Amrita Kaurwar Nighojkar

Bio: Amrita Kaurwar Nighojkar is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Adsorption & Medicine. The author has an hindex of 2, co-authored 4 publications receiving 8 citations.

Article Application of neural network in metal adsorption using biomaterials (BMs): a review.

Abstract: With growing environmental consciousness, biomaterials (BMs) have garnered attention as sustainable materials for the adsorption of hazardous water contaminants. These BMs are engineered using surface treatments or physical alterations to enhance their adsorptive properties. The lab-scale methods generally employ a One Variable at a Time (OVAT) approach to analyze the impact of biomaterial modifications, their characteristics and other process variables such as pH, temperature, dosage, etc., on the removal of metals via adsorption. Although implementing the adsorption procedure using BMs seems simple, the conjugate effects of adsorbent properties and process attributes implicate complex nonlinear interactions. As a result, artificial neural networks (ANN) have gained traction in the quest to understand the complex metal adsorption processes on biomaterials, with applications in environmental remediation and water reuse. This review discusses recent progress using ANN frameworks for metal adsorption using modified biomaterials. Subsequently, the paper comprehensively evaluates the development of a hybrid-ANN system to estimate isothermal, kinetic and thermodynamic parameters in multicomponent adsorption systems.

Use of marble and iron waste additives for enhancing arsenic and E. Coli contaminant removal capacity and strength of porous clay ceramic materials for point of use drinking water treatment

Abstract: This paper elaborates manufacture and performance analysis of new clay ceramic (CC) water filtration materials. The CC is manufactured from clay and sawdust mix. Waste marble powder and machined iron fines are used as additives to the mix for manufacturing the new modified materials. An equal volume of clay and sawdust were used to manufacture the control CC. Another ceramic, marble clay ceramic (MCC), was manufactured with distinct volume fractions of clay, sawdust, and marble (40:40:10). Third ceramic, ferrous clay ceramic (FCC), was manufactured from an equal volume of clay and sawdust and five percent by volume of iron fines. FCC showcased better arsenic (As (V)) contaminant removal from water at acidic pH while MCC showcased best As (V) removal at around pH of 8. Average flexural strength of MCC was comparatively better than FCC and CC. The modified materials showcased similar percolation rates at par with control CC. MCC showcased comparatively better E. coli removal capabilities than FCC and CC. Only limited volumetric addition of marble powder and iron fines were found to positively affect compressive strength. The results demonstrate new low-cost ways of modifying strength and specific water treatment characteristics of CC using waste materials from local marble-processing and iron-machining industries.

Functionalized polymeric architectures (FPAs) for uranium recovery from oceans: A review on adsorptive approaches, models and spectrophotometry for understanding the interaction mechanism

Abstract: Uranium is the prime source of nuclear power production. Seawater can serve as an open reservoir of nuclear fuel as it contains ∼4.5 billion metric tons of uranium; however, its low concentrations (∼3.3 ppb) make its large-scale selective extraction economically challenging. Adsorption via functionalized polymeric architectures (FPAs) has been efficient for sequestering uranium from ocean water because of their high affinity towards uranyl ions, chemical stability, and good mechanical strength. The review is focused on analyzing the uranium extraction ability of FPAs in real and artificial seawater matrix. It assesses the role of experimental variables, sorption models, and technical characterization studies from the perspective of understanding uranium binding mechanisms. The review indicated that the adsorption rate of FPAs in natural seawater ranged between 0.003 – 2.27 g kg−1 day−1. The bifunctional amidoximated three-dimensional fibers yielded maximum uptake capacity of 985 mg g − 1 while the Zn2+-poly(amidoxime) hydrogel membrane exhibited superefficient uptake kinetics ∼1180 mg g − 1. The sorption data demonstrated that the pseudo-second order model well captured the kinetics and that interparticle diffusion governed the mass transfer. The analytical characterization of Ur-loaded FPAs showed synergistic chelation of amidoxime and amine functional groups with uranyl ions from seawater. However, there is scant literature about the complex uranium adsorption behavior in dynamic conditions involving marine microorganisms and increasing temperature conditions. Therefore, future priorities should include marine applicability, durability, and life cycle sustainability impacts (LSCA) for measuring the commercial feasibility of FPAs for uranium recovery from oceans.

Fabrication of porous ceramic pot filters for adsorptive removal of pollutants in tannery wastewater

Abstract: The use of porous ceramic pot filters for wastewater treatment is considered a cost-effective technology however presence of appropriate pore size to trap pollutants and microorganisms from industrial wastewater remain a challenge. In this study, naturally available kaolin was first characterized and porous ceramic pot filters from different ratios of the kaolin to sawdust which served as combustible material and fired at 910 °C were produced. Ten different filters were fabricated with different mixing ratios of kaolin and sawdust. The clay materials were characterized for their chemical compositions, morphology and thermal stability using different analytical instruments. The performance of the regular and scrubbed ceramic water filters from the different proportions at different the flow rate, their porosities and removal efficiencies of some pollutants in tannery wastewater were evaluated The chemical compositions of the raw material (kaolin) contained oxides of silicon (51.03%) and aluminium (33.75%), respectively. Physicochemical and microbial analysis of the tannery wastewater were carried out using standard methods and the results of the analysis showed significant differences in the removal efficiencies of the pollutants by the various ceramic pot filters. The least porous filter pots coded (T8) containing 67% kaolin and 33% sawdust with flexural strength (55.53 MPa) was found most effective for the removal of COD (78.37%), BOD (91.66%), chloride (88.77%), nitrate (49.07%), sulphate (82.97%), TDS (86.84%), TSS (78.70%), TH (70.00 %) and TA (86.26%) compared to other fabricated pot filters (T1-T7, T9 and T10). All the ceramic filters exhibited excellent antimicrobial removal efficiency towards Fusarium chlamydosporium, Bacillus subtilis and Bacillus megaterium in tannery wastewater. From the results, it was concluded that regular ceramic pot filters performed better than the scrubbed filters due to the clogging effect of the former than the latter. Finally, the degree of porosity affects the performance and removal efficiency of the fabricated kaolin based filters.

Article Application of neural network in metal adsorption using biomaterials (BMs): a review.

Abstract: With growing environmental consciousness, biomaterials (BMs) have garnered attention as sustainable materials for the adsorption of hazardous water contaminants. These BMs are engineered using surface treatments or physical alterations to enhance their adsorptive properties. The lab-scale methods generally employ a One Variable at a Time (OVAT) approach to analyze the impact of biomaterial modifications, their characteristics and other process variables such as pH, temperature, dosage, etc., on the removal of metals via adsorption. Although implementing the adsorption procedure using BMs seems simple, the conjugate effects of adsorbent properties and process attributes implicate complex nonlinear interactions. As a result, artificial neural networks (ANN) have gained traction in the quest to understand the complex metal adsorption processes on biomaterials, with applications in environmental remediation and water reuse. This review discusses recent progress using ANN frameworks for metal adsorption using modified biomaterials. Subsequently, the paper comprehensively evaluates the development of a hybrid-ANN system to estimate isothermal, kinetic and thermodynamic parameters in multicomponent adsorption systems.

Fabrication of Biodegradable Fibrous Systems by Employing Electrospinning Technology for Effluent Treatment

Abstract: The everlasting industrialization with the evolution of humankind and the upsurge in population has led to undesirable environmental changes due to anthropogenic activities, exacerbating the environ, especially the aquatic ecosystem....