Morphological investigation of self-healing polymer composites and blends for deformation and damage sensing applications

The stretchable electronics used in soft robotics represent exciting frontiers offering
significant advantages across various applications. These innovative technologies are
designed to be flexible, adaptable, and resilient, which allows for integration into
environments and devices that require dynamic movement and interaction. However, the
susceptibility of the soft substrates to damage is detrimental and their failure has
catastrophic consequences. Therefore, the reliability of products can significantly be
improved by utilizing self-healing materials that repair damages before they grow into larger
issues. This research focuses on the use of self-healing polymers based on a
thermoreversible Diels-Alder reaction between furan and maleimide reacting groups. These
dynamic covalent bonds create reversibly crosslinked networks where thermal reversibility
not only enables the reprocessing and recycling of the network but also allows the polymer
network structure to recover its properties favoring sustainable manufacturing. This work
aims to develop self-healing formulations for deformation and damage-sensing applications
that revolve around reversible Diels-Alder polymers. With the central point of structure-
property-application relationships and with emphasis on the influence of the network design
parameters Diels-Alder-based polymer composites or polymer blends were synthesized. As
a first attempt by meticulously integrating hybrid fillers including carbon black particles and
nanoclay platelets into the Diels-Alder network, self-healing electrically conductive
composites were developed that synergistically benefit from enhanced electrical and self-
healing properties. Hence, the self-healing conductive composite was used as a conducting
component to fabricate self-healing strain sensors with decent electromechanical
performance. These sensors could recover their properties after damage-healing cycles. To
explore other potentials of these Diels-Alder networks and to benefit from high electrical
conductivity combined with superior stretchability, in the second attempt a liquid metal was
chosen as the conducting component of the strain sensor. In this case, the challenge was to
preserve the shape of the liquid metal and avoid its oxidation. The flowability of the liquid
metal, which serves as an inherent self-healing behavior combined with the stretchable and
self-healing encapsulant provided a route to the fabrication of self-healing liquid metal-
based strain sensors. Since soft polymers suffer from poor barrier properties against water
and oxygen a blending procedure was considered as a solution. Two dynamic covalent
networks based on the Diels-Alder reaction were blended to exploit the properties of the
immiscible polymer backbones. By relying on the hydrophobicity of two chemistries and with
choosing the right blend/network design parameters phase-separated morphologies evolved
that compromised the trade-off between the mechanical flexibility and barrier properties of
the polymer encapsulant. This compromise could successfully pave the way for fabricating
liquid metal-based strain sensors that show decent sensitivity and linearity in the
electromechanical response. Moreover, owing to the special design of the sensor its
electrical response with almost no hysteresis was independent of the polymer network
dynamics. This addressed the hysteresis of the sensor arising from the viscoelasticity of the
polymers. These findings indicated that the Diels-Alder-based self-healing polymers can be
effectively engineered to serve as substrates for conductive materials, offering promising
potential for the future of wearable technologies, stretchable electronic devices, and soft
robotic systems.