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Investigation of strongly correlated paramagnetic state at sub-Kelvin regime for S ≥ 1/2 systems: Role of disorder and dimensionality
No full textA magnetic system usually orders ferro- or anti-ferromagnetically at temperatures
comparable to interaction strength between the spins. Moreover, an interacting
spin system tends to order with the increase of dimensionality of the magnetic lattice,
as determined by the spin-spin correlation along various directions. However, there
are certain lattice types where such orderings are strongly suppressed. A prototypical
example is the Ising spin-1/2 on a triangular lattice with a nearest neighbour antiferromagnetic
interaction where the triangular arrangement results in competing interactions
leading to a large number of distinct states with the same ground state energy
and therefore magnetic frustration. When frustration extends over a long range, it
can lead to the formation of highly degenerate ground states with spin fluctuations at
absolute zero temperature, leading to exotic magnetic ground states such as Quantum
Spin Liquid (QSL). In recent times, there is an increasing interest in such magnetically
frustrated systems, in search of QSLs which relieve the frustration by entangling
the spins instead of ordering. Another approach to achieve a ground state without ordering
is to introduce sufficient magnetic disorder in a lattice. Such systems may get
stuck in a differently disordered “glassy” state. In this thesis work, we explore what
happens when extensive disorder is in the frustrated triangular lattice such that conditions
that promote spin liquid coexist with those aiding glassiness. The thesis will
present in detail such dynamic correlated paramagnetic states in a few selected materials.
These systems differ, not only in their chemical compositions and the nature of
the magnetic ions, but also in terms of the dimensionality of the magnetic interactions
and the extent of disorder.
Using combined experimental and theoretical approaches,
detailed investigations have been carried out on a series of magnetic materials,
varying the extent of disorder, dimensionality of magnetic interactions, and the
magnetic spin moments, at the sub-Kelvin temperature regime, revealing several unexpected
behaviours
A Context-Aware Neural Approach for Explainable Citation Link Prediction
No full textCitations have become an integral part of scientific publications. They play a crucial role in supporting authors’ claims throughout a scientific paper. However, citing related work is a challenging and laborious task, especially for novice researchers who are not much familiar with the literature and have little or no experience in writing citation text. In this work, we study the task of Citation Link Prediction and propose a novel neural architecture called ExCite, that predicts the existence of a citation link between a pair of scientific documents within a given context. More importantly, it also generates the corresponding citation text at the same time. For this purpose, ExCite leverages diverse role-based views of the documents to learn robust document representations. The proposed model achieves state-of-the-art performance on both citation link prediction and citation text generation subtasks. We performed an extensive set of experiments to show the effectiveness of each module in the proposed neural architecture and evaluated our explanations using a wide range of state-of-the-art automatic evaluation metrics. By performing qualitative and quantitative analyses, we showed that ExCite is capable of generating high-quality citation text that is highly coherent with the citation context
An Investigation of the Characteristics of Monsoon Low Pressure Systems in the Present Climate and their Sensitivity to Topography and Climate Change
No full textMonsoon Low-Pressure Systems (LPS) are synoptic-scale tropical disturbances that periodically form over the Indian subcontinent during the summer monsoon season (June-September). Apart from being a lifeline to agriculture, the LPS-triggered precipitation could cause catastrophic floods. This thesis investigates the large-scale factors that influence LPS characteristics under the current and future climate change scenarios. In the early part of the thesis, a new approach is developed to track the formation and propagation of LPS over the Indian subcontinent. A detailed statistical and visual comparison is made between LPS tracks generated using our approach applied to ERA-Interim reanalysis data and tracks obtained in previous studies. Furthermore, extreme rainfall at locations in the vicinity of LPS is analyzed which could be valuable for flood risk assessment during the monsoon season in central India.
In the latter part of the thesis, a fully coupled version of the Community Earth System Model (CESM 1.2.2) is run at 0.9°×1.25° spatial resolution, and 6-hourly output is generated for track analysis. The model’s ability to simulate the characteristics of LPS is first assessed by performing a present-day control simulation. Simulations to study the sensitivity of LPS statistics to topographical features in the south Asian region (presence or absence of southeast Asian mountains and the height of Tibetan and Himalayan Orography (THO)) and the change in LPS characteristics under climate change are also performed. Simulations without the southeast Asian mountains enable determining the influence of these mountains on the downstream amplified systems (remnants of Pacific tropical cyclones) over the Bay of Bengal. The sensitivity analysis on the influence of the height of THO shows an interesting result: while a decrease in monsoon precipitation with a reduction in the height of THO is simulated, the number of LPS increases. A detailed analysis of the dynamic factors leading to this counter-intuitive result is performed. Finally, the change in LPS characteristics and the associated large-scale SST and circulation anomalies in the Indian Ocean and south Asian region are assessed for the RCP8.5 emissions scenario. It is found that the monsoon circulation is weakened, summer monsoon precipitation over India is enhanced, and the number of LPS remains nearly unchanged in a warmer world
Van der Waals Heterojunctions for Emerging Device Applications
No full textLow-dimensional systems are an exciting platform for exploring new physics and realizing novel devices. The intriguing features, such as the existence of strongly bound multiparticle complexes and thickness-dependent band structures, enable us to utilize them to overcome many challenges faced by bulk materials and conceive new technologies. Since the isolation of graphene, the class of two-dimensional materials has grown tremendously. The array of materials one can choose from for implementing an idea is vast. Nevertheless, understanding the underlying physics is essential for utilizing these properties for real-life applications. Here, we explore the optical, electrical, and optoelectrical characteristics of heterostructures based on 2D layered systems.
The strongly bound excitonic complexes hosted by monolayer transition metal dichalcogenide semiconductors (TMDC) are an excellent platform for probing many-body physics. The strong luminescence and a plethora of exciting properties make them a good candidate for applications such as single photon emitters and light-emitting diodes. In the first work, we explore new ways to tune the emission from these particles without compromising their luminescence. Using a high-quality graphene/hBN/WS2/hBN/Au vertical heterojunction, we demonstrate for the first time an out-of-plane electric field-driven change in the sign of the Stark shift from blue to red for four different excitonic species, namely, the neutral exciton, the charged exciton (trion), the charged biexciton, and the defect-bound exciton. We also find that the encapsulating environment of the monolayer TMDC plays a vital role in wave function spreading and hence in determining the magnitude of the blue Stark shift. We also provide a theoretical framework to understand the underlying physics better. The findings have important implications in probing many-body interaction in the two dimensions and developing layered semiconductor-based tunable optoelectronic devices.
A significant advantage of the 2D material system is its robustness against lattice mismatch between the successive layers and the ability to extract exciting characteristics from the resultant system. The final system's behavior greatly depends on how the energy bands of the individual materials line up and can result in drastically different properties. In the second work, we demonstrate how an additional ultra-thin barrier layer modifies the properties of a black phosphorus (BP)/SnSe2 tunnel diode. While the system without the barrier layer showed a linear relationship between current and voltage, the additional barrier layer modified it to a highly nonlinear relation and exhibited negative differential resistance (NDR). Moreover, the tunnel diodes exhibited highly repeatable, ultra-clean, and gate tunable NDR characteristics with a signature of intrinsic oscillation and a large peak-to-valley current ratio (PVCR) of 3.6 at 300 K (4.6 at 7 K), making them suitable for practical applications. We then show that the thermodynamic stability of the van der Waals (vdW) tunnel diode circuit can be tuned from astability to bistability by altering the constraint by choosing a voltage or a current bias, respectively. After exploring the dynamics of the device, we assess its viability for designing systems with real-life applications. In the astable mode under voltage bias, we demonstrate a compact, voltage-controlled oscillator without needing an external tank circuit. In the bistable mode under current bias, we demonstrate a highly scalable, single element, a one-bit memory cell promising for dense random access memory applications in memory-intensive computation architectures.
In the third work, we explore the usage of vdW materials for generating a cryptographically secure true random number generator. Such generators rely on external entropy sources for their indeterminism. Physical processes governed by the laws of quantum mechanics are excellent sources of entropy available in nature. However, extracting enough entropy from such systems for generating truly random sequences is challenging while maintaining the feasibility of the extraction procedure for real-world applications. Here, we design a compact and an all-electronic vdW heterostructure-based device capable of detecting discrete charge fluctuations for extracting entropy from physical processes and use it for the generation of independent and identically distributed (IID) true random sequences. Using the proposed scheme, we extract a record high value (> 0.98 bits/bit) of min-entropy. We demonstrate an entropy generation rate tunable over multiple orders of magnitude and show the persistence of the underlying physical process for temperatures ranging from cryogenic to ambient conditions. We verify the random nature of the generated sequences using tests such as the NIST SP 800-90B standard and other statistical measures and verify the suitability of our random sequence for cryptographic applications using the NIST SP 800-22 standard. The generated random sequences are then used to implement various randomized algorithms in real life without preconditioning steps.
We then investigate how knowledge of the dynamics of optically generated carriers, ability to sense discrete charge fluctuation, and transport of carriers across vdW heterostructure can be combined to design a comprehensive system to detect single photons. Single-photon detectors (SPDs) are crucial in applications ranging from space and biological imaging to quantum communication and information processing. The SPDs operating at room temperature are particularly interesting to broader application spaces as the energy overhead introduced by cryogenic cooling can be avoided. Although silicon-based single photon avalanche diodes (SPADs) are well matured and operate at room temperature, the bandgap limitation restricts their operation at telecommunication wavelength (1550 nm) and beyond. On the other hand, InGaAs-based SPADs are sensitive to 1550 nm photons but suffer from relatively lower efficiency, high dark count rate, afterpulsing probability, and pose hazards to the environment from the fabrication process. By coupling a low bandgap (~350 meV) absorber (black phosphorus) to a sensitive van der Waals probe capable of detecting discrete electron fluctuation, we demonstrate a room-temperature single-photon detector. While the device is capable of covering up to a wavelength of ~3.5 um, we optimize the device for operation at 1550 nm and demonstrate an overall quantum efficiency of 21.4% (estimated as 42.8% for polarized light) and a minimum dark count of ~720 Hz at room temperature
Local Projection Stabilization Methods for the Oseen Problem
No full textFinite element approximation of fluid flow problems with dominant convection exhibit spurious oscillations. To eliminate these nonphysical oscillations one needs to incorporate stabilizations that can curb the effect of convection. The main aim of this thesis is to design and analyse local projection stabilization based finite element schemes for the Oseen problem.
In chapter \ref{intro}, we have established a background for the Oseen problem citing its main difficulties and a literature survey. In the thesis, we have predominantly discussed the use of three different finite elements methods, namely, the non-conforming Crouzeix-Raviart () method, the H(\Hdiv;\Omega) conforming Raviart-Thomas () element method and the hybrid high order method. The thesis is divided into four chapters.
Chapter \ref{chap1} analyses the edge patchwise local projection (EPLP) stabilized nonconforming finite element methods for the Oseen problem. For approximating the velocity, the lowest-order Crouzeix-Raviart (CR) nonconforming finite element space is considered, whereas for approximating the pressure, two separate discrete spaces are considered, namely, the piecewise constant polynomial space and the lowest-order CR finite element space. The proposed discrete weak formulations are a combination of the standard Galerkin method, EPLP stabilization and weakly imposed boundary condition (Nitsche's technique). We present stability results for both schemes and provide convergence analysis.
{\it A~posteriori} error analysis of the edge patch-wise local projection (EPLP) stabilized Crouzeix-Raviart finite element method is developed in chapter \ref{chap2}. The {\it a~posteriori} analysis is based on the approach of Verf\"urth \cite{verfurth_dual_main}. We prove a stability result for the Oseen equation under a dual norm. The stability result gives an equivalence of error and residual which is independent of the discrete formulation. This gives the freedom of using other stabilizations and finite element spaces in the setting of our analysis. Equivalence of error and residual is exploited to formulate an error estimator which is proven to be reliable. Efficiency estimates show a dependence on the diffusion coefficient.
In chapter \ref{chap3}, we define a Local projection stabilization (LPS) scheme with the Raviart-Thomas( ) elements for the oseen problem. We show that a divergence free, pressure robust LPS scheme can be designed with elements of order . We also show that stability under the streamline upwind Petrov-Galerkin (SUPG) norm can be achieved if the space is enriched with tangential bubbles. The enriched scheme also gives divergence free velocity. We present {\it a~priori} error estimates for both the schemes.
Chapter \ref{chap4} deals with the use of a local projection stabilized Hybrid High-Order scheme for the Oseen problem. We prove an existence-uniqueness result under a SUPG like norm. We derive an optimal order {\it a~priori} error estimate under this norm for equal order polynomial discretization of velocity and pressure spaces.
In the last chapter we provide some concluding remarks on the results proved in the thesis and discuss some future problems to work on
Accelerating Estimation of Perfusion Maps in Contrast X-ray Computed Tomography using Many-core CPUs and GPUs
No full textX-ray Computed Tomography (CT) perfusion imaging is a non-invasive medical imaging modality that has been established as a fast and economical method for diagnosing cerebrovascular diseases such as acute ischemia, sub-arachnoid hemorrhage, and vasospasm. Current CT perfusion imaging being dynamic in nature, requires three-dimensional data acquisition at multiple time points, resulting in a long time for processing ranging from six to twelve minutes post acquisition. In emergency medical conditions such as stroke, every second is crucial for obtaining the perfusion maps, which are used for deploying brain-saving therapies. Since time is of the utmost importance, this thesis work attempts to develop strategies for computationally accelerating the processing of the CT perfusion data to provide perfusion maps using many-core CPUs and GPUs.
Current major steps involved in perfusion maps estimation from CT perfusion data involve estimation of Arterial Input Function (AIF), followed by model-based deconvolution of AIF from tissue enhancement curves pixel-by-pixel to assess the cerebral blood flow (CBF) accurately. The deconvolution of the AIF is embarrassingly parallel and current methodologies do not account for this process to be accelerated using high performance computing environments. Specifically, this thesis utilises the multiple CPU cores that are available in current computing environments as well as General Purpose Graphics Processing Units (GP-GPUs) to provide massively parallel computing power to parallelise the deconvolution process at the pixel level. The GPUs are attractive for this application as they are built on the SIMD (Single Instruction Multiple Data) architecture. Though there are multiple ways of solving the ill-posed inverse problem of deconvolution for obtaining high-quality perfusion maps, this thesis work focuses on the Circulant Truncated-SVD based method, which was implemented using the Nvidia CUDA API that Nvidia provides for its GPUs.
Further, this thesis work explores the algorithms that work for single-AIF deconvolution, which, though not very accurate, is a very good first approximation for time-critical cases to know the area of damage. These experiments were followed by the exploration of multiple-AIF deconvolution, which, although slow, is the gold standard for brain perfusion imaging. These algorithms were developed using the KBLAS library which utilizes multiple CPU and GPU cores. A detailed computational analysis through use cases reveals that GP-GPU computing is a viable option for accelerating the X-ray CT perfusion imaging and are attractive in clinic due to the footprint of these GPU machines
Investigations on Increasing Linear Modulation Range in Hybrid Multilevel Inverter Fed Induction Machine Drives Regardless of Load Power Factor
No full textNowadays, multilevel inverters (MLIs) have become a promising alternative to the twolevel inverter in medium voltage high-power applications such as motor drives, active power filters,
HVDC, electric vehicles, wind, and solar power generation. In the high-speed motor drives domain,
the motor speed reaches above the base speed region. The motor runs in the flux-weakening zone
above the designed base speed using either an open-loop variable frequency variable voltage
algorithm or a closed-loop field-oriented control algorithm. But, the maximum torque production
capability of the motor decreases substantially while it runs in the field-weakening zone. To increase
the maximum torque of the motor drive, the peak phase fundamental needs to be raised by enhancing
the DC-link utilisation of the inverter. The only possible way to increase DC bus utilisation for any
hexagonal Space Vector Structured (SVS) VSI is to operate the inverter in six-step mode. However, in
the six-step mode, the inverter yields square wave output voltages comprised of undesirable lower
order harmonics such as 5th,7th,11th and 13th etc., which causes low frequency torque ripple. The
low frequency torque ripple (such as 6th and 12th etc.) may eventually cause a breakdown of the
motor shaft at a higher speed, reducing the lifespan of the motor.
In the work of the thesis, the issues mentioned earlier are addressed so that the modulation range
can be increased linearly without the presence of lower order harmonics irrespective of load power
factor (p.f). In the first work, a hybrid nine level T-type inverter topology with extended DC bus
utilisation is proposed. An increase in the DC bus utilisation is possible by increasing the pole voltage
levels to ±(Vdc/2 + Vdc/8) using the H-bridge capacitor voltage during 11 level mode, and it is achieved
by adding an offset to sine reference. This offset is added so that all the capacitor voltages remain
regulated in the 11-level mode of operation. The aforementioned offset added PWM strategy
increases the peak phase fundamental voltage from 0.577Vdc to 0.625Vdc in the case of unity p.f load
and 0.6366Vdc for 0.82 p.f load with the proposed nine level inverter. The proposed inverter scheme
and its claim of increasing the peak phase fundamental voltage is experimentally validated in a
laboratory prototype. The second work presents a 10-level dual inverter scheme to extend the linear
modulation range (LMR) by using a unique space vector pulse width modulation (SVPWM) technique.
The 10-level inverter structure is formed using a 2-level inverter and an H-bridge (HB) in cascade from
one end and a floating capacitor-based 2-level inverter cascaded with an H-bridge from the other end
to drive an open-end winding induction motor (OEWIM). This proposed circuit structure yields a 9-
level SVS that can be further extended to a unique 10-level SVS by subtracting or adding the HB
capacitors voltages. All the HB capacitor voltages are balanced by using SV redundancy, where for
every vector points, there exists a pair of the opposite vector from HBs and secondary 2-level. The
claim of balancing the capacitor voltages throughout the whole modulation range is varied
experimentally in this paper. The third work presents a hybrid seven level dual inverter scheme with
increased LMR. The hybrid inverter structure is formed by supplying the load from the primary side
using a cascaded structure of a two-level inverter and H-bridge. A floating capacitor supplies the
secondary side of the load fed two-level inverter. The combination of primary two level SVS with
secondary two level SVS and primary three level SVS of HB form a seven level SVS that can further be
extended to an eight level hexagonal SVS. This structure was then reduced to a 12-sided 8-level SVS
to avoid exceeding motor phase voltage rating. Subsequently, using this eight level SVS in a unique
PWM mode, the proposed topology can increase the modulation range linearly from 0.577Vdc to
0.6366Vdc peak phase fundamental voltage for any load p.f. To balance HB capacitors voltages in this
work, a concept of indirect SV redundancy is used. The efficacy of the proposed inverter scheme is
verified through various experimental results at different steady state and transient condition
Wide Area Measurement Based Cyber-Attack Resilient Breaker Failure Protection Scheme
No full textBreaker Failure Protection(BFP) is a backup protection that comes into action when the primary protection schemes are unable to clear the fault. In power systems, every component has a redundant version to avoid failures. Substations duplicate Current Transformers(CTs), Voltage Transformers(VTs), Protective Relays, and DC power supplies to avoid failures. However, duplicating a circuit breaker is expensive. So, the BFP is introduced to avoid circuit breaker duplication. Nowadays, BFP is incorporated in microprocessor-based multi-functional relays. When the designated zone breaker does not clear the fault, the BFP scheme commands the backup breakers to open. The BFP operation leads to the disconnection of a larger area, causing a significant loss of load. Thus, a false BFP operation may lead to major disturbances in the power system. Hence, BFP becomes an attractive target for cyber-attacks.
Currently, there is a lack of literature addressing cyber-attack on the BFP scheme. Hence, the thesis proposes a novel Cyber-Attack Resilient BFP scheme employing Wide-Area Measurements. Modern microprocessor-based relays have Phasor Measurement Unit(PMU) capability in them. BFP relay-PMU will trigger the proposed algorithm running at the Phasor Data Concentrator(PDC). Relay-PMUs at each substation will send phasors to the PDC. There are two parts of the novel proposed algorithm. Part 1 is the Synchrophasor-based Fault Validation Algorithm(SFVA). The purpose of SFVA is to check whether the BFI issued to the BFP relay is genuine or a cyber-attack. Part 2 is the modification in the logic of the existing BFP scheme to incorporate the decision of SFVA in the BFP scheme output. A novel concept named Dynamic Relay-Whitelisting(DRW) is proposed to avoid measurements from the susceptible relay-PMUs to participate in the SFVA. When a relay-PMU of a particular relay-PMU family is attacked, there is an increased susceptibility to other relay-PMUs belonging to the same family. Thus, measurements participating in the SFVA shall be from relay-PMUs of different make and relay-PMU families. It is called Dynamic Relay-Whitelisting. The proposed algorithm is compatible with all commonly implemented BFP schemes.
Usually, a power system fault causes positive-sequence under-voltage at the adjacent substation buses from the fault location. Thus, under-voltage at a bus indicates a fault in the vicinity of that bus. SFVA has two layers. Layer-1 detects a fault in the vicinity of the BFP relay-PMU by implementing a voting scheme on the synchrophasors from the adjacent substation buses to check whether they observe positive-sequence under-voltage. Layer-1 is called Fault Detection Algorithm(FDA). Layer-2 confirms whether the power-system fault is within the zone of the relay that issued the BFI. Layer-2 confirms the fault location by estimating the fault distance observed by the adjacent buses from the perceived location of the fault. Layer-2 is called Fault Confirmation Algorithm(FCA).
The proposed algorithm is computationally efficient because it utilizes only a voting scheme and fault distance estimation.
The scope of the thesis is to detect multiple cyber-attacks during normal operation and block BFP scheme operation. Moreover, it also detects multiple cyber-attacks executed simultaneously with a power system fault and block BFP scheme operation. PSCAD software simulations on the IEEE-118 bus system validate the proposed algorithm. A lab implementation is developed to emulate a part of the IEEE-118 bus system's synchrophasor communication. Lab implementation confirms that the execution time of the proposed algorithm adheres to the timing budget of the BFP scheme
Supramolecular Self-assembly of Diketopyrrolopyrrole with Emergent Photophysics and Unprecedented Photoconductivity
No full textStructural fluctuation in organic molecular semiconductors often plays a key role in fragmenting the conducting pathways even in their condensed phases due to the large fraction of free volumes, acting as trap sites for free charge carriers. Long-range ordering via non-covalent directional interactions between the monomeric unit in organic semiconductors is an excellent approach to reduce trap densities.
To address this problem, we have rationally designed a series of Hamilton-receptor-based supramolecules of DPP. The Hamilton receptor endows supramolecular polymerization via hydrogen bonding with enhanced structural ordering and excitonic couplings. Owing to their synthetic tunability, high stability, strong visible absorption, high fluorescent quantum yield, and reasonable charge carrier mobility, DPP based π-conjugated systems have potential applications in the field of molecular optoelectronic devices such as organic field-effect transistors (OFETs), Organic solar-cell devices (OPVs).
In the light of the foregoing, in this thesis, efforts are made to investigate new synthesized DPP-based supramolecular self-assembly and their emergent photophysics and unprecedented photoconductivity. Initially, the detailed mechanism of supramolecular polymers via self-complementary intermolecular hydrogen bonding (-NH…O=C-) of Hamilton receptor is established by FT-IR, concentration-dependent, and diffusion order spectroscopy (DOSY) NMR studies. Further, the reversible nature of the self-assembly is established from the variable temperature-dependent NMR studies. The presence of a slipped stack arrangement between two DPP units and self-complementary intermolecular hydrogen bonding through amide moiety of Hamilton receptor is clearly elucidated from the single-crystal X-ray diffraction structure of HR-TDPP-C20.
Further, a flash photolysis time-resolved microwave conductivity study reveals unprecedented photoconductivity and charge carrier mobility in the thin film. Substituting different side-chains and introducing dihedral angle twists within the backbone observed a notable difference in solid-state packing, photoconductivity, and thin film morphology. Grazing incidence wide-angle X-ray scattering (GIWAXS) and thin film X-ray diffraction measurements reveal that the packing order is enhanced for hexyl substituted DPP derivatives, resulting in high intrinsic charge carrier mobility of ∑μ=1.7 cm^2 V^(-1) s^(-1): unprecedented one as 1-dimensional supramolecular architecture with such small conjugated cores. At the microscopic level, electron and atomic force microscopy show the unique self-assembly remarkably improves structural order via hydrogen bonding. These findings demonstrate that supramolecular self-assembly strategy via the present hydrogen bonding networks effectively reduces the structural defects in molecular semiconductors and further improves the performance of optoelectronic devices.
Subsequently, the excited state dynamics of DPP-based supramolecular self-assembly is investigated by using transient absorption spectroscopy (TA). We obtain two markedly different aggregate coupling motifs (J and H-like) for HR-TDPP-TEG in thin film, simply through the choice of solvent used in the deposition. Focusing on a characteristic 1(TT) photoinduced absorption band in the near-infrared, which is uncontaminated by thermal effects. The resulting 1(TT) state is capable of symmetry-forbidden luminescence – a first among DPP materials. The low-lying excimer-like state below the exciton-coupled S1 acts as a trap that hinders singlet fission in H-like film, highlighting the importance of intermolecular packing structures to manipulate the excited-state relaxation pathways.
Finally, we perceive that the DPP-based supramolecular systems selectively recognize the barbituric acid (among Dopamine, Serotonin, and Uric acid) via six self-complementary hydrogen bonds. Upon mixing barbituric acid with DPP-based supramolecular polymers (HR-TDPP-C20 and HR-TDPP-HEX) form nano-rods microstructure, which might have a potential application in the field of biomolecular sensors
Quasi-Static and Implicit-Dynamic Finite Element Solution of Large Deformation Elastic Adhesive Contacts Using a Volumetric Interaction Scheme
No full textAdhesive forces, mediated by van der Waals’ and other interactions, dominate the contact response in the micron and sub-micron regimes. Understanding adhesion is especially important in biological systems (interaction of cells with pathogens, bio-locomotion, and drug delivery), mechanical systems (nano-indentation), and Micro-Electro-Mechanical Systems (MEMS), among many others. Classical adhesive contact models like the JKR, DMT, and Maugis’ models apply in the small-deformation regime for regular bodies. Despite attempts by Shull, Lin, and others, enabling large deformation and arbitrary shapes is infeasible in such semi-analytical schemes, necessitating the use of finite element analysis (FEA).
Existing FE models use volume-to-volume (V2V), surface-to-surface (S2S), point to volume (P2V) or point to surface (P2S) interactions. S2S (e.g. Fan et al.) are computationally efficient but are not accurate enough to simulate strong adhesion in soft bodies due to inherent approximations. In these paradigms, a well-known FE scheme is the Coarse-Grained-Contact-Model (CGCM) developed by Sauer and co-workers. While CGCM is quite general, it uses a modification of the classical continuum, which is complicated to implement. More importantly, adhesion involves inherent ‘jump-to’ and ‘jump-off’ instabilities, which have not received adequate attention in the existing simulation literature. Moreover, these instabilities are more pronounced in soft materials, and necessitate new supporting algorithms and computational approaches for successful simulation. Lastly, for applications, it is important for solvers to demonstrate the ability to simulate adhesive systems with realistic material and interaction parameters.
In the present work, a V2V, interaction-based, continuum FE model is developed for large deformation plane strain adhesive contacts, with all interacting bodies considered to be elastic. A tree-based, ultra-fine, structured mesh generator is developed to accurately model interactions while reducing the associated computational expense. A k-d tree based algorithm is implemented to compute the interactions, reducing the computational cost. Both quasi-static and implicit dynamic solvers are developed. The quasi-static solver uses a custom path-following algorithm which can tackle ‘jump-to’ and ‘jump-off’ instabilities for a wide range of problems. The dynamic solver provides an alternative solution strategy to resolve only the stable branches of the solution curve and is especially useful for soft materials with strong adhesion.
The solutions obtained by the quasi-static solver and the dynamic solver in the low-velocity limit show good agreement, except, obviously, in the snap-back zone. In the past, dynamics solvers for adhesive problems (Johnson et al.; Jayadeep et al.) have typically focused on the impact ('unforced') regime rather than on the constant-velocity ('forced') regime, which is often more important in applications.
Some studies were carried out to validate various aspects of these solvers, including checks on the accuracy of interaction force calculations, mesh convergence behavior, and various limiting cases. Several model applications were considered to study and test these solvers, including cylinders and elliptical cylinders interacting with half-spaces, and a multi-body problem involving two cylinders and a half-space. Apart from the load-displacement and load-gap curves, a complete set of sub-surface strain fields and transmitted contact tractions is presented. The temporal evolution of the pressure peaks near the edges of contact is clearly revealed, flipping from tensile to compressive as the bodies approach each other very closely. The simulations show that tensile peaks always occur near the 'edge of contact' even in a highly repulsion-dominated regime. The solvers developed in the present work are expected to be useful to explore a spectrum of adhesive contact problems that arise in applications