Award Abstract # 1841649
EAGER SitS: Bury and Forget Nitrogen Sensors Coupled With Remote Sensing for Soil Health

NSF Org: ECCS
Division of Electrical, Communications and Cyber Systems
Recipient: IOWA STATE UNIVERSITY OF SCIENCE AND TECHNOLOGY
Initial Amendment Date: September 6, 2018
Latest Amendment Date: September 6, 2018
Award Number: 1841649
Award Instrument: Standard Grant
Program Manager: Svetlana Tatic-Lucic
ECCS
 Division of Electrical, Communications and Cyber Systems
ENG
 Directorate for Engineering
Start Date: September 15, 2018
End Date: August 31, 2021 (Estimated)
Total Intended Award Amount: $150,000.00
Total Awarded Amount to Date: $150,000.00
Funds Obligated to Date: FY 2018 = $150,000.00
History of Investigator:
  • Jonathan Claussen (Principal Investigator)
    jcclauss@iastate.edu
Recipient Sponsored Research Office: Iowa State University
1350 BEARDSHEAR HALL
AMES
IA  US  50011-2103
(515)294-5225
Sponsor Congressional District: 04
Primary Place of Performance: Iowa State University
537 BISSELL RD
AMES
IA  US  50011-1096
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): DQDBM7FGJPC5
Parent UEI: DQDBM7FGJPC5
NSF Program(s): Special Projects - CNS,
CCSS-Comms Circuits & Sens Sys
Primary Program Source: 01001819DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 090E, 7916
Program Element Code(s): 171400, 756400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Excess fertilizer application from farm fields results in nitrogen runoff which causes major drinking water contamination as well as commercial fishing and tourism industry decline. Therefore, it is vitally important to have accurate predictive nitrogen soil models that can help farmers reduce fertilizer use by knowing exactly what type of fertilizer to use and precisely when and where in a field to apply. However, the accuracy of these soil models is lacking because soil nitrogen concentration data acquired at numerous points within a field is currently cost prohibitive and technically challenging. This research will create low-cost sensors that can electrically transmit soil nitrogen levels (ammonium and nitrate ion concentration levels) from various soil depths and locations to a central hub so that data can be transmitted through the internet and analyzed remotely. Sensors that can be fitted with low-cost data transmission electronics will be made of low-cost graphene (carbon) that is disposable and can be created using scalable manufacturing protocols. The completed sensors will be tested in the soils surrounding tomato plants to acquire high resolution spatial and temporal nitrogen data for improving soil nitrogen models that can be utilized by farmers.

The objective of this project is to develop bury-and-forget nitrogen sensors coupled with remote sensing technologies for real-time analysis of soil health. The sensors will be developed with flexible graphene electrodes functionalized with ionophore membranes for sensing of ammonium and nitrate ions in soils using laser inscribing and inkjet printing techniques (Aim 1). A network of these sensors will be developed using commercial Bluetooth-based mesh network modules for sensor power, computing, and communications (Aim 2). This project will elucidate the sensor depth and broadcast frequency that is capable/needed for successful in-soil nitrogen monitoring using a bucket brigade approach. This sensor network will be merged with existing crop models developed and challenged with in-field relevant conditions using a model tomato system in a testbed facility (Aim 3). The testbed facility will be used for collecting high resolution nitrogen sensor data from the soil coupled with monitoring of the Normalized Difference Vegetation Index of the plants as benchmarks to integrate remote sensing and real-time field measurements. The proposed project will lead to new: 1) wireless nitrogen sensors (both labile and mobile); 2) knowledge of spatiotemporal dynamics of soil nitrogen coupled with above ground plant physiology; 3) knowledge of scaling micro/nanosensor subsurface soil data, long-duration signal acquisition/curation, and pinpointing the maximum wireless data transmission depth in soil; and 4) best management practices for coupling soil sensor results to current field-scale tools such as remote sensing. The project will be the first to connect in-situ nanosensors, remote sensing, and crop modeling for the same sample, therein establishing a platform for improving understanding of soil biogeochemistry, sensor networks, and fundamental spatiotemporal scaling principles. This project will facilitate rapid studies for improving empirical model parameters (crop coefficients), as well as to validate assumptions in remote sensing (links between yellowing leaves and nutrient stress) and in-situ soil sensors (nutrient fate and transport). In addition to testing the developed sensor systems, this project will establish strategies and best practices for the development, testing, and deployment of soil nutrient sensors that can be reproduced anywhere for sensor testing and/or hypothesis testing, leading to improved models and observation networks to manage soil health. Such sensor networks and resultant models are expected to lead to precision agriculture where fertilizers are spread onto specific locations of the field in a metered fashion only when needed.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 14)
Chen, Bolin and Johnson, Zachary T. and Sanborn, Delaney and Hjort, Robert G. and Garland, Nate T. and Soares, Raquel R. and Van Belle, Bryan and Jared, Nathan and Li, Jingzhe and Jing, Dapeng and Smith, Emily A. and Gomes, Carmen L. and Claussen, Jonatha "Tuning the Structure, Conductivity, and Wettability of Laser-Induced Graphene for Multiplexed Open Microfluidic Environmental Biosensing and Energy Storage Devices" ACS Nano , v.16 , 2022 https://doi.org/10.1021/acsnano.1c04197 Citation Details
Garland, Nate T. and McLamore, Eric S. and Cavallaro, Nicholas D. and Mendivelso-Perez, Deyny and Smith, Emily A. and Jing, Dapeng and Claussen, Jonathan C. "Flexible Laser-Induced Graphene for Nitrogen Sensing in Soil" ACS Applied Materials & Interfaces , v.10 , 2018 https://doi.org/10.1021/acsami.8b10991 Citation Details
Hall, Lucas S. and Hwang, Dohgyu and Chen, Bolin and Van Belle, Bryan and Johnson, Zachary T. and Hondred, John A. and Gomes, Carmen L. and Bartlett, Michael D. and Claussen, Jonathan C. "All-graphene-based open fluidics for pumpless, small-scale fluid transport via laser-controlled wettability patterning" Nanoscale Horizons , 2021 https://doi.org/10.1039/D0NH00376J Citation Details
Hjort, Robert G. and Pola, Cícero C. and Soares, Raquel R. and Opare-Addo, Jemima and Smith, Emily A. and Claussen, Jonathan C. and Gomes, Carmen L. "Laser-Induced Graphene Decorated with Platinum Nanoparticles for Electrochemical Analysis of Saliva" ACS Applied Nano Materials , v.6 , 2023 https://doi.org/10.1021/acsanm.3c03786 Citation Details
Hondred, John A. and Medintz, Igor L. and Claussen, Jonathan C. "Enhanced electrochemical biosensor and supercapacitor with 3D porous architectured graphene via salt impregnated inkjet maskless lithography" Nanoscale Horizons , v.4 , 2019 https://doi.org/10.1039/C8NH00377G Citation Details
Johnson, Zachary T. and Williams, Kelli and Chen, Bolin and Sheets, Robert and Jared, Nathan and Li, Jingzhe and Smith, Emily A. and Claussen, Jonathan C. "Electrochemical Sensing of Neonicotinoids Using Laser-Induced Graphene" ACS Sensors , v.6 , 2021 https://doi.org/10.1021/acssensors.1c01082 Citation Details
Kucherenko, Ivan S. and Chen, Bolin and Johnson, Zachary and Wilkins, Alexander and Sanborn, Delaney and Figueroa-Felix, Natalie and Mendivelso-Perez, Deyny and Smith, Emily A. and Gomes, Carmen and Claussen, Jonathan C. "Laser-induced graphene electrodes for electrochemical ion sensing, pesticide monitoring, and water splitting" Analytical and Bioanalytical Chemistry , v.413 , 2021 https://doi.org/10.1007/s00216-021-03519-w Citation Details
Kucherenko, Ivan S. and Sanborn, Delaney and Chen, Bolin and Garland, Nate and Serhan, Michael and Forzani, Erica and Gomes, Carmen and Claussen, Jonathan C. "IonSelective Sensors Based on LaserInduced Graphene for Evaluating Human Hydration Levels Using Urine Samples" Advanced Materials Technologies , v.5 , 2020 https://doi.org/10.1002/admt.201901037 Citation Details
McLamore, Eric S. and Alocilja, Evangelyn and Gomes, Carmen and Gunasekaran, Sundaram and Jenkins, Daniel and Datta, Shoumen P.A. and Li, Yanbin and Mao, Yu (Jessie) and Nugen, Sam R. and Reyes-De-Corcuera, José I. and Takhistov, Paul and Tsyusko, Olga an "FEAST of biosensors: Food, environmental and agricultural sensing technologies (FEAST) in North America" Biosensors and Bioelectronics , v.178 , 2021 https://doi.org/10.1016/j.bios.2021.113011 Citation Details
Parate, Kshama and Pola, Cícero C. and Rangnekar, Sonal V. and Mendivelso-Perez, Deyny L. and Smith, Emily A. and Hersam, Mark C. and Gomes, Carmen L. and Claussen, Jonathan C. "Aerosol-jet-printed graphene electrochemical histamine sensors for food safety monitoring" 2D Materials , v.7 , 2020 https://doi.org/10.1088/2053-1583/ab8919 Citation Details
Parate, Kshama and Rangnekar, Sonal V. and Jing, Dapeng and Mendivelso-Perez, Deyny L. and Ding, Shaowei and Secor, Ethan B. and Smith, Emily A. and Hostetter, Jesse M. and Hersam, Mark C. and Claussen, Jonathan C. "Aerosol-Jet-Printed Graphene Immunosensor for Label-Free Cytokine Monitoring in Serum" ACS Applied Materials & Interfaces , v.12 , 2020 10.1021/acsami.9b22183 Citation Details
(Showing: 1 - 10 of 14)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

This project produced a rapid and inexpensive method for monitoring multiple fertilizer ions in soil.  The project developed these sensors using laser induced graphene that were coated with ion selective membranes.  The finalized sensors were able to continuously monitor nitrate, ammonium, and potassium ions in soil slurries and water solutions for months with negligible interference from other ions.  The sensors were fitted to soil probes and used to monitor these fertilizer ions in soils.  Electronics with wireless transmission capabilities were developed to power the sensors and transmit the data out of soils to a central network so that data could be collected without removing the sensors from the soil.   

The data collected from the soil sensors could be used to predict nitrogen variations in distinct plant crops, field contours, and field drainage conditions. More broadly speaking, distributing networks of these sensors could lead to precision agriculture where fertilizers are spread onto only certain locations of the farm field in a metered fashion only when needed. Also, the transmission of data out of soils has been a challenge to the scientific community and hence the knowledge gained in this project could be useful for a wide variety of engineers and scientists who are interested in developing precision agriculture tools that are connected to the internet.

The project also elucidated some key techniques for developing graphene-based sensors and ion sensor development in general. The project made some important discoveries on how the electrical conductivity, surface roughness, and surface wettability could be distinctly changed to produce ion selective sensors that experienced less noise and were more stable so that they could be used for months of operation.  These material properties were also changed to create graphene-based open channels (i.e., open microfluidics) that could split and transport a single field sample to distinct ion selective sensors so that nitrate, ammonium, and potassium could be measured simultaneously (i.e., multiplexed sensing).  Hence this project demonstrated the versatility of laser induced graphene and its ability for superior performance over conventional sensor materials.  More broadly, the techniques developed in this project to create and tune laser induced graphene could be applied to a wide variety of electronic electrochemical devices beyond sensors including energy harvesting devices, salt desalination devices, and water splitting devices for example.

 


Last Modified: 02/06/2022
Modified by: Jonathan C Claussen

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