BITS Faculty Publications
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Item Structural and Optical Characterizations of Electrochemically Grown Connected and Free-Standing TiO2 Nanotube Array(Springer, 2014-05) Hazra, Arnab; Manjuladevi, V.; Gupta, Raj KumarA TiO2 nanotube array was grown electrochemically by using single and mixed electrolyte/s with 20 V constant potential at room temperature. Anodization was carried out for 120 min using five different electrolytes, e.g., H3PO4, NH4F, HF, NH4F with H3PO4 and HF with H3PO4. Structural characterizations of the grown titania nanotubes were conducted by using x-ray diffraction and field emission scanning electron microscopy. Optical properties of the grown nanotubes were investigated through photoluminescence (PL) spectroscopy. In the case of the 4 M H3PO4 electrolyte, no perceptible growth of nanotubes was observed. The individual electrolytes of 0.3 M NH4F and 1 M HF resulted into the formation of the wall-connected nanotubes. In contrast, the mixed electrolytes comprising the strong (NH4F, HF) and weak (H3PO4) electrolytes have been found to be efficient for the growth of wall-separated titania nanotubes. The results of the PL spectroscopy have demonstrated that the free-standing nanotubes offer low PL intensity compared to its connected counterpart owing to the lower carrier recombination rate of free-standing nanotubes.Item Water Quality Index Calculation: Switching from MATLAB Fuzzy Toolbox to Python for Real-Time Implementation(IEEE, 2020) Gupta, Raj Kumar; Gupta, Karunesh KumarWater quality assessment has always been of primary importance before consumption as most of the available water is polluted, which could transmit several waterborne diseases. Water Quality Index (WQI) is a unique single value to determine overall water quality. WQI summarizes the water quality parameters in a single value. MATLAB fuzzy is the standard toolbox to implement the water quality index. The user has to determine only the inputs as different water quality parameters and the membership functions based on the complexity of the application. This approach is offline, as it cannot be implemented in real-time. An alternate method may be the WQI measurement in the Python framework for real-time implementation. In this paper, we are trying to find out that it is possible to switch from MATLAB fuzzy toolbox to the Python framework for real-time implementation. The WQI measurement is performed in both the fuzzy toolbox from MATLAB® and Python 3.4. Based on the results, a comparative study has been done, and the switching possibility is found out.Item Development of Cyber-Physical Systems for Water Quality Monitoring in Smart Water Grid(Springer, 2022-05) Gupta, Raj Kumar; Gupta, Karunesh KumarThere are many challenges while developing a smart city, such as air/water quality monitoring, water resource management, power grid implementation, and transport management. Water quality monitoring is one of them in which many researchers and scientists showed interest. The current water distribution systems always face leakage, failure, and maintenance delays due to the unavailability of real-time monitoring in distribution systems, which results in a high amount of water wastage. This can be solved by implementing a smart water grid. This paper proposes a solution for water quality monitoring for distribution systems in a real-time environment based on low-cost commercial off-the-shelf modules. Various water quality parameters were monitored from the developed setup. The proposed architecture can log, analyze data, make decisions, and remotely represent the data. The data obtained from various sensing nodes were uploaded to the cloud, a service provided by Amazon Web Services (AWSs). Experimental results show that the proposed low-cost sensing network can be an ideal early warning system in smart cities.Item Detection of cadmium ion in aqueous medium by simultaneous measurement of piezoelectric and electrochemical responses(Elsevier, 2018-09) Gupta, Karunesh Kumar; Gupta, Raj Kumar; Manjuladevi, V.Cadmium is one of the important heavy metals which poses health hazards due to its consumption through potable water. Cadmium is known to form complexes with amine group and also it has good affinity towards carbon nanotubes. The octadecylamine functionalized single-walled carbon nanotubes (ODACNTs) can be employed for sensing cadmium ion in aqueous medium. A thin film of ODACNTs offers not only strong adsorption properties towards cadmium ion but also provides an enormous gain in surface to volume ratio, and good mechanical and chemical stability. Therefore, a sensing layer of ODACNTs was formed on the gold deposited quartz wafer and the sensing towards cadmium ion in the aqueous medium was performed. An experimental setup was designed to record the electrochemical and piezo-responses simultaneously. The piezo and electrochemical responses were found to be linear in the given concentration range. Interestingly, the piezoresponse modulates systematically and repeatedly from a maximum to minimum value due to voltage sweep during cyclic voltammetry indicating the interfacial phenomenon of adsorption and desorption.Item Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: a Python framework approach(DWES, 2019) Gupta, Raj Kumar; Gupta, Karunesh KumarThis paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.Item Assessment of Water Quality Parameters in Real-Time Environment(Springer, 2020-10) Gupta, Raj Kumar; Gupta, Karunesh KumarAssessment of drinking water quality has been an important issue nowadays as the water available is severely polluted and can be the cause of diseases like cholera, diarrhea, dysentery, etc. The traditional methods for water quality monitoring require a high-labor-cost and tine consumption as these methods include a sample collection followed by lab-based chemical testing. In addition, the chemicals used in the testing are toxic and of high-cost. So, there is a need for real-time monitoring and chemical-free testing of water quality parameters. This paper presents a real-time water quality monitoring system based on the Raspberry Pi 3 development board and a Python framework. The water quality parameters utilized for water quality monitoring are temperature, pH, oxidation reduction potential, electrical conductivity, and dissolved oxygen and E. coli. The water quality sensors were interfaced with the designed embedded platform. Finally, the acquired parameters were compared with the benchmark equipment for validation.Item Facile ultrathin film of silver nanoparticles for bacteria sensing(Elsevier, 2020-12) Gupta, Karunesh Kumar; Gupta, Raj Kumar; Manjuladevi, V.Silver nanoparticles (AgNPs) exhibit excellent anti-microbial and bactericidal properties. Due to bacterial abhorrence for AgNPs, it is difficult to develop a label-free, sensitive and low-cost bacteria sensor using them. In the present article, we report that an ultrathin and uniform Langmuir–Schaefer (LS) film of AgNPs can be employed for bacteria sensing effectively as compared to that of non-uniform and randomly distributed AgNPs in spin coated film. The uniformly distributed AgNPs in the LS film offer a relatively larger contact surface for bacteria as compared to that of spin coated film. Due to higher contact surface, adsorption of the bacteria on LS film is strongly preferable as compared to that of spin coated film leading to an enhanced sensing performance of the LS film than that of spin coated film. Soil bacteria was grown by the standard protocol and were utilized as model system for bacteria sensing application. The soil bacteria sensing was done by monitoring the piezoresponse and dissipation parameters using a quartz crystal microbalance, simultaneously. Our study indicates that the LS film of AgNPs not only facilitates the adsorption of the soil bacteria but also kills them.Item A review of partial least squares modeling (PLSM) for water quality analysis(Springer, 2020-10) Gupta, Raj Kumar; Gupta, Karunesh KumarRegression is a powerful tool in statistical modeling suited for qualitative and quantitative analysis and widely used in forecasting and prediction. The partial least squares modeling (PLSM) is one of the regression tools used in statistical analysis. There are many fields in which PLSM has been used; water is one of them, which is an area of interest for many researchers and scientists for more than two decades. Since water has multiple parameters to analyze, there is a problem of dimensionality and collinearity. The problem of multidimensionality, as well as collinearity, can be solved by PLSM. PLS regression can be suitable for analysis as it is the most prominent multivariate regression tool. This paper describes the use of PLS regression modeling for water quality analysis of different kinds of water samples (groundwater, wastewater, river water, and coastal water). Various methods employing PLSM for water quality analysis has been discussed in detail.Item Heavy Metal Ion Sensing using Ultrathin Langmuir-Schaefer Film of Tetraphenylporphyrin Molecule(IEEE, 2020) Gupta, Raj Kumar; Gupta, Karunesh Kumar; Manjuladevi, V.; Kumar, DalipThe exciting properties of porphyrin molecules can be employed for several applications like sensing, catalysis, photovoltaics and energy related fields. The assemblies of the molecules at interfaces can give rise to some unique physicochemical properties which can enhance the device performance. In this article, we report our studies on heavy metal ion sensing in aqueous medium using ultrathin film of tetraphenylporphyrin (TPP) molecules. The TPP molecules were synthesized and used for forming Langmuir monolayer at the air-water interface. The monolayer was transferred onto solid substrates by Langmuir-Schaefer (LS) method at different target surface pressure of deposition (πT). The morphological analysis of the films indicated supramolecular assembly of the molecules in the LS film deposited at πT = 30 mN/m. The LS films of TPP molecules were employed for sensing heavy metal cations viz. Pb 2+ , Hg 2+ , Co 2+ and Cd 2+ from the aqueous medium by measuring piezoresponse from a quartz crystal microbalance. The sensing performance was found to be the best with LS film deposited at πT = 30 mN/m. The sensitivity-towards Pb 2+ ion is found to be the highest. The sensing of the heavy metal cations using randomly oriented TPP molecules in spin coated thin film was found to be much inferior as compared to that of LS films of the molecule. The enhanced sensing performance by the LS film of TPP molecules may be attributed to the supramolecular assembly of the molecules. We report that the interference of the sensing measurement for the recognition of Cd 2+ and Pb 2+ ions is least and thus these species can be detected selectively with less errors. The cation species recognition features obtained from scanning electron microscope images and Raman spectroscopy were found to be remarkably different and therefore these cationic heavy metal species can be selectively detected using the LS film of TPPItem Drift compensation of commercial water quality sensors using machine learning to extend the calibration lifetime(Springer, 2020) Gupta, Karunesh Kumar; Gupta, Raj KumarThere are specific issues in the multi-sensor systems used for water quality monitoring, which prevents these systems for routine measurement of water samples. An important issue is drift; related to sensor readings, which may refute the calibration of sensors leads to the necessity of frequent recalibration of the sensors that required effort as well as shut down the system. An alternative approach for drift correction is based on the mathematical correction method. The paper proposed a regression calibration method and implemented by the machine learning approach. In this paper, we have used a feed-forward artificial neural network based regression model to extend the calibration lifetime of sensors. The evaluation of the model was performed based on the root mean square error and the root mean square error for cross-validation. The proposed model is also compared with the traditional statistical method and proved to be superior to the traditional one. The experimental results demonstrate the best performance with a negligible error rate. Based on the results of the current study, ANN appears to be more adaptive for data analysis in environmental monitoring applications.