Highly sensitive and selective determination of p-nitrophenol at an interpenetrating networks structure of self-assembled rod-like lanthanum hydroxide-oxidized multi-walled carbon nanotubes nanocomposite.

In this study, a novel electrochemical sensor based on self-assembled rod-like lanthanum hydroxide-oxidized multi-walled carbon nanotubes (La(OH)3-OxMWCNTs) nanocomposite was developed for sensitive determination of p-nitrophenol (p-NP). The La(OH)3-OxMWCNTs nanocomposite with an interpenetrating networks structure was characterized by field emission electron microscope (FE-SEM), Fourier transform infrared (FT-IR) spectroscopy, Raman spectra and X-ray photoelectron spectroscopy (XPS). The cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements were performed to study the electrochemical behaviors of La(OH)3-OxMWCNTs modified glassy carbon electrode (La(OH)3-OxMWCNTs/GCE). The La(OH)3-OxMWCNTs/GCE was used for sensitive determination of p-NP by CV and linear sweep voltammetry (LSV). Under the optimum conditions, the peak currents of LSV versus the concentrations of p-NP in the range 1.0-30.0 µmol L-1 showed a good linear relationship (R2=0.9971), and the limit of detection (LOD) was calculated to be 0.27 µmol L-1 (signal-to-noise ratio of 3, S/N=3). The recoveries of p-NP in real samples of industrial wastewater and Xiangjiang water at La(OH)3-OxMWCNTs/GCE were in the range of 95.62-110.75% with relative standard deviation (RSD) in the range of 1.65-3.85%. The intra-day and inter-day precisions were estimated to be less than 2.76% (n= 5), indicating that La(OH)3-OxMWCNTs/GCE possessed highly stability. In addition, La(OH)3-OxMWCNTs/GCE sensor showed good anti-interference ability for determination of p-NP in aqueous mixtures containing high concentrations of inorganic and organic interferents, and a decrease of oxidation peak currents by less than 3.57% relative to the initial levels indicated it possessed excellent selectivity. Therefore, La(OH)3-OxMWCNTs/GCE could be used as a fast, selective and sensitive electrochemical sensor platform for the selective determination and quantification of aqueous p-NP.

Hybrid carbon nanotubes modified glassy carbon electrode for selective, sensitive and simultaneous detection of dopamine and uric acid.

Based on a hybrid carbon nanotube composite, a novel electrochemical sensor with high sensitivity and selectivity was designed for the simultaneous determination of dopamine (DA) and uric acid (UA). The hybrid carbon nanotube composite was prepared by ultrasonic assembly of carboxylated multi-walled carbon nanotube (MWCNT-COOH) and hydroxylated single-walled carbon nanotube (SWCNT-OH). And the hybrid (MWCNT-COOH/SWCNT-OH) composite was characterized by field emission scanning electron microscopy (FE-SEM) and Fourier transform infrared (FT-IR) spectroscopy. The electrochemical performances of MWCNT-COOH/SWCNT-OH composite modified glassy carbon electrode (MWCNT-COOH/SWCNT-OH/GCE) were analyzed by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV). Under the optimum experimental conditions, the as-prepared sensor showed high sensitivity and selectivity for DA and UA. The calibration curves obtained were linear for the currents versus DA and UA concentrations in the range 2-150 µM, and limits of detection (LODs) were calculated to be 0.37 µM and 0.61 µM (signal-to-noise ratio of 3, S/N = 3), respectively. The recoveries of DA and UA in bovine serum samples at MWCNT-COOH/SWCNT-OH/GCE were in the range 96.18-105.02%, and relative standard deviations (RSDs) were 3.34-7.27%. The proposed electrochemical sensor showed good anti-interference ability, excellent reproducibility and stability, as well as high selectivity, which might provide a promising platform for determination of DA and UA.

A sensitive non-enzymatic electrochemical sensor based on acicular manganese dioxide modified graphene nanosheets composite for hydrogen peroxide detection.

In this work, a novel manganese dioxide-graphene nanosheets (MnO2-GNSs) composite was synthesized by a facile one-step hydrothermal method, in which manganese dioxide (MnO2) was fabricated by hydrothermal reduction of KMnO4 with GNSs. The structure and morphology of MnO2-GNSs composite were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD) analysis and X-ray photoelectron spectroscopy (XPS). A sensitive non-enzymatic electrochemical sensor based on MnO2-GNSs composite for the detection of low concentration hydrogen peroxide (H2O2) was fabricated. The electrochemical properties of MnO2-GNSs composite modified glassy carbon electrode (MnO2-GNSs/GCE) were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and amperometry. The observations confirmed that the fabricated sensor exhibited high electrocatalytic activity for oxidation of H2O2 owing to the catalytic ability of MnO2 particles and the conductivity of GNSs. Under the optimum conditions, the calibration curve was linear for the amperometric response versus H2O2 concentration over the range 0.5-350 µM with a low detection limit of 0.19 µM (S/N = 3) and high sensitivity of 422.10 µA mM-1 cm-2. The determination and quantitative analysis of H2O2 in antiseptic solution on MnO2-GNSs/GCE exhibited percent recovery of 96.50%-101.22% with relative standard deviation (RSD) of 1.48%-4.47%. The developed MnO2-GNSs/GCE might be a promising platform for the practical detection of H2O2 due to its prominent properties including excellent reproducibility, good anti-interference and repeatability.

[Spectral baseline correction by piecewise dividing in Fourier transform infrared gas analysis].

Aimed at the problem that baseline drift or distortion often appears in Fourier transform spectra after spectrometer has continuously worked for a long time, baseline variation caused by IR source temperature drift and fluctuation, tilt of moving mirror, performance parameter change of beam splitter and lateral shift of detector were studied by simulating using MATLAB. Simulation results show that spectral baseline drift is approximately linear. On this basis, a novel method named spectral baseline correction by piecewise dividing (SBCPD) is proposed to correct spectral baseline in the present work By comparing peak height of simulated spectra, it was found that performance of SBCPD is better than that of common methods of polynomial fitting, air-PLS (adaptive iteratively reweighted Penalized Least Squares). And the application in gas well-logging showed that prediction accuracy of SBCPD is also higher. Additionally, this method is reliable and of less calculation, and is suitable for engineering application.