Self-adhesive polyurethane via selective photo-polymerization for biocompatible epidermal soft sensor and thermal heater
Source abstract
Abstract
Polyurethane (PU) is the most extensively used soft backbone substrate for wearable applications. However, even with biocompatibility and stretchability, PU-based wearable devices are unsuitable for epidermal devices because they lack of adhesive properties. To impart adhesive properties to PU, commercial adhesive additives are required or the mixing ratio of specific materials should be adjusted. Despite PU biocompatibility, additional additives cause skin damage because they are not usually biocompatible due to their toxic ingredient. This study introduces a simple method of fabricating self-adhesive polyurethane (SAPU) without specific adhesive additives for a biocompatible epidermal soft sensor and an attachable epidermal thermal heater. During the selective photo-polymerization of PU resin, the defective crosslinking networks between laser-scanned resin lines enhance the adhesive properties of PU. Adjusting photopolymerization conditions results in self-adhesive polyurethane with high adhesiveness and low Young's modulus comparable to those of human skin. A mouse skin toxicity test confirms the biocompatibility and highly conformal contact of SAPU. SAPU is then further applied for the fabrication of a biocompatible epidermal soft sensor and an attachable epidermal thermal heater with silver nanowire network. The fabricated self-adhesive epidermal soft sensor successfully detects human motion and bio-signals, whereas the self-adhesive epidermal soft heater efficiently transfers heat to the epidermis due to its excellent conformal contact characteristics on the human skin. (c) 2022ElsevierLtd. Allrightsreserved.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Tactile and Sensory Interactions · Polymer composites and self-healing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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