Lakshminath Bezbaroa Central Library Digital Repository
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- This digital archive comprised of the Institutes' intellectual output.
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Recent Submissions
Inflaton and Dark Matter Phenomenology Via Reheating and Its Observational Signatures
(2025) Mondal, Rajesh
We are currently in the era of precision cosmology, which offers us a unique opportunity to investigate beyond the Standard Model (SM) of physics. Toward this endeavor, the inflaton and Dark Matter (DM) are assumed to be natural new physics candidates. It is believed that reheating takes place right after inflation, during which all the SM particles are produced. Interestingly, reheating not only explains the cosmic origin of visible matter but also provides a mechanism for the production of other cosmological relics, such as DM. Furthermore, reheating can also affect the observational predictions of the preceding phase of inflation. Thus, reheating offers a promising playground for the phenomenological study of inflation and DM within a unified framework, which has been studied extensively in this thesis. Wefirst studied the dynamics of reheating for a general inflaton equation of state (EoS), considering both gravitational and non-gravitational interactions between the inflaton and radiation. We showed that, depending on the EoS and the nature of the inflaton’s decay products (radiation), thermal effects can play a significant role in the reheating process. We have constrained key microphysical parameter, namely the non-gravitational inflaton coupling, in terms of the inflaton EoS, the reheating temperature, and the CMB spectral index. Furthermore, we analyzed the implications of the reheating dynamics for the DM phenomenology, considering both thermal and non-thermal production of DM. The non-trivial expansion and thermal history during reheating significantly impact the viable DM parameter space, potentially enlarging the regions accessible to future experiments. This opens a promising, indirect window to probe the early Universe in laboratory settings. Then, we explored the impact of the latest observation of Planck and BICEP/Keck data on the inflaton phenomenology. Due to the lack of direct experimental probes, both the inflationary and post-inflationary parameters, like inflationary e-folding number, reheating temperature, inflaton couplings, etc, remain largely unconstrained. Using the latest constraints on CMB from Planck+BICEP/Keck, we derived detailed phenomenological constraints on inflationary and post-inflationary parameters. Finally, we propose a novel reheating scenario governed by the right-handed neutrinos (RHNs) in the well-known Type-I seesaw framework embedded in the SM. Our scenario represents the most minimal possible framework, as it does not introduce any new interactions beyond the SM, except for gravity. We call this scenario gravitational neutrino reheating, abbreviated as νGRe. Interestingly, νGRe not only offers successful reheating but also solves the well-known neutrino mass and baryon asymmetry problems. This νGRe constrains a large class of inflation models, RHN masses, and predicts a non-vanishing lightest active neutrino mass. Overall, this thesis demonstrates how reheating serves as a unifying bridge between inflation, dark matter, and particle physics, allowing these seemingly disparate sectors to be constrained within a single framework. By combining theoretical modeling with state-of-the-art cosmological observations, it shows how precision cosmology can indirectly probe physics at energy scales far beyond the reach of terrestrial.
Structure and Functional Analysis of a Recombinant Endoglucanase (AtGH9C-CBM3A-CBM3B) from Acetivibrio Thermocellus ATCC 27405 and its Application in Synthesis of Nanocellulose-based Hydrogel for Dye Removal
(2025) Mandal, Ardhendu
Cellulose, the most abundant homogenous polysaccharide on Earth, is a renewable and sustainable carbon source. Its efficient degradation requires a synergistic enzyme system known as cellulases. Among these, glycoside hydrolase family 9 (GH9) members exhibit endo-, exo-, or processive endocellulase activity, although the structural basis for this variation remains unclear. This study investigates a novel recombinant GH9 β-1,4-endoglucanase, AtGH9C-CBM3A-CBM3B, from Acetivibrio thermocellus ATCC 27405, focusing on its biochemical properties, the catalytic role of its carbohydrate-binding modules (CBMs), structural conformation, and application in nanocellulose synthesis and dye adsorption. The gene encoding full-length AtGH9C-CBM3A-CBM3B and its truncated variants (AtGH9C-CBM3A, AtGH9C, CBM3A, CBM3B) were cloned, expressed in E. coli BL21(DE3), and purified. AtGH9C-CBM3A-CBM3B displayed maximum activity at 55 °C and pH 7.5, with highest activity toward carboxymethyl cellulose (CMC, 58.8 U/mg), followed by lichenan (44.5 U/mg), β-glucan (36.2 U/mg), and hydroxyethyl cellulose (17.9 U/mg). The catalytic core AtGH9C alone exhibited negligible activity, confirming the essential contribution of CBMs. The enzyme showed pH stability (6.0–9.0), thermal stability up to 60 °C for 90 min, and a Tm of 65 °C. Product analysis revealed generation of cellotetraose and longer oligosaccharides, confirming endo-β-1,4-glucanase activity. Partial recovery of AtGH9C activity by adding CBM3A, CBM3B, or both (47%, 13%, and 50%, respectively) highlighted their role in catalysis and thermostability. Structural modeling revealed an (α/α)_6-barrel fold with a catalytic triad (Asp98, Asp101, Glu489). CD analysis showed 25.2% α-helix, 18.4% β-sheet, and 56.4% random coils, aligning with PSIPRED and SOPMA predictions. MD simulations of the enzyme–cellotetraose complex (200 ns) confirmed enhanced structural stability (RMSD: 1.5 nm vs. 1.8 nm without ligand). RMSF analysis indicated high flexibility in CBM3B, suggesting a lesser role in binding. Docking studies revealed strong binding to cellotetraose (ΔG = –5.05 kcal/mol), with lower affinity for shorter or longer oligosaccharides. Loop 3 (aa 342–379) appeared to block the non-reducing end of cellulose, facilitating processive cleavage and cellotetraose release. SAXS analysis at 5 mg/mL showed a monodisperse, compact, fist-and-elbow-shaped protein. The zeta potential (–24 mV) confirmed stability without aggregation. The enzyme was used with exoglucanase AtCBH5A (62 kDa, 96.82 U/mg activity) to hydrolyze sugarcane trash cellulose (SCT), extracted via optimized alkaline pretreatment. Enzymatic nanocellulose (EN-NC) was produced by 6 h hydrolysis using 1.5 mg enzyme/g cellulose. For comparison, TEMPO-oxidized nanocellulose (TO-NC) was also prepared. FTIR and XRD patterns were similar for SCT, EN-NC, and TO-NC, while FESEM revealed morphological differences: SCT showed micron-scale fibers (~10 μm), whereas EN-NC and TO-NC displayed nanoscale structures (10–100 nm), with EN-NC showing narrower fibrils (≤20 nm), indicating higher specificity. EN-NC (0.5 g/50 mL) was dispersed in 2% acetic acid and blended with CMC-Na (1.0 g/50 mL) to form NC–CMC hydrogels at 35 °C. Swelling equilibrium was reached within 6 h. The hydrogel showed a pHpzc of 6.6 and a surface area of 4.81 m²/g (vs. CMC alone: 1.57 m²/g). Adsorption studies revealed 88.53% Congo Red (CR) removal at pH 7.5, 48.75 mg/L, 0.47 g dosage, and 4.75 h. Methylene Blue (MB) removal peaked at 94.67% at pH 6.0, 37.5 mg/L, 0.6 g dosage, and 3.5 h. MB followed the Freundlich isotherm (multilayer adsorption), while CR fit both Freundlich and Langmuir models. Kinetics suggested pseudo-second-order adsorption, driven by chemisorption via hydrogen bonding, electrostatic, and n–π interactions. Regeneration was effective using 0.1 M NaOH with 50% ethanol (CR) or 0.1 M HCl/HNO₃ (MB). These results establish NC–CMC hydrogels as promising, eco-friendly adsorbents for tertiary treatment of dye-laden wastewater.
Relativistic Accretion Flows Around Rotating Black Holes: Effects of Viscosity, Thermal Conduction, and Magnetic Fields
(2025) Singh, Monu
The comprehensive analysis presented in this thesis significantly advances the understanding of the physics governing relativistic accretion flows onto black holes. This thesis investigates hot, relativistic, viscous, and magnetized accretion flows around rotating black holes, focusing on how viscosity, thermal, conduction, and magnetic fields governs the flow properties, controlling the thermodynamics and radiative signatures of accreting black hole systems. The transonic properties of the flow are regulated by the by the radially varying viscosity, and modifies the critical points. Thermal conduction transfers the heat from the inner region of the flow to the outer region and thermodynamics properties of the flow gets altered and hence the luminosity and spectral energy distribution. Furthermore, magnetic field plays a vital role in transport of the angular momentum and synchrotron emission process. Overall, the thesis presents a framework for understanding the various aspects of relativistic accretion flows.
Design and Development of Advanced Porous Organic Polymeric Adsorbents for the Efficient and Selective Removal and Recovery of Phosphate and Arsenate from Water
(2025) Hazarika, Gunanka
The thesis entitled as “Design and Development of Advanced Porous Organic Polymeric Adsorbents for the Efficient and Selective Removal and Recovery of Phosphate and Arsenate from Water”, mainly focuses on the design, synthesis, and application of novel modern polymeric adsorbents for the efficient removal and recovery of environmentally hazardous oxoanions – specifically phosphate and arsenate – from aqueous media. This thesis comprises five distinct chapters, which begins with a thorough review of pertinent literature and is followed by chapters that outline the development and findings of the experimental investigations conducted during the research period.
Lightweight Deep Learning Architectures for Semantic Scene Segmentation for Applications in Autonomous Driving
(2025) Mazhar, Saquib
Semantic segmentation, which assigns a class label to each pixel in an image, is fundamental to autonomous driving systems that must perceive and understand complex environments in real time. Achieving high segmentation accuracy while maintaining computational efficiency remains a major challenge, particularly for embedded systems with limited resources. This thesis addresses these challenges by proposing novel methods that enhance both segmentation performance and efficiency. A key contribution is a composite loss function that integrates cross-entropy, boundary, and region-based losses to improve accuracy around object edges and better handle small and infrequent classes. This leads to improved segmentation results, especially for critical but underrepresented objects such as pedestrians and traffic lights. To support real-time operation, this work introduces lightweight network architectures. The Inverse esidual Dilation Pyramid Network (IRDPNet) employs efficient bottlenecks and multi-scale dilation to significantly reduce model size while preserving accuracy. The Block Attention Network (BANet) further enhances contextual understanding by integrating a modified attention mechanism that captures long-range dependencies with minimal overhead. Additionally, the Context-Guided Multi-scale Attention Network (CGMANet) is proposed to combine both low-level spatial features and high-level semantic cues through a hybrid attention mechanism. This architecture effectively balances detail preservation and context awareness, making it highly suitable for deployment on embedded platforms. Collectively, these contributions offer practical solutions for real-time, accurate semantic segmentation in autonomous driving scenarios.