2022
DOI: 10.1021/acs.est.2c01501
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Electrospraying Zwitterionic Copolymers as an Effective Biofouling Control for Accurate and Continuous Monitoring of Wastewater Dynamics in a Real-Time and Long-Term Manner

Abstract: Long-term continuous monitoring (LTCM) of water quality can provide high-fidelity datasets essential for executing swift control and enhancing system efficiency. One roadblock for LTCM using solid-state ion-selective electrode (S-ISE) sensors is biofouling on the sensor surface, which perturbs analyte mass transfer and deteriorates the sensor reading accuracy. This study advanced the anti-biofouling property of S-ISE sensors through precisely coating a self-assembled channel-type zwitterionic copolymer poly(tr… Show more

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Cited by 11 publications
(19 citation statements)
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“…41,42 Before clustering, all the MEA sensor data were processed with denoising data processing algorithm (DDPA) previously developed to alleviate the data drifting caused by electronic hardware problems (e.g., unstable sensor connections) and/or sensor material deterioration in the AD system (e.g., suspended particle attachment, S-ISM polymer matrix leaching). 25,38 The details of the MLA data set are demonstrated in Table S1. To fully exploit the MAPS and ADSS data, four MLAs (logistic regression (LR), Support vector machines (SVM), Artificial neural network (ANN), and ensembled random forest (RF)) regularly used in wastewater and AD studies were selected given their good prediction accuracy while being trained on water parameters (e.g., pH, conductivity, temperature).…”
Section: Machine Learning Algorithm (Mla) Setup and Post Hoc Validationmentioning
confidence: 99%
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“…41,42 Before clustering, all the MEA sensor data were processed with denoising data processing algorithm (DDPA) previously developed to alleviate the data drifting caused by electronic hardware problems (e.g., unstable sensor connections) and/or sensor material deterioration in the AD system (e.g., suspended particle attachment, S-ISM polymer matrix leaching). 25,38 The details of the MLA data set are demonstrated in Table S1. To fully exploit the MAPS and ADSS data, four MLAs (logistic regression (LR), Support vector machines (SVM), Artificial neural network (ANN), and ensembled random forest (RF)) regularly used in wastewater and AD studies were selected given their good prediction accuracy while being trained on water parameters (e.g., pH, conductivity, temperature).…”
Section: Machine Learning Algorithm (Mla) Setup and Post Hoc Validationmentioning
confidence: 99%
“…The Nernstian response maintains the best performance between 0 and 1500 mg/L (∼1200 mg/ L of AD NH the MAPS data errors. 25,38 The electrochemical response had severe noises (Figure S2) with the signal-noise-ration (SNR) of only 1.33 (vs. good signals: >25 25 ). Through the DDPA preprocessing, the discrepancy of Nernstian-based open-circuit potential sensor readings (NH 4 + , pH, and ORP) from the labbased validation results was reduced to 0.11%, 1.33%, and 4.72%, respectively.…”
Section: Characterization Of the Ad System In A Real-time In Situ Mod...mentioning
confidence: 99%
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“…It should be underscored that CF-MSP-ISM sensors only had a single calibration before being deployed in wastewater for 14 days and functioned accuracy without additional calibration. Sensors in other studies were calibrated on a daily basis to minimize data drifting effects and maintain sensor reading accuracy 9,17 . This exceptional long-term wastewater monitoring performance was mainly ascribed to the enhancement of anti-fouling capability (Fig.…”
Section: Evaluate Recalibration-free Capability Of Multiple Pieces Of...mentioning
confidence: 99%
“…The copolymer and non-solvent solution were co-electrosprayed in order to induce copolymer precipitation. The coated membrane utilizes the microphase separation of the zwitterionic copolymer to form hydrophilic nanochannels acting as pores to mitigate biofouling without compromising the diffusion of primary ions (e.g., NH4+ for NH4+ S-ISE sensors) throughout the ISM matrix and augment the long-term accuracy and stability of the S-ISE sensors in wastewater [ 132 ].…”
Section: Monocomponent/multicomponent Particlesmentioning
confidence: 99%