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Edberg, J., Boda, U., Mulla, Y., Brooke, R., Pantzare, S., Strandberg, J., . . . Armgarth, A. (2023). A Paper‐Based Triboelectric Touch Interface: Toward Fully Green and Recyclable Internet of Things. Advanced Sensor Research, 2(1), Article ID 2200015.
Open this publication in new window or tab >>A Paper‐Based Triboelectric Touch Interface: Toward Fully Green and Recyclable Internet of Things
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2023 (English)In: Advanced Sensor Research, ISSN 2751-1219, Vol. 2, no 1, article id 2200015Article in journal (Refereed) Published
Abstract [en]

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.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:ri:diva-63313 (URN)10.1002/adsr.202200015 (DOI)
Note

The authors would like to acknowledge funding from Vinnova through theD igital Cellulose Competence Center (DCC), Diary number 2016–05193, the Swedish Foundation for Strategic Research (Smart Intra-body network; grant RIT15-0119), and the Norrköping municipality fund for research and development (Accessibility and remembering – storytelling and innovative media use in elderly care homes, 2020. Grant: KS 2020/0345). The work was also supported by Treesearch.se. The authors thank Patrik Isacsson and co-workers at Ahlstrom Munksjö for providing the paper substrates and for valuable know-how as part of the collaboration within DCC, as well as Erik Gabrielsson, Daniel Simon, Elisabet Cedersund, and Lars Herlogsson for their involvement in the work on the original Mediabook platform.

Available from: 2023-01-30 Created: 2023-01-30 Last updated: 2025-09-23Bibliographically approved
Armgarth, A., Pantzare, S., Arven, P., Lassnig, R., Jinno, H., Gabrielsson, E., . . . Berggren, M. (2021). A digital nervous system aiming toward personalized IoT healthcare. Scientific Reports, 11(1), Article ID 7757.
Open this publication in new window or tab >>A digital nervous system aiming toward personalized IoT healthcare
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2021 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 11, no 1, article id 7757Article in journal (Refereed) Published
Abstract [en]

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).

Place, publisher, year, edition, pages
Nature Research, 2021
National Category
Computer Sciences
Identifiers
urn:nbn:se:ri:diva-52956 (URN)10.1038/s41598-021-87177-z (DOI)2-s2.0-85104084403 (Scopus ID)
Note

Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: VINNOVA; Funding details: Japan Science and Technology Agency, JST; Funding details: Linköpings Universitet, LiU; Funding details: Knut och Alice Wallenbergs Stiftelse; Funding details: Centrum för Industriell Informationsteknologi, Linköpings Universitet, CENIIT, LiU; Funding text 1: Major funding for this work was provided by the Swedish Foundation for Strategic Research, Vinnova, and the Japanese Science and Technology Agency. Additional funding was provided by grants from the Knut and Alice Wallenberg Foundation and the Önnesjö Foundation. We wish to thank Andrey Maleev and Eric Claar (Linköping University) for electronic back end-design and implementation, Dr Tomoyuki Yokota and Hanbit Jin (University of Tokyo) for aid with sensor development and input, and Theofilos Kakantousis and Robin Anders-son (RISE SICS). The authors also thank Thor Balkhed (Linköping University) for filming, Jonas Askergren (NyTeknik) for inspiration and assistance with Fig. 1, Per Janson and Dr Robert Brooke (conceptualized.tech) for visualization input and movie editing, and Dr Jae Joon Kim for significant assistance in reviewing the manuscript.

Available from: 2021-04-23 Created: 2021-04-23 Last updated: 2025-09-23Bibliographically approved
Cherian, D., Armgarth, A., Beni, V., Linderhed, U., Tybrandt, K., Nilsson, D., . . . Berggren, M. (2019). Large-area printed organic electronic ion pumps [Letter to the editor]. Flexible and Printed Electronics, 4(2)
Open this publication in new window or tab >>Large-area printed organic electronic ion pumps
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2019 (English)In: Flexible and Printed Electronics, Vol. 4, no 2Article in journal, Letter (Other academic) Published
Abstract [en]

Biological systems use a large variety of ions and molecules of different sizes for signaling. Precise electronic regulation of biological systems therefore requires an interface which translates the electronic signals into chemically specific biological signals. One technology for this purpose that has been developed during the last decade is the organic electronic ion pump (OEIP). To date, OEIPs have been fabricated by micropatterning and labor-intensive manual techniques, hindering the potential application areas of this promising technology. Here we show, for the first time, fully screen-printed OEIPs. We demonstrate a large-area printed design with manufacturing yield >90%. Screen-printed cation- and anion-exchange membranes are both demonstrated with promising ion selectivity and performance, with transport verified for both small ions (Na+, K+, Cl) and biologically-relevant molecules (the cationic neurotransmitter acetylcholine, and the anionic anti-inflammatory salicylic acid). These advances open the 'iontronics' toolbox to the world of printed electronics, paving the way for a broader arena for applications.

National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-39699 (URN)10.1088/2058-8585/ab17b1 (DOI)2-s2.0-85070647335 (Scopus ID)
Available from: 2019-08-08 Created: 2019-08-08 Last updated: 2025-09-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1983-5297

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