chip application, an untethered, muscle-driven wireless optoelectronics integrated robot is introduced in the following chapter. Integrating onboard electronics with biological machines can broaden a variety of novel applications across the fields of engineering, biology, and medicine. The hybrid bioelectronic muscle-driven robots were equipped with battery-free and micro-inorganic light-emitting diodes (μ-ILEDs) for wireless control and real-time communication. Additive manufacturing with 3D printing allowed the biohybrid robot design to host onboard optoelectronics, and its design and locomotion were optimized by computational evolutionary algorithm. These centimeter-scale bio-inspired bipedal walking robots utilized an onboard microcontroller with dual panels of μ-ILEDs to independently stimulate individual optogenetic skeletal muscle actuators, allowing for remote-control of advanced robotic functions including switching, walking, turning, plowing, transport, and manipulation of multiple robots. This work paves the way for the realization of advanced functionalities using wireless optogenetic control of advanced biohybrid robotics. Implementing biohybrid systems is highly interdisciplinary with materials science, bioengineering, mechanical and electrical engineering, and computational modeling. Through multidisciplinary approaches and active collaborations, 3D biohybrid muscle electronics systems have been introduced for advanced TOC and soft robotics applications. Integrating electronics and biohybrid systems can extend capabilities not only be shown in this thesis (ex. actuation, sensing, and wireless communication). In addition, the proposed platforms can be utilized with other types of tissue or multicellular systems for biological studies or biomedical applications. For example, integrating motor neurons with these systems would be an interesting future direction for developing neuromuscular junction (NMJ) driven autonomous biological machines and onboard neural computing.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Materials Science & Engr
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kim, Yongdeok
Contributors dc:contributor
  • Bashir, Rashid
  • Leal, Cecilia
  • Cao, Qing
  • Wang, Hua

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Partial content is pending publication. 2 years of the embargo is requested.
Language dc:language
en, eng

Identifiers

dc:identifier.*
Handle dc:identifier
https://hdl.handle.net/2142/115902

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kim, Yongdeok. 3D biohybrid muscle electronics systems. Dissertation thesis, University of Illinois at Urbana-Champaign, 2022. https://hdl.handle.net/2142/115902