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Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence.
Sensors (Basel). 2020 Jan 23;20(3):625. doi: 10.3390/s20030625.
Sensors (Basel). 2020.
PMID: 31979213
Free PMC article.
Machine Learning Analysis for Phenolic Compound Monitoring Using a Mobile Phone-Based ECL Sensor.
Taylor J, Ccopa-Rivera E, Kim S, Campbell R, Summerscales R, Kwon H.
Taylor J, et al.
Sensors (Basel). 2021 Sep 8;21(18):6004. doi: 10.3390/s21186004.
Sensors (Basel). 2021.
PMID: 34577213
Free PMC article.
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Electrochemiluminescence Mechanisms Investigated with Smartphone-Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis.
Rivera EC, Summerscales RL, Tadi Uppala PP, Kwon HJ.
Rivera EC, et al. Among authors: summerscales rl.
ChemistryOpen. 2020 Aug 19;9(8):854-863. doi: 10.1002/open.202000165. eCollection 2020 Aug.
ChemistryOpen. 2020.
PMID: 32832344
Free PMC article.
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Quenching Behavior of the Electrochemiluminescence of Ru(bpy)32+ /TPrA System by Phenols on a Smartphone-Based Sensor.
Rivera EC, Taylor JW, Summerscales RL, Kwon HJ.
Rivera EC, et al. Among authors: summerscales rl.
ChemistryOpen. 2021 Aug;10(8):842-847. doi: 10.1002/open.202100151.
ChemistryOpen. 2021.
PMID: 34409773
Free PMC article.
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