The transition to a sustainable society is driving the development of green electronic solutions designed to have a minimal environmental impact. One promising route to achieve this goal is to construct electronics from biobased materials like cellulose, which is carbon neutral, non‐toxic, and recyclable. This is especially true for internet‐of‐things devices, which are rapidly growing in number and are becoming embedded in every aspect of our lives. Here, paper‐based sensor circuits are demonstrated, which use triboelectric pressure sensors to help elderly people communicate with the digital world using an interface in the form of an electronic “book”, which is more intuitive to them. The sensors are manufactured by screen printing onto flexible paper substrates, using in‐house developed cellulose‐based inks with non‐hazardous solvents. The triboelectric sensor signal, generated by the contact between a finger and chemically modified cellulose, can reach several volts, which can be registered by a portable microcontroller card and transmitted by Bluetooth to any device with an internet connection. Apart from the microcontroller (which can be easily removed), the whole system can be recycled at the end of life. A triboelectric touch interface, manufactured using printed electronics on flexible paper substrates, using cellulose‐based functional inks is demonstrated. These metal‐free green electronics circuits are implemented in an “electronic book” demonstrator, equipped with wireless communication that can control remote devices, as a step toward sustainable and recyclable internet‐of‐things devices.

Screen printed piezoelectric polyvinylidene fluoride?trifluoro ethylene (PVDF?TrFE)-based sensors laminated between glass panes in the temperature range 80?110?°C are presented. No degradation of the piezoelectric signals is observed for the sensors laminated at 110?°C, despite approaching the Curie temperature of the piezoelectric material. The piezoelectric sensors, here monitoring force impact in smart glass applications, are characterized by using a calibrated impact hammer system and standardized impact situations. Stand-alone piezoelectric sensors and piezoelectric sensors integrated on poly(methyl methacrylate) are also evaluated. The piezoelectric constants obtained from the measurements of the nonintegrated piezoelectric sensors are in good agreement with the literature. The piezoelectric sensor response is measured by using either physical electrical contacts between the piezoelectric sensors and the readout electronics, or wirelessly via both noncontact capacitive coupling and Bluetooth low-energy radio link. The developed sensor concept is finally demonstrated in smart window prototypes, in which integrated piezoelectric sensors are used to detect break-in attempts. Additionally, each prototype includes an electrochromic film to control the light transmittance of the window, a screen printed electrochromic display for status indications and wireless communication with an external server, and a holistic approach of hybrid printed electronic systems targeting smart multifunctional glass applications.

Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing—from multiple sensors—are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system. © 2021, The Author(s).