Graduate University of Advanced Technology

About: Graduate University of Advanced Technology is a education organization based out in Kerman, Iran. It is known for research contribution in the topics: Carbon paste electrode & Electrochemical gas sensor. The organization has 890 authors who have published 2169 publications receiving 31027 citations.

Nonenzymatic coated screen-printed electrode for electrochemical determination of acetylcholine

Abstract: In the present study, a screen-printed electrode based-sensor with electrochemical detection was developed for rapid and sensitive determination of acetylcholine. At first, the screen-printed carbon electrode was modified by using a magnetic core shell and then was used for voltammetric determination of acetylcholine in ampoule, serum and urine samples. The electrochemical behaviour of acetylcholine at the modified electrode was investigated by cyclic voltammetry. The modified electrode displayed a decrease in the overpotential (ca. 130 mV) and an obvious increase in the peak current compared to the non-modified screen-printed electrode. The results indicated that modified screen-printed electrode enhanced electrocatalytic activity towards the oxidation of acetylcholine. Under optimized conditions, the limit of detection from the experiment of acetylcholine determination was 0.02 µM with acetylcholine concentration in range of 0.1–500.0 µM. The reproducibility of the measurements was tested by recording the responses for 50.0 µM acetylcholine with four different developed sensors prepared on the same manner and the same day. A relative standard deviation value of 4.3% was obtained. Finally, a recovery test is done as a part of accuracy evaluation of the system.

Sensitive voltammetric determination of cadmium at a carbon nanotubes/Fe3O4/eggshell composites modified carbon paste electrode

Abstract: In the present work, we describe a new method for differential-pulse anodic stripping voltammetric (DPASV) determination of cadmium (II) using a carbon paste electrode modified with magnetic nanocomposite of Fe3O4/eggshell and carbon nanotubes (MWCNT-MES-CPE). In addition to Fourier transform infrared spectroscopy (FT-IR) and vibrating sample magnetometer (VSM) for the characterization of the prepared magnetic nanocomposite, the morphology and structure of Fe3O4/eggshell were studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD). The effective experimental parameters on the preconcentration of Cd (II) ions and voltammetric stripping step such as supporting electrolyte (type and concentration), accumulation and reduction potential, and of time and amount of modifier were investigated by differential pulse anodic stripping voltammetry. The voltammetric peak current of Cd (II) appeared at a potential about −0.7 V, under optimum conditions. The method was then worked out for the determination of cadmium at low levels. Under optimized conditions, the response to Cd (II) is linear in the range from 3.0 to 250 ng mL−1 with a detection limit of 2.4 ng mL−1 for Cd (II) ion. The sensor was applied to the determination of Cd (II) in water, hair samples, and certified reference materials.

Reliability evaluation of groundwater quality index using data-driven models

Abstract: A trustworthy evaluation of the groundwater quality situations for different usages (i.e., drinking, industry, and agriculture) can definitely improve the management of groundwater resources for quality and quantity control, particularly in the arid and semi-arid districts. In the present investigation, GQI values and their typical categories have been yielded by the World Health Organization (WHO) instruction for the Rafsanjan Plain, the central part of Iran, during a 15-year period beginning in 2002. In this study, four robust Data-Driven Techniques (DDTs) based on the evolutionary algorithms and classification concepts have been applied to present formulations for the prediction of groundwater quality index (GQI) values in the case study of Rafsanjan Plain. In this way, monthly groundwater quality parameters (i.e., electrical conductivity, total hardness, total dissolved solid, pH, chloride, bicarbonate, sulfate, phosphate, calcium, magnesium, potassium, and sodium) were taken from 1349 observations. Performance of DDTs indicated that the Evolutionary Polynomial Regression (EPR) demonstrated the most accurate predictions of GQI than a model tree (MT), gene-expression programming (GEP), and Multivariate Adaptive Regression Spline (MARS). Moreover, to investigate all probable uncertainty in the values of groundwater quality parameters for the Rafsanjan Plain, a reliability-based probabilistic model was designed to assess the values of GQI. Hence, the Monte-Carlo scenario sampling technique has been quantified to evaluate the limit state function from DDTs. Moreover, there is a high probability (almost 100%) for the whole region to pass the “Excellent” quality, but it reduces to almost 50% over the “Good” and leads to almost 0% for the “Poor” quality.