• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.237-242
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• 2013

This experiment was conducted for the purpose of developing such a sensor that can quickly sense dopamine concentration by using chitosan-gold nanoshell. Chitosan nano particles were reacted with gold nano particles so as to synthesize chitosan-gold nanoshell, and the size of the synthesized product was about 150 nm. When dopamine was reacted with chitosan-gold nanoshell, the size of it was not definitely changed, but dopamine was well reacted with chitosan-gold nanoshell, and it generated SERS (surface-enhanced Raman scattering), which led to a clear difference in the intensity of Raman scattering within the range of dopamine concentration (1 mM-10 mM). When Raman scattering was intensity marked on chitosan-gold nanoshell by employing a calibration curve according to dopamine concentration, a straight line whose margin of error was narrow was earned.

• Journal of the Korean Electrochemical Society
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• v.4 no.3
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• pp.109-112
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• 2001

An activated carbon paste electrode was modified with the N-Hydroxysuccinimide(NHS) layer and applied to determine the dopamine in the presence of an excess ascorbic acid using square-wave voltammetry. The electrochemical properties of the modified electrode were examined in the solution containing dopamine/ascorbic acid using cyclic voltammetry(CV): the separation between the oxidation peaks of dopamine and ascorbic acid was largely dependent on the pH of the sample solution and became maximum at pH 4.0. Hence, the square-wave voltammetric determination of dopamine was carried out in a pH 4.0, 100mM phosphate buffer saline(PBS) containing 140mM NaCl. The detection limit and response slop were improved from $1.0{\mu}M\;to\;5.0\times10^{-2}{\mu}M\;and\;from\;0.93{\mu}A/{\mu}M\;to\;6.1{\mu}A/{\mu}M$, respectively, upon modification of the electrode surface by NHS.

• Analytical Science and Technology
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• v.28 no.2
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• pp.98-105
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• 2015

The development of an enzymatic biosensor for dopamine determination based on multiwall carbon nanotubes (MWCNTs) and peroxidase obtained from the crude extract of burley tobacco (Nicotiana tabacum L.) was proposed. Peroxidase catalyzes the oxidation of dopamine to dopamine quinone. The influence on the response of analytical parameters of biosensors such as enzyme concentration, dopamine concentration, pH, and phosphate buffer solution concentration were investigated. The analytical parameters obtained, including sensitivity, linearity, and stability, were investigated. The proposed method for dopamine determination presented good selectivity even in the presence of uric acid and ascorbic acid. The sensor presented a higher response for dopamine in 0.010 M phosphate buffer at pH 6.50, with an applied potential of -0.15 V. The detection limit of the electrode was 2.7×10⁻⁶ M (S/N = 3) and the relative standard deviation of the measurements, which were repeated 10 times using 5.0×10⁻² M dopamine, was 1.3%.

• Analytical Science and Technology
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• v.8 no.3
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• pp.365-370
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• 1995

A tissue biosensor for the measurement of dopamine has been constructed by immobilizing the slice of Sprague-Dawley rat liver on $NH_3$-sensing electrode. To overcome the defect of tissue sensors, the maximal velocity of response curve was measured and applied to the Lineweaver-Burk equation instead of the Nernst equation. And then compared the results with those obtained from Nernst equation. When we obtained calibration curves from Nernst equation, there were variances on the slope and the linear range. But from Lineweaver-Burk equation, the scale of variance was small. Response time was reduced from 7~12 minutes to 2~3 minutes.

• Journal of Electrochemical Science and Technology
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• v.11 no.1
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• pp.68-83
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• 2020

A fast and simple method for synthesis of Cu_xO-ZnO/PPy/RGO nanocomposite by electrochemical manner have been reported in this paper. For testing the utility of this nanocomposite we modified a GCE with the nanocomposite to yield a sensor for simultaneous determination of four analytes namely ascorbic acid (AA), dopamine (DA), uric acid (UA), and folic acid (FA). Cyclic voltammetry (CV) and Differential pulse voltammetry (DPV) selected for the study. The modified electrode cause to enhance electron transfer rate so overcome to overlapping their peaks and consequently having the ability to the simultaneous determination of AA, DA, UA, and FA. To synthesis confirmation of the nanocomposite, Field emission scanning electron microscopy (FE-SEM), Raman spectroscopy, and electrochemical impedance spectroscopy (EIS) were applied. The linearity ranges were 0.07-485 μM, 0.05-430 μM, 0.02-250 μM and 0.022-180 μM for AA, DA, UA, and FA respectively and the detection limits were 22 nM, 10 nM, 5 nM and 6 nM for AA, DA, UA, and FA respectively Also, the obtained electrode can be used for the determination of the AA, DA, UA, and FA in human blood, and human urine real samples.

• Analytical Science and Technology
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• v.29 no.1
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• pp.35-42
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• 2016

A new nano-composite carbon ink for the development of disposable dopamine (DA) biosensors based on screen-printed carbon electrodes (SPCEs) is introduced. The method developed uses SPCEs coupled with a tyrosinase modified nano-composite carbon ink. The ink was prepared by an “in-house” procedure with reduced graphene oxide (rGO), Pt nanoparticles (PtNP), and carbon materials such as carbon black and graphite. The rGO-PtNP carbon composite ink was used to print the working electrodes of the SPCEs and the reference counter electrodes were printed by using a commercial Ag/AgCl ink. After the construction of nano-composite SPCEs, tyrosinase was immobilized onto the working electrodes by using a biocompatible matrix, chitosan. The composite of nano-materials was characterized by X-ray photoelectron spectroscopy (XPS) and the performance characteristics of the sensors were evaluated by using voltammetric and amperometric techniques. The cyclic voltammetry results indicated that the sensors prepared with the rGO-PtNP-carbon composite ink revealed a significant improvement in electro-catalytic activity to DA compared with the results obtained from bare or only PtNP embedded carbon inks. Optimum experimental parameters such as pH and operating potential were evaluated and calibration curves for dopamine were constructed with the results obtained from a series of amperometric detections at −0.1 V vs. Ag/AgCl. The limit of detection was found to be 14 nM in a linear range of 10 nM to 100 µM of DA, and the sensor’s sensitivity was calculated to be 0.4 µAµM⁻¹cm⁻².

• Journal of Electrochemical Science and Technology
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• v.8 no.4
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• pp.274-281
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• 2017

This paper describes the simple fabrication of an electrode modified with electrochemically reduced graphene oxide (ERGO) for the simultaneous electrocatalytic detection of dopamine (DA), ascorbic acid (AA), and uric acid (UA). ERGO was formed on a glassy carbon (GC) electrode by the reduction of graphene oxide (GO) using linear sweep voltammetry. The ERGO/GC electrode was formed by subjecting a GO solution ($1mg\;mL^{-1}$ in 0.25 M NaCl) to a linear scan from 0 V to -1.4 V at a scan rate of $20mVs^{-1}$. The ERGO/GC electrode was characterized by Raman spectroscopy, Fourier transform infrared spectroscopy, contact angle measurements, electrochemical impedance spectroscopy, and cyclic voltammetry. The electrochemical performance of the ERGO/GC electrode with respect to the detection of DA, AA, and UA in 0.1 M PBS (pH 7.4) was investigated by differential pulse voltammetry (DPV) and amperometry. The ERGO/GC electrode exhibited three well-separated voltammetric peaks and increased oxidation currents during the DPV measurements, thus allowing for the simultaneous and individual detection of DA, AA, and UA. The detection limits for DA, AA, and UA were found to be 0.46, 77, and $0.31{\mu}M$ respectively, using the amperometric i-t curve technique, with the S/N ratio being 3.

• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.379-385
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• 2017

In this study, an amperometric non-enzymatic glucose sensor was developed on the surface of a glassy carbon electrode by simply drop-casting the synthesized homogeneous suspension of hexagonal boron nitride (h-BN) nanosheets with a copper metal-organic framework (Cu-MOF) composite. Comprehensive analytical methods, including field-emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), cyclic voltammetry, electrochemical impedance spectroscopy, and amperometry, were used to investigate the surface and electrochemical characteristics of the h-BN-Cu-MOF composite. The FE-SEM, FT-IR, and XRD results showed that the h-BN-Cu-MOF composite was formed successfully and exhibited a good porous structure. The electrochemical results showed a sensor sensitivity of $18.1{\mu}A{\mu}M^{-1}cm^{-2}$ with a dynamic linearity range of $10-900{\mu}M$ glucose and a detection limit of $5.5{\mu}M$ glucose with a rapid turnaround time (less than 2 min). Additionally, the developed sensor exhibited satisfactory anti-interference ability against dopamine, ascorbic acid, uric acid, urea, and nitrate, and thus, can be applied to the design and development of non-enzymatic glucose sensors.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.269-278
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• 2019

We fabricated glucose oxidase (GOx)-modified biosensor for detection of glucose by physical immobilization of GOx after electrochemical polymerization of the conductive mixture monomers of the 3-thiophenecarboxylic acid (TCA) and thiophene (Th) onto ITO electrode in this study. We confirmed the successfully fabrication of GOx-modified biosensor via FT-IR spectroscopy, SEM, contact angle, and cyclic voltammetry. The fabricated biosensor has the detection limit of $0.1{\mu}M$, the linearity of 0.001-27 mM, and sensitivity of $38.75mAM^{-1}cm^{-2}$, respectively. The fabricated biosensor exhibits high interference effects to dopamine, ascorbic acid, and L-cysteine, respectively. From these results, the fabricated GOx-modified biosensor with long linearity and high sensitivity could be used as glucose sensor in human blood sample.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2627-2642
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• 2023

Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.