Printed stretchable strain sensors for plant growth monitoring

Plants represent ~82% of the total biomass on earth and are critical to ecology and agriculture. However, the direct measurement of plant growth with minimal human intervention has been challenging. Wearable strain sensors have made a great impact in various areas including human motion detection, health monitoring, soft robotics, and electronic skin, but have rarely been applied to plant biology research. The few reported wearable strain sensors for measuring plant growth have limited stretchability due to their selected material systems (<200%), which limits their application in monitoring large plant elongation. To address this limitation, in Chapter 2, we have designed a transparent, conjugated polymer-based thin film strain sensor, which achieves a strain sensing range of ~7 times the original length. By leveraging the confinement effect attained through thin film printing, film crystallinity and crack development are suppressed, which largely increases the strain sensing range. After device engineering, the fabricated strain sensor shows high environmental stability, excellent linearity of sensor response, and good reproducibility, which are crucial factors for quantitative plant growth monitoring. Combining the strain sensor with a custom-built wireless autonomous resistance measurement system, we achieve remote, autonomous tracking of plant growth that unveils the circadian rhythm of leaf elongation challenging to obtain using other methods. In Chapter 3, we largely broaden the fields of application of our strain sensor in plant growth monitoring by both enhancing its stability and improving its stretchability. We first fabricate a strain sensor using room temperature cured Au-C-Al electrodes, which largely improve the sensor stability under direct light illumination. The sensors are successfully applied to various plant parts in a grow tent for growth monitoring, including the leaf and stem of tomato, and the cotyledon and fruit of cucumber. The sensor response can reflect changes in both elongation and radial growth rate in day/night cycles. Notably, the cucumber cotyledon is so far the youngest plant (3 days after germination) on which a strain sensor has been used for growth monitoring. In Chapter 4, we design and fabricate various encapsulated patterned strain sensors to further improve the strain sensing range using direct ink writing. To explain the electromechanical behavior of the patterned strain sensors, an elastic rope model is proposed. We found that both the shape and total contour length affect the amplification of strain, which contributes most to the strain sensing range. The most stretchable long horseshoe patterned strain sensor is finally attached to a grass leaf and reaches a maximum operating apparent strain of over 1000%, a new record in plant growth strain sensors. Overall, my thesis focuses on the development of printed stretchable strain sensors and engineering the sensors for real-life plant growth monitoring. The sensors have been applied to various plant parts successfully, demonstrating their effectiveness and versatility. The insights gained from this study will benefit the development of ultra-stretchable strain sensors and the autonomous growth monitoring of plants, taking a further step towards the era of smart agriculture.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Chemical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Wang, Siqing

Contributors dc:contributor

• Diao, Ying
• Leakey, Andrew DB
• Kong, Hyunjoon
• van der Zande, Arend M

• Wearable Strain Sensor
• Plant Growth Monitoring
• Precision Agriculture
• Conjugated Polymer
• Environmental Stability
• Meniscus-guided Printing
• Direct Ink Writing

Statement dc:rights

• Copyright 2024 Siqing Wang

Language dc:language

eng, en

Handle dc:identifier

https://hdl.handle.net/2142/127444

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/127444