Lakshminath Bezbaroa Central Library Digital Repository
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- This digital archive comprised of the Institutes' intellectual output.
- It manages, preserves & makes available the academic works of faculty and research scholars.
- It is established to facilitate deposit of digital content of scholarly or heritage nature.
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Recent Submissions
Development of Optical Fiber Sensors for Environmental Engineering and Homeland Security Employing Evanescent Wave Absorption and Localized Surface Plasmon Resonance Spectroscopy
(2025) Banoo, Fatima
This thesis focuses on the development of optical fiber sensors for detecting water contaminants, specifically mercury (Hg²⁺), arsenic (As³⁺), and explosive trinitrophenol (TNP), which are crucial for environmental monitoring and homeland security respectively. The primary objective is to develop highly sensitive sensors with exceptionally low limits of detection (LOD), rapid response times, high selectivity, and high degree of stability, repeatability and reliability. The novelty of this research lies in the innovative integration of various nanocomposites, polymers, and composite materials with fiber optics to develop optical fiber Hg²⁺, As³⁺, and TNP sensors. Two key sensing techniques were employed: intensity modulation through evanescent wave absorption and wavelength modulation using localized surface plasmon resonance (LSPR). The research begins with the development of a U-shaped optical fiber LSPR based sensor for Hg²⁺ detection, utilizing graphene oxide and chitosan (GO-CS) composite as the sensing material. This sensor demonstrates outstanding sensitivity of 0.0728 nm/ppb, an ultra-low LOD of 0.29 ppb. It also exhibits high selectivity towards Hg2+ and a rapid response time of 0.6 s. In order to further enhance the sensing performance, a second Hg²⁺ sensor is developed incorporating carbon nanotube/polyvinyl alcohol (CNT/PVA) nanocomposite as the sensing material. This sensor offered even higher sensitivity of 0.2458 nm/ppb and a lower LOD of 0.08 ppb, while maintaining high selectivity and an improved response time of 0.4 s. Next, an optical fiber LSPR sensor for detecting another highly toxic water contaminant As3+ ion is developed, employing Al₂O₃/GO nanocomposite as the sensing material. This sensor exhibits high sensitivity of 0.217 nm/ppb, a remarkably low LOD of 0.09 ppb. The sensor also exhibits a fast response time of 0.5 s and high selectivity towards As3+. To further enhance sensing performance, another As³⁺ sensor is developed using lauryl-functionalized gold nanoparticles. This sensor offered an enhanced sensitivity of 0.3073 nm/ppb, even lower LOD of 0.06 ppb, while maintaining high selectivity and rapid response time of 0.5 s. For TNP detection, an optical fiber sensor based on evanescent wave absorption is developed, utilizing a novel polymer (PFTPA) film. The sensor exhibits high sensitivity of 0.0032/ppb, a remarkably low LOD of 1.06 ppb, rapid response time of 2 s and shows high selectivity towards TNP. In order to further enhance the sensing performance, another TNP sensor is developed using a LSPR configuration, incorporating zinc oxide quantum dots (ZnO QDs) as the sensing film. This sensor offers a much lower LOD of 0.19 ppb and significantly higher sensitivity of 0.1288 nm/ppb, while maintain the rapid response time of 2 s and high selectivity towards TNP. It is worth mentioning that, all the novel sensors developed in this research exhibits excellent reversibility, repeatability, stability and reliability. Moreover, their real-world applicability is validated through successful detection of Hg²⁺, As³⁺, and TNP in real water samples, demonstrating their potential for environmental monitoring and homeland security applications.
Computational Investigation of Cyclic Peptide Nanotubes: Self-Assembly, Solvent Effects, and Transport Behavior of Water and Ions
(2025) Moral, Rimjhim
The present thesis entitled “Computational Investigation of Cyclic Peptide Nanotubes: Self-Assembly, Solvent Effects, and Transport Behavior of Water and Ions” presents a comprehensive molecular dynamics investigation of cyclic peptide nanotubes (CPNTs), focusing on their self-assembly, stability, and transport properties across diverse environments. The self-assembly mechanism of cyclic peptides in aqueous solutions is examined, revealing salting-in and salting-out effects governed by NaCl concentration and enhanced nanotube formation at lower temperatures. The influence of solvent polarity and amino acid composition is then explored, demonstrating that non-polar solvents and alternating hydrophilic-hydrophobic residues stabilize the CPNT structure. Extending to deep eutectic solvents (DESs), simulations show that DESs markedly stabilize CPNTs, with stability diminishing upon increased hydration and temperature. Subsequent studies in lipid bilayers establish that CPNTs integrate seamlessly as synthetic water channels, maintaining characteristic water transport dynamics. Finally, ion transport studies reveal a strong preference for cations, particularly Na⁺ and K⁺, while anions face significant energy barriers. Together, these findings provide fundamental insights into CPNT behavior across environments and suggest their potential for applications in nanofluidic and biomimetic membrane systems.
Structure and Functional Insights of a Recombinant Bifunctional a-L-arabinofuranosidase (BoGH43_35) with Endo-xylanase Activity from Bacteroides ovatus ATCC 8483 and its Application in Fruit Juice Clarification and Waste Peel Saccharification
(2025) Shrivastava, Madhulika
The thesis includes introduction and literature review on dietary fiber and their sources, including the nutritional value of arabinoxylan, its hydrolyzed products, followed by cloning and expression of the putative α-L-arabinofuranosidase, BoGH43_35, a family 43 and subfamily 35 glycoside hydrolase (GH43_35) from Bacteroides ovatus ATCC 8483. This study reports biochemical and structural characterization of novel bifunctional α-L-arabinofuranosidase/endo-β-1,4-xylanase. The gene cloned in pHTP1 expressed in E. coli BL21(DE3) was purified to homogeneity, revealing a ~74 kDa protein. BoGH43_35 showed maximum activity against wheat arabinoxylan at 37°C and pH 7.0. BoGH43_35 hydrolyzed wheat arabinoxylan with Vmax 5.4 U.mg-1 and KM 2.7 mg.mL-1. BoGH43_35 hydrolyzed products of wheat arabinoxylan when subjected to TLC and HPLC revealed both α-L-arabinofuranosidase and endo-β-1,4-xylanase activities. NMR displayed that BoGH43_35 removes L-arabinose at O-2 or O-3 position from mono-substituted arabinoxylan thereby categorizing it as Type I α-L-arabinofuranosidase. AlphaFold2 revealed 5-bladed-β-propeller fold of catalytic module followed by two consecutive jellyroll type β-sandwich fold by CBM6A and CBM6B. MD simulated structures of BoGH43_35-arabinose complex and only BoGH43_35 revealed stability of BoGH43_35-arabinose complex. Binding analysis of BoGH43_35 by fluorescence spectroscopy against wheat arabinoxylan showed association constant, Ka of 3.11x102 M−1 and presence of two binding sites. BoGH43_35 maximized TRS yield in raw pomegranate and mosambi peels producing significant amounts of reducing sugars, with TRS yields of 66 mg/g raw PP and 60 mg/g raw MP. With continued research and industrial adoption, BoGH43_35 has potential to revolutionize fruit processing and lignocellulosic biomass utilization, contributing to a more sustainable agro-industrial sector.
Production and recovery of Polyhydroxybutyrate (PHB), biodegradable plastic from cyanobacteria under photoautotrophic conditions
(2025) Yashavanth, P R
The current study investigates the single-stage cultivation of Chlorogloea fritschii TISTR 8527 with phototrophic CO2 assimilation and polyhydroxybutyrate (PHB) production using acetate as an inducer under dark. The study focuses on the improvement of PHB production in photobioreactor under diurnal light mimic to sunlight. Initially the effect of constant and diurnal light on growth of C. fritschii and effect of nitrate under diurnal light on PHB production have been explored. Also, the optimum level of acetate inducer has been decided based on experiments. A phosphate and nitrate feeding strategy has been used to improve the PHB production using single-stage cultivation. NaNO3, K2HPO4, TRACE (micronutrient solution), Na2EDTA, and MgSO4.7H2O were screened as important media compositions. The multi-objective media optimization based on desirability approach with response surface methodology (RSM) was performed to simultaneously enhance the dry cell weight (DCW, g/L), PHB (% w/w) and auto-sedimentation concentration factor (SCF) in single stage cultivation under diurnal light to reduce the process cost. This is the first multi-objective optimization study for media optimization using cyanobacteria reported till now under diurnal light mimic to sunlight for bioplastic production. The effect of CO2 supply and multiple additions of acetate inducer on growth, PHB accumulation and SCF were also studied under diurnal simulated sunlight with optimized medium in flat panel photobioreactor (PBR). PHB extraction from cyanobacteria increases production cost since PHB is an intracellular product and must be purified in various steps. The intracellular PHB was recovered with various methods utilizing pretreatment of biomass with hypochlorite or methanol along with solvent extraction by halogenated and green solvents. PHB recovered from C. fritschii using green solvent dimethyl carbonate (DMC) has improved thermal and material characteristics compared to PHB recovered using dispersion. Characterization of recovered PHB suggested that C. fritschii can accumulate biopolymer similar to commercial PHB.
Removal of Arsenic from Water using Hybrid SLM-Electrocoagulation Technique
(2024) Sarkar, Soumi
This research focuses on a novel hybrid technique combining supported liquid membrane (SLM) separation with electrocoagulation for effective arsenic removal from water. Utilizing sesame oil, an environmentally benign solvent, and Aliquat® 336, the study developed a pseudo-binary liquid membrane system. The work includes comprehensive physicochemical analysis and molecular modelling of the membrane system. It reveals that As(V) is more favourable for extraction due to its larger ionic size and higher positive charge compared to As(III). Two-phase equilibrium studies and advanced statistical and machine learning models, including artificial neural networks and genetic algorithms, optimized the extraction process. A three-phase SLM setup demonstrated efficient separation and recovery of arsenic species, with performance enhanced by synergistic effects between As(III) and As(V).