Silver nanoclusters-catalyzed luminol chemiluminescence for hydrogen peroxide and uric acid detection

Sheng, Yingying; Yang, Hongli; Wang, Ying; Han, Lu; Zhao, Yanjun; Fan, Aiping

doi:10.1016/j.talanta.2017.01.066

Cited by 83 publications

(25 citation statements)

References 42 publications

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“…Before we are able to understand H 2 O 2 ' s role in the body, there must be reliable, fast, and versatile methods of detection with appropriate range and detection limits to function within biological systems and to detect biologically-relevant concentrations. In the past five years, researchers have continued to improve existing H 2 O 2 sensors [26,27,33,34,36,52,57,65,66,71,76] and developed novel methods of H 2 O 2 detection [26,27,32,66,67]. Sensor developments have occurred in the improvement of H 2 O 2 detection limits, with researchers able to detect much smaller concentrations than in the past; longevity, with researchers developing sensors that function over multiple weeks/months; and cost, with prices dropping in sensor development, this making sensors easier to manufacture at desired price points [65,66,71].…”

Section: Discussionmentioning

confidence: 99%

“…In the following year, Sheng et al used silver nanocluster-capped bovine serum albumin (BSA) as a catalyst for the luminol-H 2 O 2 reaction [34]. The silver nanocluster capped BSA is a small alteration that allows for variable emission wavelengths, creating a tunable sensor [34].…”

Section: Developments From 2015 To 2019mentioning

confidence: 99%

“…H2O2 sensors that could be used by researchers, including those outlined below [10,25,[28][29][30][31][32][33][34][35][36][37][38]. light that can then be read to determine H2O2 concentration [16].…”

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confidence: 99%

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Hydrogen Peroxide Sensors for Biomedical Applications

et al. 2019

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Hydrogen peroxide (H2O2) is an important molecule within the human body, but many of its roles in physiology and pathophysiology are not well understood. To better understand the importance of H2O2 in biological systems, it is essential that researchers are able to quantify this reactive species in various settings, including in vitro, ex vivo and in vivo systems. This review covers a broad range of H2O2 sensors that have been used in biological systems, highlighting advancements that have taken place since 2015.

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Section: Discussionmentioning

confidence: 99%

Section: Developments From 2015 To 2019mentioning

confidence: 99%

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Hydrogen Peroxide Sensors for Biomedical Applications

et al. 2019

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“…Thus, H 2 O 2 determination is gaining more attention in the biomedical science, food inspection and industrial application as a countermeasure in preventing further damage on life and property. Various analytical methods, such as colorimetric , fluorescence , titrimetric , chemiluminescence , chromatography and electrochemical , have been established for detection and quantification of H 2 O 2 . Among these techniques, electrochemical detection has many advantages such as simple instrumentation, reliability, excellent sensitivity and selectivity and rapid response time.…”

Section: Introductionmentioning

confidence: 99%

Magnetite Nanorods Stabilized by Polyaniline/Reduced Graphene Oxide as a Sensing Platform for Selective and Sensitive Non‐enzymatic Hydrogen Peroxide Detection

et al. 2019

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In this study, magnetite nanorods stabilized on polyaniline/reduced graphene oxide (Fe3O4@PANI/rGO) was synthesized via a wet‐reflux strategy. The possible formation of Fe3O4@PANI/rGO was morphologically and structurally verified by field emission scanning electron microscopy (FE‐SEM), Fourier transform infrared (FT‐IR) spectroscopy, Raman spectroscopy, X‐ray diffraction (XRD) and X‐ray photoelectron spectroscopy (XPS). Furthermore, the thermal stability of Fe3O4@PANI/rGO was measured by a thermogravimetric analyzer (TGA); the composite had good thermal stability owing to the ceramic nature of Fe3O4. The Fe3O4@PANI/rGO has been applied as a potential sensing platform for electrochemical detection of hydrogen peroxide (H2O2). By the combined efforts of extended active surface area, active carbon support, more catalytic active sites and high electrical conductivity, the Fe3O4@PANI/rGO exhibited an improved performance toward the non‐enzymatic detection of H2O2 in 0.5 M KOH with a fast response time (5 s), high sensitivity (223.7 μA mM−1 cm−2), low limit of detection (4.45 μM) and wide linear range (100 μM–1.5 mM). Furthermore, the fabricated sensor exhibited excellent recovery rates (94.2–104.0 %) during real sample analysis.

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“…Various analytical methods are developed for the determination of UA. These include electrochemical and chemiluminescence [7,8], high-performance liquid chromatography [9,10], and spectroscopic quantitative analysis [11,12]. As spectroscopic quantitative analysis only requires a small sample with easy preparation, the method for blood analysis attracts more attention [13,14].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Regression with High-Dimensional Space Mapping for Blood Component Spectral Quantitative Analysis

Cao

Zhang

Zhou

2018

Journal of Spectroscopy

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Accurate and fast determination of blood component concentration is very essential for the efficient diagnosis of patients. This paper proposes a nonlinear regression method with high-dimensional space mapping for blood component spectral quantitative analysis. Kernels are introduced to map the input data into high-dimensional space for nonlinear regression. As the most famous kernel, Gaussian kernel is usually adopted by researchers. More kernels need to be studied for each kernel describes its own high-dimensional feature space mapping which affects regression performance. In this paper, eight kernels are used to discuss the influence of different space mapping to the blood component spectral quantitative analysis. Each kernel and corresponding parameters are assessed to build the optimal regression model. The proposed method is conducted on a real blood spectral data obtained from the uric acid determination. Results verify that the prediction errors of proposed models are more precise than the ones obtained by linear models. Support vector regression (SVR) provides better performance than partial least square (PLS) when combined with kernels. The local kernels are recommended according to the blood spectral data features. SVR with inverse multiquadric kernel has the best predictive performance that can be used for blood component spectral quantitative analysis.

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Silver nanoclusters-catalyzed luminol chemiluminescence for hydrogen peroxide and uric acid detection

Cited by 83 publications

References 42 publications

Hydrogen Peroxide Sensors for Biomedical Applications

Hydrogen Peroxide Sensors for Biomedical Applications

Magnetite Nanorods Stabilized by Polyaniline/Reduced Graphene Oxide as a Sensing Platform for Selective and Sensitive Non‐enzymatic Hydrogen Peroxide Detection

Nonlinear Regression with High-Dimensional Space Mapping for Blood Component Spectral Quantitative Analysis

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