Spatiotemporal imaging of electrocatalytic activity on single 2D gold nanoplates <i>via</i> electrogenerated chemiluminescence microscopy

Chen, Mingming; Zhao, Wei; Zhu, Meiying; Li, Xiangling; Xu, Conghui; Chen, Hong‐Yuan; Xu, Jing‐Juan

doi:10.1039/c9sc00889f

Cited by 67 publications

(67 citation statements)

References 33 publications

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“…The electrochemiluminescence and its related mechanism are being extensively investigated due to its important application as a platform of light-emitting sensors and an analytical detection technique. [11,15,26,27] This study does not intend to deepen theoretical studies of the ECL mechanism of the Ru(bpy) 3 2 + /TPrA system, but rather to illustrate that the parameter estimation procedure of a complex system can be a straightforward task. Thus, this study used the reaction mechanisms originally proposed by Miao et al, [8] which are described in Eqs.…”

Section: Ecl Mechanism and Theoretical Aspectsmentioning

confidence: 99%

“…These reactions have been used for simulation purposes in several theoretical studies. [10,15,28] 2.1.1.…”

Section: Ecl Mechanism and Theoretical Aspectsmentioning

confidence: 99%

“…7- (14), R 1 and R 2 represent the charge-transfer reaction rates expressed by Eqs. (15) and (16), respectively, whereas R 3 to R 6 represent the homogeneous reaction rates expressed by Eqs. 17- (20), respectively (mM/s).…”

Section: Conservation Equationsmentioning

confidence: 99%

“…In this study, the parameters k f 1 , k b 1 , k f 2 and k b 2 in Eqs. (15) and (16) are modeled using the Butler-Volmer-type Eqs. 21to (24), respectively.…”

Section: Conservation Equationsmentioning

confidence: 99%

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Electrochemiluminescence Mechanisms Investigated with Smartphone‐Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

et al. 2020

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The present study introduces a unified framework combining a mechanistic model with a genetic algorithm (GA) for the parameter estimation of electrochemiluminescence (ECL) kinetics of the Ru(bpy)32+/TPrA system occurring in a smartphone‐based sensor. The framework allows a straightforward solution for simultaneous estimation of multiple parameters which can be, otherwise, time‐consuming and lead to non‐convergence. Model parameters are estimated by achieving a high correlation between the model prediction and the measured ECL intensity from the ECL sensor. The developed model is used to perform a sensitivity analysis (SA), which provides quantitative effects of the model parameters on the concentrations of chemical species involved in the system. The results demonstrate that the GA‐based parameter estimation and the SA approaches are effective in analyzing the kinetics of the ECL mechanism. Therefore, these approaches can be incorporated as analysis tools in the ECL kinetics study with practical application in the calibration of mechanistic models for any required sensing condition.

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Section: Ecl Mechanism and Theoretical Aspectsmentioning

confidence: 99%

“…These reactions have been used for simulation purposes in several theoretical studies. [10,15,28] 2.1.1.…”

Section: Ecl Mechanism and Theoretical Aspectsmentioning

confidence: 99%

Section: Conservation Equationsmentioning

confidence: 99%

“…In this study, the parameters k f 1 , k b 1 , k f 2 and k b 2 in Eqs. (15) and (16) are modeled using the Butler-Volmer-type Eqs. 21to (24), respectively.…”

Section: Conservation Equationsmentioning

confidence: 99%

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Electrochemiluminescence Mechanisms Investigated with Smartphone‐Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

et al. 2020

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“…For this, it is necessary to obtain the experimental measurements of the main state variables (e.g., concentration of luminophore and co-reactant) over the course of ECL reaction at regular time intervals, which is not a straightforward task [6]. The proper choice of the reaction rates and their corresponding kinetic parameters to propose a reliable mechanistic model is the subject of considerable discussion in recent literature [6,7,15,16]. In other approaches, the so-called calibration curve, i.e., a regression equation, can be useful to infer the concentration of Ru(bpy) 2+ 3 if it is correlated with a key feature of the system such as the maximum value of the ECL intensity.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence

Rivera

Swerdlow

Summerscales

et al. 2020

Sensors

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Understanding relationships among multimodal data extracted from a smartphone-based electrochemiluminescence (ECL) sensor is crucial for the development of low-cost point-of-care diagnostic devices. In this work, artificial intelligence (AI) algorithms such as random forest (RF) and feedforward neural network (FNN) are used to quantitatively investigate the relationships between the concentration of Ru ( bpy ) 3 2 + luminophore and its experimentally measured ECL and electrochemical data. A smartphone-based ECL sensor with Ru ( bpy ) 3 2 + /TPrA was developed using disposable screen-printed carbon electrodes. ECL images and amperograms were simultaneously obtained following 1.2-V voltage application. These multimodal data were analyzed by RF and FNN algorithms, which allowed the prediction of Ru ( bpy ) 3 2 + concentration using multiple key features. High correlation (0.99 and 0.96 for RF and FNN, respectively) between actual and predicted values was achieved in the detection range between 0.02 µM and 2.5 µM. The AI approaches using RF and FNN were capable of directly inferring the concentration of Ru ( bpy ) 3 2 + using easily observable key features. The results demonstrate that data-driven AI algorithms are effective in analyzing the multimodal ECL sensor data. Therefore, these AI algorithms can be an essential part of the modeling arsenal with successful application in ECL sensor data modeling.

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Microtube Electrodes for Imaging the Electrochemiluminescence Layer and Deciphering the Reaction Mechanism

et al. 2020

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Electrochemiluminescence (ECL) is a powerful transduction technique in biosensing and diagnostics, while mechanistic studies are still scarce. Herein we report the combined use of microtube electrode (MTE) and microscopy to measure the thickness of ECL layer (TEL) to decipher reaction mechanisms. For the classical system involving tris(2,2'-bipyridyl)ruthenium and tri-n-propylamine, the ECL pattern generated at the MTE tends to change from ring to spot upon increasing the luminophore concentration, with the TEL varying from ca. 3.1 mm to > 4.5 mm. This variation is rationalized to arise from the contribution of the so-called catalytic route. While using 2-(dibutylamino)ethanol as the coreactant, the ECL pattern remains ring-shaped and independent on the luminophore concentration. The TEL in this case is ca. 2.1 mm, implying that ECL generation is always surfaceconfined. MTEs can thus act as optical rulers for measuring the TEL and providing insightful mechanistic information.

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Spatiotemporal imaging of electrocatalytic activity on single 2D gold nanoplates via electrogenerated chemiluminescence microscopy

Abstract: Spatiotemporal resolved electrocatalytic activity on single 2D gold nanoplates was imaged via electrogenerated chemiluminescence microscopy.

Cited by 67 publications

References 33 publications

Electrochemiluminescence Mechanisms Investigated with Smartphone‐Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

Electrochemiluminescence Mechanisms Investigated with Smartphone‐Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence

Microtube Electrodes for Imaging the Electrochemiluminescence Layer and Deciphering the Reaction Mechanism

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