Bi-functional renewable biopolymer wrapped CNFs/Ag doped spinel cobalt oxide as a sensitive platform for highly toxic nitroaromatic compound detection and degradation

Balram, Deepak; Lian, Kuang‐Yow; Sebastian, Neethu; Al‐Mubaddel, Fahad S.; Noman, Muhammad

doi:10.1016/j.chemosphere.2021.132998

Cited by 26 publications

(14 citation statements)

References 41 publications

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“…The designed model works in the following manner i.e., correlates the actual response with the process variables, evaluates the predicted response and indicates the better approach. ANN models are the widely used machine learning tools for prediction and classification of real-world applications e.g., textile processes [ 5 , 6 ], computer vision [ 7 ], materials engineering [ 8 , 9 ] and biomedical engineering [ 10 , 11 , 12 ]. ANN has great potential for prediction from input variables, especially when an unknown mathematical relationship exists between input and output variables [ 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton

et al. 2022

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In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values.

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Section: Introductionmentioning

confidence: 99%

Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton

et al. 2022

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“…The wide scan range of the XPS image of the synthesized AgNPs demonstrated the presence of silver, oxygen, and carbon species, as shown in Figure 2 D. The high-resolution spectrum of Ag 3d illustrated two asymmetrical peaks with well-separated spin-orbit components. The deconvoluted Ag 3d spectrum represented the binding energies of Ag 3d5/2 and Ag 3d3/2 at 368 and 373 eV, respectively, indicating that the synthesized AgNPs were primarily present in a metallic state [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

“…The high-resolution spectrum of Ag 3d illustrated two asymmetrical peaks with well-separated spin-orbit components. The deconvoluted Ag 3d spectrum represented the binding energies of Ag 3d5/2 and Ag 3d3/2 at 368 and 373 eV, respectively, indicating that the synthesized AgNPs were primarily present in a metallic state [31]. A TEM image of synthesized AgNPs is presented in Figure 2C and reveals that the distribution of the synthesized silver particles was uniform and well dispersed with little agglomeration.…”

Section: Characterization Of the Synthesized Agnpsmentioning

confidence: 96%

Characterization and Antibacterial Properties of Polyetherketoneketone Coated with a Silver Nanoparticle-in-Epoxy Lining

et al. 2022

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Polyetherketoneketone (PEKK) is an alternative material for use in removable partial denture frameworks; these frameworks must exhibit antibacterial properties to reduce the risk of periodontal disease. In the present study, silver nanoparticles (AgNPs) were synthesized via the reduction of silver nitrate with sodium borohydride in a solution containing polyvinyl pyrrolidone (PVP). Transmission electron microscope images and dynamic light scattering confirmed that metallic nanoparticles had been created with an average size of 32 nm. Furthermore, the coating of the PEKK polymeric substrate with 0.5% AgNPs was carried out using an epoxy resin lining at room temperature. Fourier transform infrared (FTIR) spectra confirmed the successful transfer of the AgNP-in-resin lining onto the polymeric substrate. Scanning electron microscopy and atomic force microscopy confirmed that the AgNPs had been uniformly deposited onto the PEKK specimens. Finally, the antibacterial activity of the specimens was tested against Porphyromonas gingivalis. An inhibition zone of 22.5 mm and an antibacterial rate of 83.47% were found for the PEKK coated with 0.5% AgNPs (0.5% Ag-PEKK) compared to an untreated polyetheretherketone (PEEK) substrate, evidencing that 0.5% Ag-PEKK has potential antibacterial properties for implant applications.

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“…These aliquots were centrifuged to remove inorganic particles; the resultant supernatant solution was taken for the absorption studies in a UV/vis spectrometer, ranging from 200-800 nm. The degradation efficiency (η) of the dye solution is illustrated below [28].…”

Section: Photocatalytic Degradation Studymentioning

confidence: 99%

Ultrasensitive Electrochemical Detection and Plasmon-Enhanced Photocatalytic Degradation of Rhodamine B Based on Dual-Functional, 3D, Hierarchical Ag/ZnO Nanoflowers

Sebastian

Balram

2022

Sensors

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The sensitive detection and degradation of synthetic dyes are pivotal to maintain safety owing to the adverse side effects they impart on living beings. In this work, we developed a sensitive electrochemical sensor for the nanomolar-level detection of rhodamine B (RhB) using a dual-functional, silver-decorated zinc oxide (Ag/ZnO) composite-modified, screen-printed carbon electrode. The plasmon-enhanced photocatalytic degradation of organic pollutant RhB was also performed using this nanocomposite prepared by embedding different weight percentages (1, 3, and 5 wt%) of Ag nanoparticles on the surface of a three-dimensional (3D), hierarchical ZnO nanostructure based on the photoreduction approach. The structure and morphology of an Ag/ZnO nanocomposite were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), elemental mapping, ultraviolet-visible (UV-vis) spectroscopy, and X-ray diffraction (XRD). The electrochemical sensor exhibited a very high sensitivity of 151.44 µAµM−1cm−2 and low detection limit of 0.8 nM towards RhB detection. The selectivity, stability, repeatability, reproducibility, and practical feasibility were also analyzed to prove their reliability. Furthermore, the photocatalysis results revealed that 3 wt% of the Ag/ZnO hybrid nanostructure acquired immense photostability, reusability, and 90.5% degradation efficiency under visible light. Additionally, the pseudo-first-order rate constant of Ag-3/ZnO is 2.186 min−1 suggested promising activity in visible light photocatalysis.

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Bi-functional renewable biopolymer wrapped CNFs/Ag doped spinel cobalt oxide as a sensitive platform for highly toxic nitroaromatic compound detection and degradation

Cited by 26 publications

References 41 publications

Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton

Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton

Characterization and Antibacterial Properties of Polyetherketoneketone Coated with a Silver Nanoparticle-in-Epoxy Lining

Ultrasensitive Electrochemical Detection and Plasmon-Enhanced Photocatalytic Degradation of Rhodamine B Based on Dual-Functional, 3D, Hierarchical Ag/ZnO Nanoflowers

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