Polyurethane/Carbon Nanotube-Based ThermoSense Electronic Skin: Perception to Decision Making Aided by Internet of Things Brain

Human skin has several receptors collaborating with the brain to provide appropriate “decisions” when applying stimuli. Several research articles state that biomimetic electronic skin (e-skin) is reportedly used for sensor-related applications and performs similarly to natural skin. However, research reporting the capability of the e-skin to make decisions and therefore react upon exposure to adverse conditions is still in its nascent stage. Herein, we report the development of an e-skin, ThermoSense, that can thermoregulate by making appropriate decisions. Thermoplastic polyurethane and multiwalled carbon nanotubes were used as the model composite. The heating and sensing capabilities of the optimized e-skin were studied in detail. In the study window, the e-skin demonstrated excellent electrothermal conversion efficiency by generating a temperature of 192 °C, consuming a power of 2.23 W. A finite element modeling (FEM) was adopted to determine the distribution of the filler in the case of the optimized e-skin and thus was used to probe the reason for the heating across the e-skin via mapping of the internal energy across the sample. FEM results and experimental findings are in strong agreement. Additionally, the e-skin demonstrated its capability to act as a thermal sensor with a 0.947% °C –1 sensitivity. To integrate the decision-making capabilities of the e-skin, an Internet of Things (IoT) brain console was made using the e-skin and electronic chips by leveraging More than Moore’s concept. The IoT brain was automated with decision-making programming that was controllable via an in-house-developed mobile application. The console worked exclusively under simulated conditions. When there was a shift from the set point temperature, it started to heat. Postusage, the e-skin matrix was recycled, and the recycled e-skin demonstrated a marginal decrement in performance attributes. This study opens new avenues for developing decision-making e-skins for next-generation human–machine interphases.