Award Abstract # 1706597
RUI:Development of a portable ECL immunosensor with mobile technologies

NSF Org: CBET
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Recipient: ANDREWS UNIVERSITY
Initial Amendment Date: June 9, 2017
Latest Amendment Date: March 25, 2021
Award Number: 1706597
Award Instrument: Standard Grant
Program Manager: Aleksandr Simonian
asimonia@nsf.gov
 (703)292-2191
CBET
 Division of Chemical, Bioengineering, Environmental, and Transport Systems
ENG
 Directorate for Engineering
Start Date: July 1, 2017
End Date: June 30, 2022 (Estimated)
Total Intended Award Amount: $249,198.00
Total Awarded Amount to Date: $249,198.00
Funds Obligated to Date: FY 2017 = $249,198.00
History of Investigator:
  • Hyun Kwon (Principal Investigator)
    hkwon@andrews.edu
  • Rodney Summerscales (Co-Principal Investigator)
  • Padma Tadi Uppala (Co-Principal Investigator)
Recipient Sponsored Research Office: Andrews University
4150 ADMINISTRATION DR
BERRIEN SPRINGS
MI  US  49104-1400
(269)471-3100
Sponsor Congressional District: 05
Primary Place of Performance: Andrews University
4260 Admin Dr.
Berrien Springs
MI  US  49104-0370
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): QXJLKBKFT4H7
Parent UEI:
NSF Program(s): BIOSENS-Biosensing
Primary Program Source: 01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9229
Program Element Code(s): 790900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Mobile technology is becoming the hub of future biosensor development. The proposed work attempts to develop an Electrochemiluminescence (ECL) sensor utilizing existing mobile (smartphone) technology, transforming what was traditionally an expensive and bulky biosensor technology into a portable and affordable one. ECL sensors work by a simple principle - when a small electric voltage is applied to an ECL chemical, the chemical emits light. The ECL combined with mobile technology enables minimal instrumentation and mobile app analysis. Our goal is to make this new sensor platform equivalent not only in performance to that of existing expensive biosensors, but also more affordable and for many different biosensor needs.

The goal of this project is to advance the traditional electrochemiluminescence (ECL) immunosensor instrumentation to make it more portable and inexpensive using the latest mobile technologies. When an ECL reaction is triggered by the application of electric potential, the emitted light is in a visible spectrum, providing a great potential to satisfy the requirements for an ultra-sensitive immunoassay and in an ultra-compact format. Successful development of the proposed ECL biosensor will significantly enhance biosensor instrumentation by maximizing the practicality of mobile technologies while providing the sensitivity realized by expensive and specialized instruments. There have been attempts to develop ECL sensor with cell phone detectors but they have not been successful in detecting biomarkers at clinically relevant concentrations. The key effort of the proposed work are enhancing the inherently low ECL signal to a level that is detectable with consumer cameras and developing minimal instrumentation for efficient ECL-based detection. The research will focus on design as well as development of protocols with co-reactants, microfluidic channels on screen-printed-electrodes, electric circuits to trigger reactions, and a mobile app to control the circuit, imaging, and data analysis. The ECL immunosensor can be used for diagnosis of disease biomarkers. Its inexpensive and portable nature will make it an ideal platform to use in disaster rescue and recovery situations. The project will be performed at an undergraduate predominant institute maximizing educational aspects and emphasizing the community outreach.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Ccopa Rivera, Elmer and Swerdlow, Jonathan J. and Summerscales, Rodney L. and Uppala, Padma P. and Maciel Filho, Rubens and Neto, Mabio R. and Kwon, Hyun J. "Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence" Sensors , v.20 , 2020 10.3390/s20030625 Citation Details
Kwon, Hyun J. and Rivera, Elmer Ccopa and Neto, Mabio R.C. and Marsh, Daniel and Swerdlow, Jonathan J. and Summerscales, Rodney L. and Tadi Uppala, Padma P. "Development of smartphone-based ECL sensor for dopamine detection: Practical approaches" Results in Chemistry , v.2 , 2020 10.1016/j.rechem.2020.100029 Citation Details
Rivera, Elmer C. and Assumpção, Daniel C. and Kwon, Hyun J. and Okonkwo, Christopher C. and Ezeji, Thaddeus C. and Filho, Rubens M. and Mariano, Adriano P. "Mechanistic modeling of redox balance effects on the fermentation of eucalyptus wood-derived xylose to acetone-butanol-ethanol" Biochemical Engineering Journal , v.190 , 2023 https://doi.org/10.1016/j.bej.2022.108738 Citation Details
Rivera, Elmer C. and Taylor, Joseph W. and Summerscales, Rodney L. and Kwon, Hyun J. "Quenching Behavior of the Electrochemiluminescence of Ru(bpy) 3 2+ /TPrA System by Phenols on a SmartphoneBased Sensor" ChemistryOpen , v.10 , 2021 https://doi.org/10.1002/open.202100151 Citation Details
Rivera, Elmer Ccopa and Summerscales, Rodney L. and Tadi Uppala, Padma P. and Kwon, Hyun J. "Electrochemiluminescence Mechanisms Investigated with SmartphoneBased Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis" ChemistryOpen , v.9 , 2020 https://doi.org/10.1002/open.202000165 Citation Details
Taylor, Joseph and Ccopa-Rivera, Elmer and Kim, Solomon and Campbell, Reise and Summerscales, Rodney and Kwon, Hyun "Machine Learning Analysis for Phenolic Compound Monitoring Using a Mobile Phone-Based ECL Sensor" Sensors , v.21 , 2021 https://doi.org/10.3390/s21186004 Citation Details

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.

Electrochemiluminescence is a physical phenomenon where a simple voltage application trigger visible light emission, enabling a compact instrumentation and removing noise from light contamination.  We developed an ECL sensor apparatus to be compact and portable taking advantage of recent advance of mobile devices and its wireless connections.   The mobile phone-based ECL sensor consisted of a phone cameras, disposable screen printed electrodes, a compact potentiostat, a light-tight 3D printed housing, and mobile apps.  The sensor was developed to obtain  video or time series pictures  and amperogram signals simultaneously.  Dopamine was detected as a model target sample with the linear detection range from 1 -50 microM.   The sensor also was developed into detecting other phenolic compounds such as vanillic acid and p-courmaric acid reaching target sensing ranges in the practical samples.  One of the most important aspect of the sensor development was data analysis.  As the sensor is aimed to be assembled for low cost setting, it was critical to have a robust data analysis.   We have developed classical mechanistic model and also data-driven machine learning based methodologies.  The machine learning approaches provided a practical solution to a realistic low-cost sensor setting where sensor-to-sensor variations, nonlinearity, data fluctuation becomes a challenge in predicting analyte concentrations accurately. The effort offers new opportunities for the development of inexpensive analytical methods and compact sensors using the ubiquitous mobile device technologies.

 


Last Modified: 12/13/2022
Modified by: Hyun Kwon

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