Printed temperature sensor array for high-resolution thermal mapping
Abstract Fully-printed temperature sensor arrays—based on a flexible substrate and featuring a high spatial-temperature resolution—are immensely advantageous across a host of disciplines. These range from healthcare, quality and environmental monitoring to emerging technologies, such as artificial s...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-18321-6 |
| _version_ | 1811340412863905792 |
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| author | Tim Bücher Robert Huber Carsten Eschenbaum Adrian Mertens Uli Lemmer Hussam Amrouch |
| author_facet | Tim Bücher Robert Huber Carsten Eschenbaum Adrian Mertens Uli Lemmer Hussam Amrouch |
| author_sort | Tim Bücher |
| collection | DOAJ |
| description | Abstract Fully-printed temperature sensor arrays—based on a flexible substrate and featuring a high spatial-temperature resolution—are immensely advantageous across a host of disciplines. These range from healthcare, quality and environmental monitoring to emerging technologies, such as artificial skins in soft robotics. Other noteworthy applications extend to the fields of power electronics and microelectronics, particularly thermal management for multi-core processor chips. However, the scope of temperature sensors is currently hindered by costly and complex manufacturing processes. Meanwhile, printed versions are rife with challenges pertaining to array size and sensor density. In this paper, we present a passive matrix sensor design consisting of two separate silver electrodes that sandwich one layer of sensing material, composed of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). This results in appreciably high sensor densities of 100 sensor pixels per cm $$^2$$ 2 for spatial-temperature readings, while a small array size is maintained. Thus, a major impediment to the expansive application of these sensors is efficiently resolved. To realize fast and accurate interpretation of the sensor data, a neural network (NN) is trained and employed for temperature predictions. This successfully accounts for potential crosstalk between adjacent sensors. The spatial-temperature resolution is investigated with a specially-printed silver micro-heater structure. Ultimately, a fairly high spatial temperature prediction accuracy of 1.22 °C is attained. |
| first_indexed | 2024-04-13T18:40:36Z |
| format | Article |
| id | doaj.art-38f273a29b464fddb2ac2e2ad99fc421 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T18:40:36Z |
| publishDate | 2022-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-38f273a29b464fddb2ac2e2ad99fc4212022-12-22T02:34:43ZengNature PortfolioScientific Reports2045-23222022-08-0112111110.1038/s41598-022-18321-6Printed temperature sensor array for high-resolution thermal mappingTim Bücher0Robert Huber1Carsten Eschenbaum2Adrian Mertens3Uli Lemmer4Hussam Amrouch5University of Stuttgart, Semiconductor Test and Reliability (STAR)Karlsruhe Institute for Technology (KIT), Light Technology Institute (LTI)Karlsruhe Institute for Technology (KIT), Institute of Photonics and Quantum Electronics (IPQ)Karlsruhe Institute for Technology (KIT), Institute of Photonics and Quantum Electronics (IPQ)Karlsruhe Institute for Technology (KIT), Light Technology Institute (LTI)University of Stuttgart, Semiconductor Test and Reliability (STAR)Abstract Fully-printed temperature sensor arrays—based on a flexible substrate and featuring a high spatial-temperature resolution—are immensely advantageous across a host of disciplines. These range from healthcare, quality and environmental monitoring to emerging technologies, such as artificial skins in soft robotics. Other noteworthy applications extend to the fields of power electronics and microelectronics, particularly thermal management for multi-core processor chips. However, the scope of temperature sensors is currently hindered by costly and complex manufacturing processes. Meanwhile, printed versions are rife with challenges pertaining to array size and sensor density. In this paper, we present a passive matrix sensor design consisting of two separate silver electrodes that sandwich one layer of sensing material, composed of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). This results in appreciably high sensor densities of 100 sensor pixels per cm $$^2$$ 2 for spatial-temperature readings, while a small array size is maintained. Thus, a major impediment to the expansive application of these sensors is efficiently resolved. To realize fast and accurate interpretation of the sensor data, a neural network (NN) is trained and employed for temperature predictions. This successfully accounts for potential crosstalk between adjacent sensors. The spatial-temperature resolution is investigated with a specially-printed silver micro-heater structure. Ultimately, a fairly high spatial temperature prediction accuracy of 1.22 °C is attained.https://doi.org/10.1038/s41598-022-18321-6 |
| spellingShingle | Tim Bücher Robert Huber Carsten Eschenbaum Adrian Mertens Uli Lemmer Hussam Amrouch Printed temperature sensor array for high-resolution thermal mapping Scientific Reports |
| title | Printed temperature sensor array for high-resolution thermal mapping |
| title_full | Printed temperature sensor array for high-resolution thermal mapping |
| title_fullStr | Printed temperature sensor array for high-resolution thermal mapping |
| title_full_unstemmed | Printed temperature sensor array for high-resolution thermal mapping |
| title_short | Printed temperature sensor array for high-resolution thermal mapping |
| title_sort | printed temperature sensor array for high resolution thermal mapping |
| url | https://doi.org/10.1038/s41598-022-18321-6 |
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