• Bulletin of the Korean Chemical Society
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• 제34권1호
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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.

• 전기화학회지
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• 제4권3호
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• pp.109-112
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• 2001

활성화된 탄소반죽전극 표면을 N피드록시숙신이미드(NHS)층으로 수식한 후, 이 전극을 이용하여 square-wave voltammetry방법으로 과량의 아스코빅산 존재 하에서 도파민을 측정하였다. 수식된 전극의 특성은 도파민과 아스코빅산 혼합용액에서 순한전압전류법을 이용하여 조사하였다. 도파민과 아스코빅산의 산화 피크의 분리는 시료용액의 pH에 큰 영향을 받았으며, pH 4.0에서 최대의 피크분리(172mv)를 보였다. 따라서 도파민을 정량하기 위한 square-wave voltammeoy는 140 mM NaCl을 포함하는 100 mM phosphate buffered saline (PBS)의 pH 4.0 조건에서 수행하였다. NHS로 수식된 전극은 0.2mM 아스코빅 산의 존재 하에서 도파민의 농도 $5.0\times10^{-2}$까지 검출한계와 감응기울기 $6.1{\mu}A/{\mu}M$의 감도를 나타내었다. 반면 수식되지 않은 전극은 $1.0{\mu}M$의 검출한계와 $0.93{\mu}A/{\mu}M$ 기울기를 나타내어 표면에 수식된 N-히드록시숙신이미드가 도파민의 감응을 촉진함을 보여주었다.

• 분석과학
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• 제28권2호
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• pp.98-105
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• 2015

버얼리종 담배에서 추출물에서 얻은 peroxidase와 다중벽 탄소 나노튜브를 이용한 dopamine 정량 바이오센서를 만들었다. Peroxidase는 dopamine을 dopamine quinone으로 산화시키는 반응의 촉매 역할을 한다. 이 논문은 효소의 농도, pH와 같은 바이오센서의 감응에 영향을 주는 parameter를 조사하였다. 또한, 전극의 감도, 직선성의 범위, 전극의 안정성을 조사하였다. 본 실험에 사용한 dopamine의 정량 센서는 pH 6.50, 0.010 M 인산 완충용액, -0.15 V의 가해준 전압에서 가장 좋은 감응을 나타내었다. 전극의 검출한계(S/N ＝3)는 2.7×10⁻⁶ M이었으며, 5.0×10⁻² M dopamine을 이용하여 10회 반복 측정한 상대표준편차는 1.3%이었다.

• 분석과학
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• 제8권3호
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• pp.365-370
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• 1995

Dopamine 정량을 위한 조직 센서로 Sprague-Dawley계 숫쥐의 간조직을 암모니아 기체 감응 전극에 고정화하였다. 조직 센서가 가지고 있는 단점을 극복하기 위해 기존의 Nernst equation 대신, 감응 곡선의 최대 속도를 측정하여 Lineweauer-Burk equation에 적용함으로써 그 가능성을 살펴보았다. 기존의 방법으로는 조직마다 slope, linear range에 변화가 심하나 본 방법에 따른 경우 그 변화 정도가 적으며, 감응 시간은 7분~12분 정도로부터 2~3분으로 단축시킬 수 있었다.

• Journal of Electrochemical Science and Technology
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• 제11권1호
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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.

• 분석과학
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• 제29권1호
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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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• 제8권4호
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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.

• 센서학회지
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• 제26권6호
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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.

• 한국응용과학기술학회지
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• 제36권1호
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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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• 제17권10호
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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.