Sensors and Machine Learning Applications EScience Press en-US Sensors and Machine Learning Applications 2753-4154 Determination, Manufacturing and application of a nanoparticle lead ion-selective electrode as a sensor in flow injection systems <p>This study involves the construction of ion-selective electrodes for the determination of lead (II) ions and their utilization as sensors in a flow-injection analysis (FIA) system. The electrode was constructed using a simple environmentally friendly method from a green tea extract, and a Lead acetate solution of the cited ions as a cylindrical disc. A vertical, side-to-side cylinder, the whole is created in its centre and another lateral hole is created for the electrical attachment of the electrode, so the prepared electrode is suitable for use with the FIA system. The electrode was studied surface properties and characteristics of this electrode were analysed using X-ray diffraction and Fourier-transform infrared spectroscopy (FTR). via selection of the optimum conditions (i.e. linear calibration range, lowest Nernstian response, lowest detection limit, degree of dilution, and precision and accuracy of their analytical uses). Electrode which gave the best Nernstian response1.00×10<sup>-1</sup> to 1.00×10<sup>-10 </sup>M, a correlation coefficient of 0.9980, with lower Nernstian response of 1×10<sup>-10</sup> M and detection limit of 1×10<sup>-11</sup> M. The sampling rate was 120 samples per hour the calculated time of the contact of the sample with the electrode surface is 6 seconds and the degree of dilution is 2.37625.</p> Shatha Al-Samarrai Copyright (c) 2024 Sensors and Machine Learning Applications 2024-01-10 2024-01-10 3 1 10.55627/smla.003.01.00034 Development and application of a nano-coated selective electrode for detection of iron in wastewater <p>This study investigates the possibility of determining iron in wastewater by green chemistry method, including developing an iron selective electrode coated with nano CG-FeO- NPs extracted from mint leaves. The developed electrode was characterised using AFM, SEM, XRD and IR technologies. The performance of the new electrode was optimised for the effects of the pH, temperature and response time. The results showed that the electrode works efficiently in a pH range of 5-8, a temperature range of 20-30 <sup>o</sup>C, and a response time of 6-88 seconds. The calibration curve was range line response from&nbsp; 10<sup>-1</sup> to 10<sup>-11</sup> with a slope of -28.727 mV/decade, a correlation coefficient of 0.9997, a detection limit of 2.4×10<sup>-10</sup> M, a lifetime of 48 days and a recovery percentage of 98.5-99,80 for concentrations of 10<sup>-2</sup>,10<sup>-3</sup> and 10<sup>-4</sup>. A selectivity test was also carried out to ensure no interferences with other elements such as zinc, potassium, sulfate, lead, calcium and manganese. Measurements proved that the electrode has high selectivity towards iron ions only and not other elements. Applications were carried out using the standard addition method on an industrial water model and gave a correlation coefficient of 0.9999.</p> Aziz Salih Aziz Ajumaily Shatha Y. Al-Samarray Copyright (c) 2024 Sensors and Machine Learning Applications 2024-03-30 2024-03-30 3 1 Green nano-coated carbon electrodes for detecting furosemide drug <p>In this study, new coated carbon electrodes were created and utilized to estimate the furosemide (FUR) drug. Ion-pair preparation for the electrode construction involved a reaction of furosemide drug with silver nanoparticles (Ag-NPs) made from pomegranate peel extract, plasticizers that use dibutyl phthalate (DBP) without the use of any organic precipitant. Several techniques (AFM, XRD, FTIR, SEM) were used to characterize the characteristics. This electrode shows excellent sensitivity to furosemide (FUR) with a linear range of 10-6 -10-1 M and a correlation coefficient of 0.9798. The electrode has a lifetime of 45 days, ideal temperatures of 20-45 ºC, an optimum pH range of 3-6, a slope of 61.286 mv/decade, and a detection limit of 3.62×10<sup>-8</sup> M. The AFM was measured, the total height was 2.53 nm, and the shape was spherical or semi-spherical. The average crystal size measured by XRD was 43.52, 47, and 55.03 nm with an average size of 14.25067 nm; the particles were spherical or semi-spherical in shape, as seen using the SEM. The identification of functional aggregates was conducted by measuring them using FTIR. In conclusion, this method could be an efficient tool for determining the drug in pharmaceutical formulations.</p> Dhafer Jassim , Khaleel Ali Ibraheem ,Al Samarrai Shatha Y. Mohammed Copyright (c) 2024 Sensors and Machine Learning Applications 2024-03-30 2024-03-30 3 1