Gold Nanoparticles-based Colorimetric Sensor for Cysteine Detection

Jongjinakool, Suriyapha; Palasak, Khwankhao; Bousod, Natvara; Teepoo, Siriwan

doi:10.1016/j.egypro.2014.07.126

Cited by 53 publications

(29 citation statements)

References 23 publications

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“…When the standard cysteine solution were added to the gold nanoparticle (AuNP) dispersion, the color changed dramatically from red to purple and then blue because of the aggregation process. As studied before, the aggregation of gold nanoparticles shows the consecutive kinetics . The consecutive kinetic of gold nanoparticle (AuNP) aggregation is shown in Figure .…”

Section: Numerical Results For Experimental Datamentioning

confidence: 67%

“…Au nanoparticles have received much attention during the past decades as they play important roles in various areas of material science. The chemical characteristic and the aggregation models of Au nanoparticles in presence of cysteine were studied in . We use a similar data set to show the effect of equality soft constraints on the AFS.…”

Section: Numerical Results For Experimental Datamentioning

confidence: 99%

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Investigating the effect of flexible constraints on the accuracy of self‐modeling curve resolution methods in the presence of perturbations

Mojdehi

Sawall

Neymeyr

et al. 2016

Journal of Chemometrics

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Self-modeling curve resolution methods have continuously been improved during recent years. Many efforts have been made on curve resolution methods to reduce the rotational ambiguity by means of different types of constraints. Choosing proper constraints and cost functions is critically important for the reduction of the rotational ambiguity because the constraints have a direct influence on the accuracy of the area of feasible solution (AFS). In this work, we introduce a new improved cost function, which serves to apply nonnegativity, unimodality, equality, and closure constraints. We also investigate the reduction of the AFS under hard and soft constraints. Another point of this work is to evaluate the accuracy and precision of the reduced AFS in the presence of noise and perturbations, under hard and soft implementation of nonnegativity, unimodality, equality, and closure constraints. A comparison is given between the reduced AFS with soft constraints (small deviations from constraints are accepted) and the reduced AFS under hard constraints (restrictedly forced constraints). A graphical visualization of this comparison is presented for various model problems. The resultsshow that an AFS computation with soft constraints provides more reliable results, especially in the presence of noise. The test problems substantiate significant advantages of soft constraints over hard constraints because the obtained profiles are closer to the potentially true noisy profiles, which contain small deviations from ideal responses. Using tunable parameters ", , !, ı is one of the advantages of soft constrained cost function that allows the small deviations from ideal responses. Ultimately, soft constraints can help to reduce the lack-of-fit, and they are a proper instrument to handle the effect of noise on the AFS.

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Section: Numerical Results For Experimental Datamentioning

confidence: 67%

Section: Numerical Results For Experimental Datamentioning

confidence: 99%

Investigating the effect of flexible constraints on the accuracy of self‐modeling curve resolution methods in the presence of perturbations

Mojdehi

Sawall

Neymeyr

et al. 2016

Journal of Chemometrics

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“…Typical sensor characteristics associated with the proposed sensing methods are compared with the other reported methods and the comparison is provided in Table 1 163940414243444546474849505152535455. This comparison suggests the proposed material exhibits a comparable and in some cases even better detection limit and sensitivity values than the other reported methods and materials.…”

Section: Resultsmentioning

confidence: 90%

Multimodal Sensing Strategy Using pH Dependent Fluorescence Switchable System

Muthurasu

Ganesh

2016

Sci Rep

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Biomolecules assisted preparation of fluorescent gold nanoparticles (FL–Au NPs) has been reported in this work using glucose oxidase enzyme as both reducing and stabilizing agent and demonstrated their application through multimodal sensing strategy for selective detection of cysteine (Cys). Three different methods namely fluorescence turn OFF–ON strategy, naked eye detection and electrochemical methods are used for Cys detection by employing FL–Au NPs as a common probe. In case of fluorescence turn–OFF method a strong interaction between Au NPs and thiol results in quenching of fluorescence due to replacement of glucose oxidase by Cys at neutral pH. Second mode is based on fluorescence switch–ON strategy where initial fluorescence is significantly quenched by either excess acid or base and further addition of Cys results in appearance of rosy-red and green fluorescence respectively. Visual colour change and fluorescence emission arises due to etching of Au atoms on the surface by thiol leading to formation of Au nanoclusters. Finally, electrochemical sensing of Cys is also carried out using cyclic voltammetry in 0.1 M PBS solution. These findings provide a suitable platform for Cys detection over a wide range of pH and concentration levels and hence the sensitivity can also be tuned accordingly.

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“…This is because upon the addition of molecules of analyte, the AuNPs are induced to aggregate/dissociate. The process will leads to the changes in color from red to purple-blue (depending on their particle size) due to the formation of a new absorption band at longer wavelengths [5]. Moreover, AuNPs also use as the active substrate in SERS sensor for the detection of biomolecules due to the high extinction coefficients and strong local SPR absorption strength possessed by AuNPs.…”

Section: Introductionmentioning

confidence: 99%

Gold nanoparticle based optical and electrochemical sensing of dopamine

et al. 2015

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This review (with 110 refs.) gives an overview on the progress that has been made in the past few years on the use of gold nanoparticles (AuNPs) for use in sensors and analytical tools for the determination of dopamine (DA). Both AuNPs and their composites with other organic and inorganic materials including noble metals are treated. Following an overview on the clinical significance of DA, we discuss the various analytical methods that are (a) electrochemiluminescence (ECL); (b) surface enhanced Raman scattering (SERS); (c) colorimetric probing and visual detection; and (d) the large class of electrochemical sensors. Subsections cover sensors based on plain AuNPs, bimetallic NPs, AuNP-metal@metal oxide nanocomposites, AuNP nanocomposites with organic polymers, AuNP nanocomposites with carbon nanotubes or with graphene, and finally sensors based on ternary materials containing AuNPs. The review ends with a conclusion on current challenges of sensors for DA and an outlook on future trends.

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Gold Nanoparticles-based Colorimetric Sensor for Cysteine Detection

Cited by 53 publications

References 23 publications

Investigating the effect of flexible constraints on the accuracy of self‐modeling curve resolution methods in the presence of perturbations

Investigating the effect of flexible constraints on the accuracy of self‐modeling curve resolution methods in the presence of perturbations

Multimodal Sensing Strategy Using pH Dependent Fluorescence Switchable System

Gold nanoparticle based optical and electrochemical sensing of dopamine

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