SOUTHERN JOURNAL OF SCIENCES

Short note.

Background: Industrial wastewater contains pollutants that are detrimental to human health in varied proportions. Among the pollutants are heavy metals, including Zn2+, Pb2+, and Cu2+ found in a characterized pharmaceutical wastewater. Several techniques have been proposed for the heavy metal sequester. However, they are with attendant challenges. The adsorption techniques using clay-metal oxide modified adsorbent/composite such as silver-clay adsorbent is considered suitable for an effective sequestering process. Aims: To develop and characterize Ag/clay adsorbent for pharmaceutical wastewater treatment. Methods: The Ag nanoparticles were synthesized using Parkia biglobossa aqueous leaves extract in an optimization study. The raw clay was beneficiated and doped with silver nanoparticles via the wet impregnation method. The silver-clay adsorbent was characterized using FTIR, XRD, SEM, and EDS characterization tools. The developed adsorbent was used for the batch adsorption process of the heavy metal ion removal from the wastewater. Results and Discussion: The phytochemical analysis and FTIR results of the P. biglobosa showed that the leaf contains phenol, tannin, and flavonoids which acts as reducing, capping, and stabilizing agent required for synthesizing the silver nanoparticles. The prepared silver nanoparticles modified clay adsorbent Ag/clay, have evenly distributed stacks of pseudo-hexagonal plates, are rich in silica, possess silver nanoparticles in the frameworks, and contain functional groups suitable for binding heavy metals. The adsorptions of Zn2+, Pb2+, and Cu2+ from pharmaceutical wastewater onto the silver-modified clay were studied as a function of adsorbent dosage and contact time. The percentage removal results obtained showed that the adsorbent had up to 99.96%, 99.5%, and 99.44% removal efficiency for Zn2+, Pb2+, and Cu2+, respectively, which are better compared with previous studies. The adsorption process was feasible, spontaneous, and exothermic, with Langmuir and Pseudo-second-order models as best fits for the process. Conclusions: The adsorption of selected heavy metal ions onto the green synthesized silver-modified clay adsorbent (Ag/clay) was feasible, spontaneous, and exothermic in the order Zn2+>Pb2+>Cu2+ with Langmuir and Pseudo-second-order model best fitted for the process. These show that the synthesized silver oxide nanoparticles supported on local clay can be used as a potentially low-cost adsorbent to remove heavy metal ions from industrial wastewater.

Background: MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a stand-alone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been given much attention in the research community. Aim: the purpose of this work is to explore a structured graphical approach of determination of MQ series gas sensor circuit parameters for a stand-alone gas alarm system that yields desired sensor circuit output voltage value for the alarm point; the main objective of the study was to develop mathematical model equations that relate the: (i) sensor resistance (RS) with the gas concentration (x) and the sensor resistance at standard calibration concentration of the sensor base gas in the clean air (Ro) and (ii) sensor circuit output voltage (VRL), load resistance (RL) and sensor resistance (RS). It is expected from the model equations developed that graphical correlations of the sensor circuits parameters will be generated. Using these graphs for a particular case of an MQ-4 gas sensor under the influence of LPG, the parameters that yield desired sensor circuit output voltage of 2V for 1000 ppm of LPG alarm point will be determined. Methods: Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to LPG. Results and Discussion: The results yielded optimal values for R_O,R_S and R_L of 20 kΩ, 30 kΩ and 20 kΩ respectively, for alarm settings of 1000 ppm and a desired sensor circuit output voltage of 2 V. Based on determined parameters, the calibration equation for determination of best concentration value for a given value of emulated LPG concentration was developed. Using the method proposed in this study makes the process of determining the MQ-series gas sensor circuit parameters less cumbersome as their value can easily be obtained from the resulting graphs. Conclusions: a structured graphical approach for determination of MQ-series gas sensor circuit parameters for alarm points in a stand-alone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas, and for a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of R_O, R_S and R_L obtained were 20 kΩ, 30 kΩ, and 20 kΩ respectively. Hence, a structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a stand-alone gas alarm system under the influence of its associated gases.