Dissertations / Theses on the topic 'Research Subject Categories – INTERDISCIPLINARY RESEARCH AREAS - Materials Engineering'

2D material-based nanoelectromechanical systems have emerged as excellent tools for force measurement with extreme sensitivity levels. Most sensing methods with 2D nanoelectromechanical (2D NEMS) systems utilize frequency tuning of the resonant mode in response to external stimuli. However, the interaction of the harsh external stimulus with the delicate 2D NEMS limited these devices’ utility only in the research labs. We propose a fabrication and packaging method for 2D NEMS devices to extend their application outside the research labs. Under the proposed scheme, the 2D NEMS is coupled to the external stimulus through substrate strain. The substrate acts as a protective barrier between the NEMS and the environment. At the same time, the substrate also influences the strain on the 2D NEMS. The external stimulus changes the strain on the substrate and hence on the 2D NEMS device. The strain change on 2D NEMS changes the frequency of vibration modes. 2D materials such as graphene have a high Young’s modulus. High Young’s modulus allows the strain to frequency transductions with high accuracy and sensitivity. We report the most straightforward application of this scheme for pressure sensing with a responsivity of 20Hz/Pa. Using the proposed scheme, we also demonstrate the ability to utilize duffing nonlinear response of the graphene resonator for pressure sensing. The resonant response of the 2D nanoresonators becomes nonlinear, even at very small excitation voltages. The nonlinear response of the 2D nanoresonators shows sharp amplitude jumps at the bifurcation points and hysteresis. We utilize the sharp amplitude jumps to realize the bifurcation amplifier for pressure sensing. While the hysteresis in the frequency response is used to demonstrate basic logic operations such as OR, AND, and XOR with pressure pulse as input and vibration amplitude as output. The external stimulus can also have a dynamic variation that can excite the substrate’s vibration modes. In this case, the frequency tuning of the 2D NEMS is also dynamic as it follows the strain on the substrate. Utilizing this principle, we report the ability of the 2D NEMS to track the dynamic stimulus with a frequency component as high as 40kHz. Characterizing time-varying stimuli is crucial for accelerometers, acoustic sensors, and vibrometers. We demonstrate the use of highly responsive 2D nanoresonators for such dynamic sensing. Since the proposed 2D NEMS package allows external stimulus to couple to the 2D NEMS efficiently, the 2D NEMS is also susceptible to various environmental noise sources. We use the Allan Deviation of the frequency fluctuations to study the performance of these devices against noise. The measurements reveal that the primary cause of the frequency fluctuations of the 2D NEMS is the temperature of the surrounding air. These measurements provide crucial insights into designing a sensor with the required sensitivity, bandwidth and noise isolation. The barrier-substrate design can be changed according to specific applications to achieve the intended transduction. This concept can be extended easily for sensing inertial forces, biological stimuli, and temperature.

Quantitative diffusion analysis in multicomponent metallic systems has been a formidable task historically and despite decades of research, most of the diffusivity estimations were limited to interdiffusion and some intrinsic diffusion coefficients in binary systems and interdiffusion coefficients in a few ternary systems until recently. The experimental complications associated with the need to intersect (n-1) serpentine diffusion paths in the n dimensional space for determining the 〖(n-1)〗^2 interdiffusion coefficients lead to various approaches like average diffusivity, square root diffusivity estimations that approximate a representative value of the diffusivity across a composition range from a single experiment. However, these values are not material constants and do not provide any information about the atomic interactions. This lack of diffusivity data in multicomponent systems has hampered the development of mobility databases essential for various simulations and physico-chemical studies of materials. This work resolves the issues with quantitative multicomponent diffusion analysis via several newly proposed methods that solves the issue of intersecting diffusion paths through the application of special constrained diffusion paths. The equations necessary to apply these methods are derived and their application is discussed mathematically and applied experimentally to the model alloy system, the NiCoFeCr equiatomic multiprincipal element alloy to compare with available radiotracer data measured for this system. The work first employs the pseudo-binary diffusion couple approach that develops a rectilinear diffusion path in the multicomponent space to the NiCoFeCr system to estimate the tracer coefficients from the intrinsic coefficients at the marker plane. The mathematical formulations derived for the same justify its namesake and the obtained tracer coefficients can be used to back calculate the intrinsic and interdiffusion coefficients. The pseudo-ternary method improves on the shortcomings of the pseudo-binary diffusion couple method and enables the estimation of tracer coefficients of three components by crossing two constrained diffusion paths in a 2d plane in addition to the main and cross interdiffusion coefficients. The body diagonal method originally proposed for determination of interdiffusion coefficients is modified here to determine the tracer coefficients of all components using only two diffusion profiles thus reducing the errors associated with crossing (n-1).paths per the original approach. This work then explores the possibilities of crossing dissimilar constrained diffusion paths by crossing pseudo ternaries of different types. Strategically crossing a rectilinear pseudo-binary diffusion path with a serpentine conventional (body diagonal) diffusion path overcomes all the previous drawbacks of pseudo binary, pseudo ternary and body diagonal methods to determine the full set of diffusivities at any desired composition and generalizes the constrained diffusion path approach to any order multicomponent system. The obtained tracer coefficients show a good match with the diffusivities measured in radio tracer experiments. Finally, based on the ideas from the constrained diffusion path experiments in the NiCoFeCr system, a constrained path approach is devised to measure the diffusivities in an Al based NiCoFeCr multiprincipal element alloy system which was not possible earlier due to unavailability of radio isotopes and the complexities of interdiffusion experiments in higher order systems. The obtained tracer diffusivities, show an excellent match with the trends extrapolated from lower order systems. Calculated intrinsic and interdiffusion coefficients demonstrate the importance of vacancy wind effect as well as the issues with using diffusivities having different dependent components to make predictions on diffusion trends among different elements.

Biomedical research aims to gain deeper insights into the mechanisms of human pathophysiology to develop improved therapies and diagnostics. Despite significant advances made in the understanding and treatment of human diseases, many bottlenecks persist in successful clinical translation. Conventional culture techniques and animal models suffer from various limitations that fail to recapitulate human physiology and impede the clinical translation of therapies. Among various human diseases, cardiovascular diseases account for the highest number of deaths worldwide. Similarly, skeletal muscle disorders are the leading contributor to disability across the globe. Given the enormous health burden associated with ailments of cardiac and skeletal muscles, the broad goal of this work was to engineer tissue-mimetic templates for these tissues that can serve as reliable in vitro disease models. Toward this goal, simplified methods were standardized to obtain functionally superior primary cardiomyocytes and skeletal myotubes as a robust source of cells for these models. Alongside this, an unconventional and cost-effective surface coating, keratin, derived from human hair was reported to be effective and found comparable to ECM-derived proteins, fibronectin and gelatin, in supporting primary cardiomyocyte culture. Thereafter, microscale and nanoscale surfaces were designed and utilized for gaining unique insights into the cardiac and skeletal myocytes function in normal as well as the diseased state. Specifically, UV lithography and etching techniques were used to create micro-ridges as an organotypic platform to study cardiac hypertrophy and live calcium currents in cardiomyocytes. It was established that aligned cardiomyocytes showed an enhanced response to hypertrophic cues as compared to the unaligned ones and exhibited unidirectional flow of calcium currents. This approach was further extended to develop a potential antioxidant and anti-hypertrophic cardiac patch using PCL and PCL-gelatin electrospun nanofibers decorated with cerium oxide nanoparticles. The cardiomyocytes grown on ceria decorated PCLG nanofibers showed reduced ROS production in the presence of hydrogen peroxide and rescued hypertrophic response when treated with phenylephrine, a GPCR agonist. Furthermore, screening for a variety of engineered substrates was done to retain skeletal myotubes in culture for longer durations, which often detached on smooth surfaces. A nanofibrous platform was thus optimized and investigated as a disease model for muscle degeneration using western blotting and immunofluorescence techniques. Overall, the study revealed different aspects of culturing skeletal myotubes in comparison to cardiomyocytes. This work highlighted the cell-dependent response to topography even among structurally similar cell types. The developed platforms integrating primary cells and anisotropic substrates allowed to achieve precise cellular architecture and study their function in specific pathophysiological conditions. An improved understanding of alterations in cell function in response topography may lead to the development of laboratory models that better recapitulate the in vivo milieu than conventional culture and thereby improve the translation of devised therapies from bench to bedside.

Over 400 million patients suffer from urinary bladder-associated physiological disorders globally, which often necessitate surgical intervention for a reconstructive procedure. The current gold standard for bladder reconstruction, an autologous graft, is proven not to be an ideal substitute in clinics. Such unmet clinical needs drive the continuous surge for structural and functional substitutes of urinary tissues, including ureters, bladder-wall, and urethra. Against this backdrop, the present dissertation explores a biomaterial-based, functionalised alloplastic platform for urological reconstruction. This strategy for an alloplastic urinary tissue encompasses a biostable, 'off-the-shelf' available therapeutic option that simplifies and shortens surgical treatment. Furthermore, it presents the potential to evade the challenges and complications of autografts and scaffold-based regenerative techniques. Considering the prerequisites of a urological alloplast, the combination of polydimethylsiloxane and thermoplastic polyurethanes (TPU/PDMS) is deemed most advantageous. The synergistic integration of varying contents of PDMS within the molten TPU matrix is realised through a processing methodology of dynamic vulcanisation (DV). The experimental outcomes are evaluated and correlated with different phenomenological models to understand DV induced strengthening of structure. The theoretical predictions, in conjunction with material property characterisation, allow a better understanding of the improved interfacial behaviour and superior performance of the crosslinked polymer system. The in situ compatibilised blends are further investigated for clinically relevant viscoelastic properties to sustain high pressure, large distensions, and surgical handling/manipulation. Moreover, non-exhaustive chemical strategies are harnessed to counter urinary tract infections through the covalent incorporation of polycationic moieties. The new generation alloplasts, endowed with contact killing surfaces, are assessed for their efficacy in pathogenically infected artificial urine. In addition, the adhesion and proliferation of murine fibroblasts on different polymeric compositions to establish their cytocompatibility. Building further upon the knowledge of the antibacterial and antifouling activity of polycationic modifications, layer-by-layer (LbL) assembled multifunctional surface grafting are conceived to sustain long-term stability in a urinary environment, to suppress encrustation and biofilm formation. The performance of the single-step and LbL-grafted blends is benchmarked against the conventional urological alloplasts, using a customised lab-scale bioreactor set-up. Post-six weeks of incubation in the dynamic assembly simulating ureasepositive microbial infection, the contact-active blends exhibited a remarkable ability to resist calcium and magnesium encrustation, while retaining adequate grafting integrity. As high as 4-fold log reduction in the planktonic growth of bacterial strains associated with bladder stones and renal calculi is recorded. In vitro cellular assessment is carried out with human keratinocytes and human embryonic kidney cells to evaluate the cytocompatibility of the surface grafted blends against the medical-grade control polymer. Finally, the optimum LbL grafted formulations are investigated for their performance in a phase-I pre-clinical study utilising human urine samples collected from 129 patients. The newly developed blends meet the clinically desirable attributes and present a strong potential as a stable, contact-active, antiencrustation biomaterial platform for urinary implantation. Summarising, this dissertation contemplates the new-generation, infection and encrustationresistant alloplasts. In pursuit of this vision, multifunctional polymeric biomaterials are designed to sustain desirable performance in a urinary environment. These next-gen biomaterials pave the way for an alloplastic platform that can integrate into clinical practice to improve the quality of modern urological treatment.

The need and demand for continuous high-speed, energy-efficient hardware advancement is undisputed. Traditional computing system with von Neumann architecture leads to high energy consumption and latency due to a huge amount of data transfer between the separated memory unit and the logic unit. In response to this discrepancy, extensive research has been conducted to develop brain-inspired electronic devices that can provide alternate computing platforms needed for implementing hardware neural networks. Artificial synapse, which emulates the dynamics of biological synapses, such as “update” and “memorize,” is one approach toward solid-state implementation of bio-inspired devices. Recently, two-dimensional (2D) van der Waals (vdW) materials have been actively explored for such artificial synapses. The distinctive electronic, optoelectronic, and mechanical properties of two-dimensional (2D) materials make these quite attractive for a wide variety of applications. This thesis explores the electronic and optoelectronic properties of 2D materials for mimicking the synaptic performance of the neuron. Materials of interest include MoS2, which is semiconducting, and α-In2Se3, a ferroelectric semiconducting material, investigated as active elements for synaptic applications. In the first part of the dissertation, we try to understand the working mechanism, i.e., charge trapping and de-trapping in synaptic devices using MoS2 as the channel material in a simple back-gated configuration. To this end, we have used a high-k dielectric (Ta2O5) as the gate oxide, which is expected to reduce the voltage swing and hence the power consumption, which is beneficial when used in neuromorphic networks. The hysteresis in the transfer characteristics of the transistor arising out of the Ta2O5/MoS2 interface and interface trap charges within the oxide are exploited to demonstrate excitatory Post Synaptic current (EPSC) / Inhibitory Post Synaptic current (IPSC), Long Term Potentiation (LTP) / Long Term Depression (LTD), Spike Amplitude Dependent Plasticity (SADP), Spike Timing Dependent Plasticity (STDP) at a relatively lower energy budget. In the second part, we discuss the working mechanism of 2D ferroelectric semiconducting channel material (α-In2Se3) for synaptic applications. Ferroelectric materials have emerged as a promising candidate for enabling synaptic devices as they lead to fast operation, non-destructive readout, low-power, low variations, and high on/off ratios. The partial polarization switching behavior of the ferroelectric material can be exploited to emulate the biological synaptic functions by gradually modulating the channel conductance through an external electrical field. We also explored the continuous weight modulation through partial polarization of the channel displaying an excellent linear weight update trajectory with multiple stable conductance states. In the next part of the dissertation, we discuss artificial neural networks for pattern recognition using the conductance weights obtained from device-level emulation of synaptic dynamics. By updating the synaptic weights with conductance weight values on 18,000 digits, we achieved a successful recognition rate of 93% on the testing data. The introduction of 0.10 variance of noise pixels results in an accuracy of more than 70%, showing the strong fault-tolerant nature of the conductance states. These synaptic functionalities, learning rules, and device-to-subsystem-level simulation results based on α-In2Se3 could facilitate the development of more complex neuromorphic hardware systems based on FeS-FETs. In the last part of the dissertation, we introduce a light-sensing function merged into the artificial synapses to realize an optoelectronic synapse. The optical input signal (λ = 527 nm) is used as a presynaptic signal with various frequencies and strengths to imitate the synaptic functionalities such as short-term memory (STM) and long-term memory (LTM), paired-pulse facilitation (PPF), spike rate-dependent plasticity (SRDP) spike duration-dependent plasticity (SDDP) and memory functions like learning, forgetting, and relearning

The generation and detection of surface acoustic waves (SAWs) using interdigital transducers (IDTs) on a piezoelectric surface have been used to produce many high performance Band Pass Filters. This thesis focuses on the design and simulation of various SAW Band Pass Filters. IDTs can be fabricated on many piezoelectric substrates. The effect of substrate properties – electromechanical coupling coefficient and SAW velocity, on filter frequency response is analyzed. The IDT design properties comprise film thickness ratio, metallization ratio, acoustic aperture, and number of finger pairs. The behavior of electrical equivalent circuit of an IDT that consists of impedance parameters – radiation conductance, radiation susceptance, and capacitance, is simulated and analyzed for different piezoelectric materials. Different IDT designs offer different propagation environment to SAWs. The IDT designs based on electrode spacing – uniform and non-uniform, direction of SAW propagation – bidirectional and unidirectional, acoustic aperture – apodized and unapodized, and electrode configuration – solid electrode and split electrode, are studied. The effect of IDT design on filter performance is assessed. The design of linear phase SAW filter using fourier transform, and effect of truncation on filter specifications – amplitude ripple, side lobe rejection ratio, insertion loss, and transition bandwidth is thoroughly depicted and analyzed. The cosine window function technique is used to improve filter performance. The second order effects – bulk wave interference, diffraction, impedance matching, electromagnetic feedthrough, triple transit interference, and harmonics that corrupt the filter performance are elaborated. The effect of metallization ratio on higher harmonic suppression is studied. Design of advanced SAW band pass filters – comb filters and resulting frequency response is also explored.

Heat conduction plays a key role and is linked to the underneath lattice structure. The heat transfer in soft matter materials like DNA and polymers is seldom understood and is deeply linked to the geometry and functional groups in the molecule. Also, probing thermal conduction in shorter length scales using computations gives us a fundamental understanding of the link between structure and phenomena with respect to heat transfer. DNA satisfies the low thermal conductivity requirements for building molecular thermoelectric devices. This was a motivation for this study. Using this motivation, this thesis investigates the thermal conductivity of B-DNA and other layered materials. The thermal conductivity of B-form double-stranded DNA (dsDNA) of the Drew-Dickerson sequence d(CGCGAATTCGCG) is computed using classical Molecular Dynamics (MD) simulations. In contrast to previous studies, which focus on a simplified 1-dimensional model or a coarse-grained model of DNA to reduce simulation times, full atomistic simulations are employed to understand the thermal conduction in B-DNA. Thermal conductivity at different temperatures from 100 to 400 K are investigated using the Einstein-Green-Kubo equilibrium and Müller-Plathe non-equilibrium formalisms. The thermal conductivity of B-DNA at room temperature is found to be 1.5 W/m·K in equilibrium and 1.225 W/m·K in non-equilibrium approach. In addition, the denaturation regime of B-DNA is obtained from the variation of thermal conductivity with temperature. It agrees with previous works using Peyrard-Bishop-Dauxois (PBD) model at a temperature of around 350 K. The quantum heat capacity (Cvq ) has given the additional clues regarding the Debye and denaturation temperature of 12-bp B-DNA. Also, the effect of changing base-pairs on the thermal conductivity of dsDNA, needed investigation at a molecular level. Hence, four sequences, viz. poly(A), poly(G), poly(CG) and poly(AT) were initially analysed in this work. Firstly, length of these sequences was varied from 4-40 base-pairs (bp) at 300 K and the respective thermal conductivity (κ) was computed. Secondly, the temperature dependent thermal conductivities between 100 K and 400 K were obtained in 50 K steps at 28 bp length. The Müller-Plathe reverse non-equilibrium molecular dynamics (RNEMD) was employed to set a thermal gradient and obtain all thermal conductivities in this work. Moreover, mixed sequences using AT and CG sequences, namely A(CG)nT (n=3-7), ACGC(AT)mGCGT (m=0-5) and ACGC(AT)nAGCGT (n=1-4) were investigated based on the hypothesis that these sequences could be better thermoelectrics. 1-dimensional lattices are said to have diverging thermal conductivities at longer lengths, which violate Fourier law. These follow power law, where κ ∝ Lβ . At longer lengths, the exponent β need to satisfythe condition β > 1/3 for divergent thermal conductivity. We find no such significant Fourier law violation through divergence of thermal conductivities at 80 bp lengths or 40 bp lengths. Also, in the case of second study, the presence of short (m ≤ 2) encapsulated AT sequences within CG sequences show an increasing has given the additional clues regarding the Debye and denaturation temperature of 12-bp B-DNA. Also, the effect of changing base-pairs on the thermal conductivity of dsDNA, needed investigation at a molecular level. Hence, four sequences, viz. poly(A), poly(G), poly(CG) and poly(AT) were initially analysed in this work. Firstly, length of these sequences was varied from 4-40 base-pairs (bp) at 300 K and the respective thermal conductivity (κ) was computed. Secondly, the temperature dependent thermal conductivities between 100 K and 400 K were obtained in 50 K steps at 28 bp length. The Müller-Plathe reverse non-equilibrium molecular dynamics (RNEMD) was employed to set a thermal gradient and obtain all thermal conductivities in this work. Moreover, mixed sequences using AT and CG sequences, namely A ( CG ) n T (n=3-7), ACGC ( AT ) m GCGT (m=0-5) and ACGC ( AT ) n AGCGT (n=1-4) were investigated based on the hypothesis that these sequences could be better thermoelectrics. 1-dimensional lattices are said to have diverging thermal conductivities at longer lengths, which violate Fourier law. These follow power law, where κ ∝ Lβ . At longer lengths, the exponent β need to satisfy the condition β > 13 for divergent thermal conductivity. We find no such significant Fourier law violation through divergence of thermal conductivities at 80 bp lengths or 40 bp lengths. Also, in the case of second study, the presence of short (m ≤ 2) encapsulated AT sequences within CG sequences show an increasing trend. These results are important for engineering DNA based thermal devices. DNA and layered materials are characterized by a stacking periodicity. Whilst in DNA, we have weakly interacting base pair stacking, in layered materials we have Van der Waals interactions . Anharmonicity is strong in both materials. The phonon dispersion of an atomic layer of h-BN and the heat capacity of MAX phase Ti3SiC2 nanolaminates are calculated using ground state density functional theory (DFT) calculations. trend. These results are important for engineering DNA based thermal devices. DNA and layered materials are characterized by a stacking periodicity. Whilst in DNA, we have weakly interacting base pair stacking, in layered materials we have Van der Waals interactions . Anharmonicity is strong in both materials. The phonon dispersion of an atomic layer of h-BN and the heat capacity of MAX phase Ti3SiC2 nanolaminates are calculated using ground state density functional theory (DFT) calculations.
Ministry of Education, Government of India

Search for clean and renewable energy resources has driven recent interest in designing thermoelectric materials that convert the waste heat to useful electricity. High performance thermoelectric materials require excellent electronic transport and favorable thermal transport, simultaneously. Given the interdependence of various transport parameters, it is daunting to achieve desirable performance. We attempt to address some of these challenges using density functional theory in combination with machine-learning based approaches. We first report the decoupling of Seebeck coefficient and electrical conductivity by tuning the distortion parameter of chalcopyrites leading to complete convergence of bands, thereby resulting in unprecedented enhancement of electronic transport properties. A combination of excellent electronic transport and low thermal conductivity in CdGeAs2 results into a high ZT of 1.67 at 1000K. To find a system with low thermal conductivity, we study the oxychalcogenide system AgBiTeO, demonstrating the unique collective rattling motion hosted by chemical bond hierarchy. The favorable electronic and thermal transport properties result in a maximum ZT of 1.99 at 1200K, which is highest among the existing bulk oxide-based thermoelectric materials. Owing to the complexity and resource extensive calculations involved in determining electron relaxation time (τel), we employed machine learning approach to estimate the τel. The machine learning model uses data available for experimental electrical conductivity and a collection of accessible elemental information. This model with a rmse of 0.22, outperforms the deformation potential model, and performs adequately on the unseen data to predict the relaxation time over a wide range of temperatures. Further, we develop an effective descriptor by using chalcopyrite class of compounds, to guide an accelerated screening of materials with desirable degree of anharmonicity. The high-throughput study corroborates the role of a very simple parameter, “phonon band center”. This can be calculated within the harmonic regime, yet having profound impact on the anharmonicity of the compounds. Since, the performance of thermoelectric devices is limited by the quality of the interface, we explore the role of fundamental parameters, such as surface termination of interface, electronegativity difference and lattice mismatch that influence the interface. Optimization of these parameters will have a significant role in preserving the thermoelectric performance of the materials in devices. The results of our study pave way to overcome some of the critical challenges related to thermoelectrics by effectively addressing electronic and thermal transport problems.

The discovery of LiFePO4 cathode for Li-ion battery ushered intensive study on polyanionic high-voltage battery insertion materials. Polyanionic materials offer rich crystal chemistry, robust framework, voltage tunability, and high redox potential based on the inductive effect due to the polyanionic unit [(XO4)mn-, X = S, P, Si, W, Mo, etc.] [1]. Among them, SO4-based polyanionic systems have the advantage of higher redox potential and ease/versatility of low temperature synthesis. In this spirit, I have investigated bisulfate [A2-xM(SO4)2: A= Li, Na, K; x= 0,1] and hydroxysulfate [AMSO4OH: A = Li] type sulfate-based polyanionic frameworks. Few salient features of my thesis work are: (i) Spray drying route was used to discover a metastable monoclinic polymorph of Li2NiII(SO4)2 (s.g. P21/c). As per first principle calculations, it can work as a 5.5 V (vs. Li+/Li) cathode for Li-ion battery coupling both cationic (Ni2+/Ni3+) and anionic (O-) redox activity. The crystal chemistry, phase stability landscape and the ground state magnetic structure (A-type Antiferromagnetic spin ordering) of this novel compound have been examined [2,3]. (ii) Mineralogical exploration and synthetic preparation of naturally found minerals are strategically used to unveil battery electrode materials. Following, saranchinaite Na2Cu(SO4)2 and its hydrated derivative kröhnkite Na2Cu(SO4)2.2H2O bisulfate minerals have been prepared using the facile spray drying synthesis route. The thermodynamic phase stability landscape has been explored along with the structural effects on the Na+ ion mobility. While the presence of Cu makes them unsuitable for insertion ion chemistry, they have been reported as potential conversion type battery electrodes [4]. (iii) The eldfellite NaVIII(SO4)2 (s.g. C2/m) is demonstrated as a versatile novel cathode material for both Li-ion (2.57 V, 80 mAh/g) and Na-ion (2.28 V, 70 mAh/g) battery at current rate of C/20 and based on solid solution reaction mechanism. (iv) Hydrothermally prepared orthorhombic polymorph of FeIIISO4OH (s.g. Pnma) has been examined as a 3.2 V (110 mAh/g, C/20) Li-ion battery cathode. I have further demonstrated the first reversible Na-ion (de)insertion in monoclinic FeIIISO4OH at ~2.9 V based on solid solution reaction mechanism with a discharge capacity of 85 mAh/g (C/100) [5,6]. Overall, this work can be suitably placed in the materials science tetrahedron encompassed by “structure-property-processing-performance”. I will elaborate the above-mentioned sulfate based polyanionic battery insertion materials.
Ministry of Human Resource Development

The past years have seen an increasing interest in high-efficient thermoelectric materials because of their promising application to harvest the widely distributed waste heat. Realizing high-efficient TE materials into actual devices remains a challenge. The suitability of thermoelectric material is judged by a dimensionless parameter called thermoelectric figure-of-merit, zT. The efficiency of a thermoelectric (TE) device depends on material parameters and, to a large extent, on joints/contacts these semiconducting materials form with metallic conductors for completing an electrical circuit. The maximum power output gets significantly reduced due to parasitic losses occurring at these metal-semiconductor junctions because of many interdependent factors. One of the critical factors is the chemical interaction of TE materials with the conducting connectors like Cu, Ag, or Al. The interaction of TE materials with these materials results in intermetallic phases that deteriorate the interface properties, leading to decreased bond strength and, in severe cases, mechanical detachment of the joints. Additionally, since these devices are intended to work at higher ranges of temperatures, unwarranted growth of phases formed during joining or during operation due to atomistic diffusion of elements significantly affects these joints' reliability. A diffusion barrier is inserted between the semiconductor and metal conduct/solder alloys to prevent this interaction. The diffusion barrier, which is in immediate contact with TE material, is called the contact material for that TE. PbTe is a state-of-the-art thermoelectric alloy for power generation in intermediate-temperature range applications (600-900K) whose maximum zT values have already reached 2.2-2.5. This thesis investigates the interaction between PbTe (TE material) and Ni (and its alloys) as contact material by conducting a structural and microstructural study of temperature-dependent phase evolution at diffusion bonded interfaces. The thesis is divided into seven chapters.

Infectious diseases caused by pathogenic bacteria are creating a global health problem. In the recent report of World Health Organization (WHO), it has been mentioned that around 7 lacks people are dying each year worldwide due to drug resistant microbials. After discovery of the lifesaving “wonder drug” molecule penicillin, it was extensively used for the treatment of bacterial infection diseases. However, the excessive use of antibiotics leads to the development of antimicrobial resistance in the pathogenic bacterial strains to overcome the bactericidal effect of antibiotics. The drug-resistance bacteria follow multiple pathways to show resistance towards the existing antimicrobial agents and eventually make them abortive. The prevalence of these drug resistant bacterial strains poses a serious threat to the present medical system. Therefore, there is an urgency to develop advanced antimicrobial agents which can restrict the spread of pathogenic bacteria to eradicate infectious diseases. In this context, the current advancement in the field of nanotechnology would help us to develop nanomaterial-based antimicrobial agents which could be one of the possible alternatives of conventionally used antibiotics. There are numerous reports, which established that nanomaterials such as graphene oxide, carbon nanotube, noble metal nanoparticles, metal oxides like ZnO2, MnO2 etc. have possessed antibacterial activity. In particular, the use of nanosized molybdenum disulfide (MoS2), a transition metal dichalcogenide showed a great potential to utilize for the development of potent antibacterial agents owing to its unique chemical and photophysical properties. Two-dimensional MoS2 nanosheets provide a large surface to volume ratio for the effective interaction with the bacterial cell membrane. For better biological interactions of MoS2 nanomaterials, its surface modification can be easily achieved through functionalization using thiol ligand molecule. Functionalization also enhances its aqueous dispersibility in manyfold. In this thesis work, I have utilized MoS2 nanomaterials and their nanocomposites to develop nanomaterial-based effective antimicrobial agents for the pathogenic bacterial strains using multiple strategies. To extend my work towards the development of nanomaterial-based antibacterial agents, I have explored antibacterial activity of the supramolecularly self-assembled nanosized cage molecule to eradicate drug-resistant bacteria. Apart from antibacterial activity, I have also expanded the scope of applicability of our newly developed nanomaterials in the direction of bio-analyte detection and environmental remediation such as degradation of organic pollutant and detoxification of the chemical warfare agent.

World health organization (WHO) has recognized multiple degenerative diseases as the leading causes of mortality, globally. The drugs-based clinical treatment of chronic degenerative diseases such as multiple sclerosis, Parkinson’s disease, osteoarthritis, muscular dystrophy, etc., has been accomplished with limited success. In this perspective, “stem cell-based regenerative engineering” provides a new treatment option to repair and regenerate the damaged tissue or organ. Stem cells have the unique capability to replicate themselves (self-renewal) unless they are provided with specific external factors (i.e., biochemical, and biophysical). Among various biophysical signals, the efficacy of electrical stimulation, substrate stiffness, and conductivity have been demonstrated to direct stem cell differentiation. In the present thesis, cellular differentiation has been regulated using biophysical signals on multifunctional biomaterials. The multifunctional biomaterials provide a ‘smart’ platform to deliver biophysical cues to direct stem cell differentiation. The electrical stimulation on conducting polymer (polyvinylidene difluoride, PVDF reinforced with multiwall carbon nanotubes) guided the stem cells towards neuron-like and glial-like cells. The strategy to differentiate stem cells towards functional neurons has future implications in stem cell therapy to treat neurodegenerative diseases. Also, the conducting polymeric biomaterials, developed in the present dissertation, can be further developed into an artificial nerve conduit and nerve patch to repair the damaged nerve tissues. To address the osteoarthritis-related clinical challenges, bone and cartilage mimicking polymer composites have been developed in this thesis. The electrical stimulation on a bone-mimicking polymeric platform (PVDF reinforced with Barium Titanate) induced the differentiation of stem cells towards bone-like cells. The continuous electrical signal generated higher stresses in stem cells, while the non-continuous alternative electrical signal exhibited differentiation without causing cellular stress. The bone-mimicking PVDF composite has the potential to be used as an acetabular liner in total-hip-joint replacement. The electrical stimulation technology can be translated to induce a faster bone healing with an upregulated ability of osseointegration of synthetic polymer implant. Furthermore, a novel hybrid bilayer composite with elastically stiff and compliant (soft) polymeric matrices has been fabricated to mimic the osteochondral tissue (interfacial tissue of bone and cartilage). The upregulated activity of bone cells on the elastically stiff layer and maturation of cartilage cells on the elastically compliant layer demonstrates the efficacy of the bilayer construct to repair the osteochondral defect. The modulated osteochondral functionalities on the elastically stiff and compliant substrate also revealed the role of substrate stiffness to direct cellular differentiation. Taken together, the present thesis conclusively establishes the efficacy of external biophysical signals to direct cellular differentiation using multifunctional biomaterial platforms for neural and osteochondral regeneration.

Breath based Diagnostics (BbD) can enable a paradigm shift in the Point-of-Care Diagnostic (PoCD) devices. Exhaled human breath has been demonstrated to contain over 2000 volatile organic and inorganic compounds, some of which report marked change in concentration under diseases conditions. A sensitive, selective, cost effective and portable gas sensing system could thus non-invasively diagnose multiple diseases from a single breath sample. However, there is a need to develop highly sensitive gas sensors with very low limit of detection (LLoD) down to ppb to ppt and high selectivity to meet this requirement. This thesis focuses on developing such gas sensors based on novel 2D nanomaterials and their hybrids while using a simple, scalable synthesis route. This is in contrast to the conventional choice of sensing materials (Metal Oxides, polymers, CNT’s etc.) and expensive fabrication methods. Here, we explored layered materials namely Transition Metal Dichalcogenides (TMDC) and Layered Transition metal oxides (TMO) and their hybrids for the detection of Ammonia (NH3), Hydrogen Sulphide (H2S) and Nitrogen Dioxide (NO2), three important constituents of exhaled breath. The synthesis of these layered materials was carried out at room temperature via the liquid phase exfoliation (LPE) technique using low boiling point solvents. This technique is attractive because it is simple, scalable and does not require sophisticated instrumentation. The key findings from this work can be summarized as follows. Layered Transition metal oxide (TMO) namely 2D MoO3 based devices demonstrated reasonable response to NH3 at room temperature but only down to 300 ppb which was not sufficient for our intended application. Further, we observed that the layered TMD’s WS2, WSe2 and its hybrid with Fe3O4 demonstrate remarkable ammonia sensing. WS2 demonstrated high sensitivity towards NH3 (detection down to 50 ppb) with fair selectivity but at an elevated operating temperature of 250oC. On the other hand, WSe2/fe3O4 hybrid-based devices demonstrated enhanced sensitivity and selectivity towards ammonia, that too at room temperature, with a 50 ppb LLoD. Another notable observation was the similar response of pristine WSe2 nanosheets towards NO2 as NH3. Hence, we enhanced the NO2 sensing performance of WSe2 based sensors by functionalizing their surface with noble metals such as Au and Pt using a simple wet chemical route. Interestingly, we obtained highly sensitive (down to 100 ppb) and selective response towards NO2 at room temperature. More importantly, the complete recovery to the original baseline without any external energy source was remarkable since it is known to be challenging. While exploring other inorganic TMO’s, we observed that 2D V2O5 based devices detect H2S non-selectively at 350oC and down to only 500 ppb. Further improvement in H2S sensing is helped by TMD’s again as we modified the surface of WS2 in such a manner that it suppressed NH3 sensing, by using low temperature microwave irradiation assisted synthesis technique. Thus, it demonstrated highly selective, sensitive, and prompt H2S detection, though at an elevated temperature of 250oC. Later, we observed that a novel material of this same class (1T-TiS2) could provide similar attributes at room temperature. This material was not investigated before for gas sensing; hence we conducted a theoretical study and presented a plausible mechanism based on vdW interaction, substantiating physisorption between adsorbate and adsorbent. Thus, this thesis investigates novel materials, hybrids, and methods for scalable production of ultrasensitive, selective, stable, and low-cost sensors for NH3, H2S and NO2, which can potentially find applications for field-usable breath-based diagnostics in the future
MHRD, DEITY, DST Nanomission through NNeTRA

Airway pathology leads to alteration in fluid flow, tissue biomechanics, and loss of patency. To address this clinical challenge, we developed an intraoperative tool to locate the site of obstruction, characterize tracheal tissue stiffness, and quantify the lumen diameter. To quantify the three parameters, flows sensors, force sensors, and unfurling compliant actuator evolved. The small size, fast response, and low power consumption of Microelectromechanical system (MEMS) sensors for medical diagnostics and biointerface engineering make them an optimal choice for integrating with healthcare monitoring tools. MEMS sensors allow miniaturization, batch fabrication, conformal mounting on catheters, guidewires, and endoscopes. This work comprehends all phases involved in the tool development, from the fabrication of microengineered sensors to integrating on flexible printed circuit board (FPCB) and further validating its utility in a pseudo-physiological test bench using excised sheep tracheal tissues.

Understanding the principles and applications of crowd dynamics in mass gatherings is very important, specifically with respect to crowd risk analysis and crowd safety. Historical trends from India and other countries suggest that the crowd crushes in mass gatherings, especially in religious events, frequently occur, highlighting the importance of studying crowd behaviour more scientifically. This is required to support appropriate and timely crowd management principles in planning crowd control measures and providing early warning systems at mass gatherings. Hitherto, the researchers have studied the previous incidents of crowd crushes from the viewpoint of high density and the resulting physical forces and poor geometric facilities, but the factors such as psychological triggers and weather are overlooked. Further, although the average number of victims per panic event seems to decrease, their total number increases with the frequency of mass religious gatherings. Unless proper measures are in place, this trend will continue. Therefore, a comprehensive risk assessment is required to assess the potentially risky situations associated with an event that can lead to crowd crushes. To manage large crowds, an understanding of crowd dynamics is required to reasonably predict the level of risk and implement appropriate crowd management measures. However, there is a lack of empirical studies with real-world data on crowd behaviour and dynamics. Therefore, deriving motivation from the given background, the objectives of this research are: (1) to conduct a detailed empirical data collection in a mass religious gathering in an uncontrolled setup, (2) to understand the fundamental relationships between speed, flow, and density across different sections of case study, (3) to analyse the potentially risky situations observed in the site, and (4) to develop a comprehensive crowd risk model concerning crowd movement in mass religious gatherings and arrive at a Crowd Risk Index (CRI) which can give a range of values on scale defining the possibilities of crowd risks in a given area of mass religious gathering. The case study considered was Kumbh Mela 2016, held in Ujjain, India, between 22 April and 21 May. It attracted an estimated population of 75 million with an interesting mix of domestic and international pilgrims, spiritual leaders, and holy men, who journeyed to Ujjain from short duration (one day) to long-term stay (throughout the event). The key attractions of Kumbh were (1) taking a dip in the river Kshipra and (2) visiting temples. Data was collected throughout the event, covering the important days on which the crowd was expected to be more. Data in video form was recorded using Go-Pro, head-mount cameras, mobile phones and CCTV cameras. Additionally, data was also collected using GPS trackers and survey forms. Further, quantitative data was collected through visual observations. The Crowd Risk Index was developed from three pillars of indices: Crowd Dynamic Index (CDI), Crowd Anxiety Index (CAI), and Temperature-Humidity Index (THI). CDI include (i) macroscopic fundamental flow diagrams of a spiritually motivated crowd (ii) characteristics of stop and go waves in one-dimensional interrupted pedestrian flow through narrow channels (iii) understanding social group behaviour in the crowd and the effect of the presence of groups on the crowd movement, and (iv) understanding serpentine group behaviour and its impact on crowd dynamics. Using the above-mentioned study observations, the CDI was developed for ghat and temple locations as they were the two key attractions of Kumbh Mela. All the variables were used both for ghat and temple model. About 53 expert opinions were gathered separately for the temple and ghat videos. The experts rated the risk levels from the video clippings as low, medium, or high. Low was taken as class 1, medium as class 2, and high as class 3, which was given as an input to the CDI. The dataset was imbalanced, and so the SMOTE-Tomek Link method was used to balance out the dataset. Cross Validation technique using the Random Forest algorithm was used to predict the level of risk for CDI. CAI included the patience and aggression scores obtained from the study conducted on understanding the crowd’s emotions. A Structural Equation Modelling (SEM) was performed, and hypotheses testing were done to verify the relationship between the first order (cue-dependence (CD), tolerance (TO) and goal-oriented (GO); norm violation (NV), obstruction to movement (DO) and social display of power (SP)) and second-order factors (patience and aggression). All the first-order factors under patience and aggression were found to have a direct and significant impact on the second-order factors, i.e., patience and aggression, respectively. The patience and aggressions scores were obtained from the path loadings. Moreover, the effect of high temperature can have an indirect impact on the CRI through increasing aggression. This was also included in the index. The dataset here was also imbalanced, and so the SMOTE-Tomek Link method was used to balance out the dataset. The same Cross Validation technique using the Random Forest algorithm was used to predict the level of risk for CAI. A value between 0 and 1is class 1 (low), a value between 1 and 2 is class 2 (medium), and a value between 2 and 3 is class 3 (high). THI from literature was used to gauge the effect of temperature on the crowd risk. Kumbh Mela 2016 was held during peak summer under the scorching heat. The average temperature across the event duration was above 91-degree Fahrenheit, which implies that the event happened under severe stress conditions. This indicates the importance of including temperature effects into the model, especially for events that happen under high-temperature conditions. The comfort zone values were considered as class 1 (low), mild and severe stress conditions are combined as class 2 (medium), and severe stress conditions as class 3 (high). The CAI, CDI, and THI together form the CRI. The relative importance of these indices was also gathered from the same 53 experts. The weights were then calculated using the AHP process. Then the final CRI prediction equation was formulated. A CRI value between 0 and 1 indicates low risk, a value between 1 and 2 indicates medium risk, and a value between 2 and 3 indicates high risk. This can help in predicting the level of risk in a given area for every one-minute interval. Therefore, the CRI developed includes factors such as crowd anxiety and temperature, other than the crowd dynamics and behaviours, as it is important to include a comprehensive set of factors for a better prediction. With an overarching understanding of the factors leading to critical crowd conditions, the CRI developed in this work can help reasonably predict the level of risk and implement appropriate crowd management measures. However, the approach used in the study has its own set of limitations. There are other important factors that could endanger crowd safety, including bottleneck movement and crowd turbulence, among others, which are not considered. Studying and incorporating these into the CRI can result in a more accurate model. Adding health-related aspects and studying other psychological aspects supplemented with video data can also improve the model's precision. In addition, a comparison of different machine learning techniques to assess their performance could be a follow-up to this research. Despite these limitations, the study proposes a novel methodology for predicting crowd risk in mass religious gatherings. This is a one-of-a-kind study in crowd disaster and crowd safety that has never been attempted before in the literature.

High-efficiency power cycles for concentrating solar power (CSP) technology such as air or supercritical carbon-dioxide (s-CO2) based Brayton cycle require high-pressure high-temperature conditions at the gas turbine inlet. This requires heating of the heat transfer fluid (HTF) to those conditions (~3-35 bar, 900-1600 K for air and ~200 bar, 1000 K for s-CO2) using a solar thermal receiver. Thus, the design and analysis of the pressurized receiver system form an important part towards the development of such solarized power plants. A coupled optical and thermal model is developed for analyzing a cavity-based pressurized receiver, with dynamic variation of solar radiation input. The optical part involves the focal region flux characterization of a fixed-focus Scheffler reflector that provides a spatially resolved heat flux to the receiver cavity surface. This is achieved using a combination of on-sun experiments and ray-tracing simulation. On the other hand, the transience in heat input to the receiver is captured by curve-fitting the measured DNI variation with time corresponding to the experimental testing period. This spatially and temporally varying heat flux is coupled to the thermal analysis of the receiver to predict the flow field and the enthalpy gain by the heat transfer fluid (HTF) along with the thermal losses from the receiver cavity. This numerical model is subsequently validated with on-sun experimental testing of a hybrid tubular and cavity receiver using a 32 m2 Scheffler dish for heat input and compressed air at 20 bar as the HTF. The numerical and experimental results are found to be in good agreement under comparable conditions, thus proving the effectiveness of the coupled optical and thermal model. To account for the transient nature of the receiver heating during the on-sun experiments, the receiver efficiency definition is modified to include the thermal inertia of the receiver material. It is observed that natural convection is the dominant heat loss mechanism that significantly reduces the overall thermal efficiency of the receiver. In the context of cavity receivers, the rate of heat transfer to the pressurized HTF is limited by the forced convection mode. For the enhancement of heat transfer in such systems, a passive method using metallic wire meshes in the HTF flow path is explored. Firstly, a pore-scale analysis is performed on the inline stacked wire mesh geometry for determining the hydraulic and thermal characteristics of the medium. The heat transfer taking place between the wire struts and the airstream at the local level is captured by thermal analysis on a representative elementary volume (REV) defined for this mesh geometry. This yields an interstitial Nusselt number for capturing the local heat transfer between the two phases. Subsequently, a homogeneous equivalent porous medium is defined using the properties obtained from the pore-scale analysis. For modelling the heat transfer within the two phases, the local thermal non-equilibrium (LTNE) model is implemented using the obtained Nusselt number correlation. The numerical model is subsequently validated with laboratory-scale experiments performed on a channel stacked with wire mesh layers and thermal load provided using an electric heater. The model prediction shows good agreement with the experimental results. However, the LTNE effect is not that pronounced under the present thermal conditions. Among the storage options available for such applications, sensible heat storage using ceramic material with honeycomb structure having gas flow passages has been used for the present study, because of its cost advantage and stability at high temperatures and pressures. To enhance the performance of such systems, the effect of block arrangement is analysed with respect to the rate of charging and discharging. Towards this end, two configurations are explored for the same storage material volume; a bigger cross-sectional area system with smaller HTF flow length and a smaller cross-sectional area system with a longer flow length. These systems are thermally cycled between 443 K and 300 K using compressed air at 10 bar pressure. Analytical and numerical models are developed that are validated using laboratory experiments, and the results are in good agreement with both the modelling approaches. This study reveals that the block arrangement that allows for higher flow velocity through the honeycomb channels of the ceramic block charges and discharges the system at ~1.5 times faster than the other configuration with slower air stream velocity under identical thermal conditions.

In the pursuit of interactive electronic devices, there is a need for smart materials which can serve multiple functionalities. 2D (two-dimensional) layered materials have gained attention in semiconductor technology because of their versatile electrical and optical properties. Furthermore, some materials exhibit piezoelectricity at 2D scale and can withstand enormous strain. These properties make them suitable as smart materials involving electromechanical signals. In the literature, materials which are semiconducting and piezoelectric are termed piezotronic (piezo+electronic) materials. Theoretical studies have indicated many materials as piezoelectric in 2D form. However, experimental tools to investigate the extent of piezoelectric coupling in 2D materials are limited, and their relevance for piezotronics has not been studied in detail. This dissertation presents some key aspects of 2D Piezotronics for improved performance and to achieve additional functionalities with heterojunctions. The work constitutes proposing a technique to estimate piezoelectric coupling coefficients, choice of flexible substrates for piezotronics, methods to reduce the charge screening effects, measurement strategies to extract the actual piezoelectric output from the bending measurements, and the study of heterojunctions for rectifying behaviour. In this work, Molybdenum disulfide (MoS2) is used as active piezoelectric material. In the initial part of the work, I propose a technique to estimate in-plane piezoelectric coupling quantitatively for 2D materials. The method involves a novel approach for in-plane field excitation in lateral Piezo force microscopy (PFM). Contact resonance gain of the tip-sample system is leveraged to measure the piezoelectric coupling coefficients in a few pm/V to sub pm/V range. However, I have shown that operating PFM at contact resonance can cause pseudo piezoelectric signals. Therefore, a detailed methodology for signal calibration and electrostatic background subtraction is developed in this work. The technique is verified by estimating the in-plane piezoelectric coupling coefficients (d11) for freely suspended MoS2 of one to five atomic layers. The technique presented is useful in estimating the piezoelectric coupling strengths in emerging 2D materials. Piezotronic devices are made on flexible substrates for practical applications. Fabrication on flexible substrates often poses great difficulties in handling them, depositing inorganic materials, and carrying out lithography processes. I propose the commercially available nano flex film as a prospective substrate for piezotronics. Carrying out fabrication on these substrates is as seamless as that on rigid substrates. Substrates such as PET, Nano flex and TPU can be used for low-temperature (<150 deg C) applications. Kapton is one of the flexible substrates that can handle higher temperatures(>200 deg C). However, they tend to twist when heated, making the fabrication difficult. I have proposed a gel-based bonding for the Kapton substrates wherein the debonding process is automatic. The method is helpful for the fabrication of 2D material devices on Kapton. Besides selecting the substrates, suitable base layers and passivation techniques are studied to reduce the charge screening effects and thus improve the performance of piezotronic devices. It is verified that open circuit voltages and strain gauge factors obtained for the current monolayer MoS2 device on SiO2 are three folds higher than those presented in the literature. A simple measurement setup which does not require probe needles or wire bonding is developed for the bending strain measurements. The open circuit voltage and short circuit current signals obtained from a single 2D material device are very small. The noise signals that originate from various triboelectric and electrostatic sources of the measurement setup can be of similar magnitude. Consequently, the electrical outputs from these devices during bending measurements are often misinterpreted. Thus, it is essential to analyse various noise sources in bending measurements. I then discuss ways to reduce the background noise and identify the valid piezoelectric output. Finally, I have studied some homogeneous and heterogeneous junctions of MoS2 to achieve good rectifying junction behaviour, which can add extra functionalities for piezotronics. The rectification ratio values as high as 5000 could be achieved at 1 V bias. Besides the rectifying ratio, I have observed that the heterojunctions of MoS2 and MoTe2 have superior piezoelectric behaviour compared to other 2D material junctions reported so far with open circuit voltages as high as ~1 V and peak power density of ~200 mW/m2 at 0.44% bending strain. Formation of the p-n and Schottky junction hybrid in MoS2-MoTe2 heterojunction could achieve high rectification ratios and open circuit voltages and is fascinating for further study.

Two-dimensional (2D) materials have revolutionized the field of materials science since the successful exfoliation of graphene in 2004. Consequently, the advances in computational science have resulted in massive generic databases for 2D materials, where the structure and the basic properties are predicted using density functional theory (DFT). However, discovering material for a given application from these vast databases is a challenging feat. In this thesis, we have developed various automated high-throughput computational pipelines combining DFT and machine learning (ML) to assess the suitability of 2D materials for specific applications. Methods have also been developed to draw valuable insights into what makes these materials suitable for these applications. The assessed properties include suitability for energy storage in the form of Li-ion battery (LIB) and supercapacitor electrodes, along with high-temperature ferromagnetism and the presence of exotic charge density waves (CDW). The ultra-large surface-to-mass ratio of 2D materials has made them an ideal choice for electrodes of compact LIBs and supercapacitors. We combine explicit-ion and implicit-solvent formalisms to develop high-throughput pipelines and define four descriptors to map “computationally soft” single-Li-ion adsorption to “computationally hard” multiple-Li-ion-adsorbed configuration located at global minima for insight finding and rapid screening. Leveraging this large dataset, we also develop crystal-graph-based ML models for the accelerated discovery of potential candidates. A reactivity test with commercial electrolytes is further performed for wet experiments. Our unique approach, which predicts both Li-ion storage and supercapacitive properties and hence identifies various important electrode materials common to both devices, may pave the way for next-generation energy storage systems. Although there are numerous studies computationally exploring 2D materials as Li-ion battery electrodes, these studies are mostly material-specific, i.e., only a few materials are explored in each of these studies. In our work, however, using the novel descriptor-based technique, we explore thousands of 2D materials for LIB electrode applications. Moreover, to the best of our knowledge, no study has explored these thousands of 2D materials for supercapacitor electrodes yet, which we also achieve. The discovery of 2D ferromagnets with high Curie temperature is challenging since its calculation involves a manually intensive complex process. We develop a Metropolis Monte-Carlo-based pipeline and conduct a high-throughput scan of 786 materials from a database to discover 26 materials with a Curie point beyond 400 K. For rapid data mining, we further use these results to develop an end-to-end ML model with generalized chemical features through an exhaustive search of the model space as well as the hyperparameters. We discover a few more high Curie point materials from different sources using this data-driven model. CDW materials are an important subclass of two-dimensional materials exhibiting significant resistivity switching with the application of external energy. We combine a first-principles-based structure-searching technique and unsupervised machine learning to develop a high-throughput pipeline, which identifies CDW phases from a unit cell with an inherited Kohn anomaly. The proposed methodology not only rediscovers the known CDW phases but also predicts a host of easily exfoliable CDW materials (30 materials and 114 phases) along with associated electronic structures. Apart from these, we have also investigated Li-ion storage in distorted rhenium disulfide crystal, polymorphism-driven Li-ion storage of monoelemental 2D materials, and cation intercalation-driven reversible magnetism in ferrous dioxide using global-energy-minima search technique. Our findings could provide useful guidelines for future experimental efforts. All the data, ML models, and computer codes are available freely for community usage. We stress that the automated methodologies/workflows developed in this thesis are as important as the results obtained and generalized enough to be applicable to any 2D materials. The available 2D materials databases are ever-growing, and the workflows introduced by us can aid in the discovery of even better application-specific 2D materials in the future.
Indian Institute of Science and Ministry of Education, Government of India