Design,Development and Testing of Nb-Ti Superconducting Magnet & Creation of Liquid Helium Test Facility

Research in the area of advanced materials for various applications is the demand of time. Discovery of nano technology, high Tc superconductivity and multi functional materials are just few of them. For proper understanding of the underlying physics, Low temperature investigations on these materials are very much needed. If magnetic field is added to low temperature,sometimes new insights are witnessed e.g., superconductivity, quantum Hall effect etc. Intense efforts are going on around the world to make simple and inexpensive superconducting magnet systems for performing variable temperature experiments on the above materials under high magnetic fields. Keeping in view of these facts, a lab scale mobile superconducting magnet system is designed and developed in house using Nb- Ti wire (0.43 mm nominal diameter, Cu:SC Ratio of 2:1) and tested for production of 6 Tesla field and repeated quenching of the coil. The thesis describes the step-by-step procedure involved in winding and testing of the superconducting magnet. Further, a simple commercially available Liquid Helium transport dewar is suitably modified for magnet insertion with necessary instrumentation for liquid helium transfer port, hall field-probe, LHe level indicator, temperature and field sensors, power supply and vapor cooled current leads etc. The magnet is tested in a commercially available cryostat, available at VECC Kolkata. In a parallel effort, the present thesis also describes the setting up of Liquid Helium production and magnet testing facility along with necessary vacuum and electrical instrumentation. The out come of the present thesis is expected to accelerate the growth of Cryogenic/Vacuum/Applied Superconductivity research at NIT Rourkela

Monitoring the low doping regime in graphene using Raman 2D peak-splits: Comparison of gated Raman and transport measurements

Avoiding charge density fluctuations and impurities in graphene is vital for high-quality graphene-based devices. Traditional characterization methods require device fabrication and electrical transport measurements, which are labor-intensive and time-consuming. Existing optical methods using Raman spectroscopy only work for doping levels higher than ~10^12 cm^-2. Here, we propose an optical method using Raman 2D peak-splitting (split between the Raman 2D1 and 2D2 peaks at low doping levels). Electrostatically gated Raman measurements combined with transport measurements were used to correlate the 2D peak-split with the charge density on graphene with high precision (2x10^10 cm^-2 per 2D peak-split wavenumber). We found that the Raman 2D peak-split has a strong correlation with the charge density at low doping levels, and that a lower charge density results in a larger 2D peak-split. Our work provides a simple and non-invasive optical method to quantify the doping level of graphene from 10^10 cm^-2 to 10^12 cm^-2, two orders of magnitude higher precision than previously reported optical methods. This method provides a platform for estimating the doping level and quality of graphene before fabricating graphene deviceshttps://arxiv.org/abs/1908.10961First author draf

On constructing correct and scalable iBGP configurations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 51-53).BGP (Border Gateway Protocol), the Internet's current inter-domain routing protocol, has two modes of operation: eBGP (external BGP, used to exchange routing information between autonomous systems (ASes)), and iBGP (internal BGP, used to propagate that information about external destinations to other BGP routers within an AS). Full-mesh iBGP and iBGP with route reflection are the two most common methods of configuring iBGP. Although a full-mesh iBGP guarantees correct and predictable routing, it requires a large number of iBGP sessions-approximately quadratic in the number of BGP routers. Such configurations do not scale well in the number of BGP routers in the AS because of the memory, bandwidth and CPU overhead involved in exchanging routes over a large number of iBGP sessions at each router. Hence configurations based on route reflectors are commonly used for intra-AS route dissemination in large ASes. However, researchers have found that configuring route reflectors in an unprincipled fashion can result in routing anomalies like forwarding loops and sub-optimal paths. Although previous work on iBGP configuration correctness gives sufficient conditions to check if a given iBGP configuration is correct, the problem of constructing correct and scalable iBGP configurations using route reflection has not received much attention.(cont.) This thesis proposes and analyzes the first (to our knowledge) algorithm to construct iBGP session configurations that are both correct and more scalable than a full-mesh iBGP. Our algorithm, BGPSep, uses the notion of a graph separator--a small set of nodes whose removal partitions a graph into connected components of roughly equal sizes--to choose route reflectors and iBGP sessions in a way that guarantees correctness. We evaluate an implementation of the BGPSep algorithm on several real-world network topologies and find that iBGP configurations generated by BGPSep have between 2.5 to 5 times fewer iBGP sessions than a full-mesh.by Mythili Vutukuru.S.M

Investigation of dual varying area flapping actuator of a robotic fish with energy recovery

Autonomous under-water vehicles (AUV) performing a commanded task require to utilize on-board energy sources. At the time when on-board power source runs low during operation, the vehicle (AUV) is forced to abort the mission and to return to a charging station. The present work proposes the technique of an energy recovery from surrounding medium. This effect is studied for dual action actuator movement that obtains energy from fluid. It is realized that a flapping or vibrating actuator can be used for energy extraction phenomenon apart from the non-traditional propulsive technique. In the present work a simple dual flapping actuator that can switch between simple flat plate and perforated plate at extreme end positions (angles) by using an efficient mechatronic mechanism that would help in overcoming viscous forces of the operating medium is extensively studied. The main objective of the present article is to develop a new approach for energy gain and recharge power pack of on-board sources from the surrounding medium and to create a robotic fish that would work autonomously by using unconventional drive along with the possibility of energy restoration by using dual varying area type vibrating actuator. At the time of recharge, the robotic fish would project its tail (actuator) out of water and use surrounding medium (air) to scavenge the energy. All the equations describing the process are formed according to classical laws of mechanics. The mechatronic system is explained and the results obtained are discussed in detail for air as the operating fluid to scavenge energy

Cross-layer wireless bit rate adaptation

This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the physical layer and exported to higher layers via the SoftPHY interface to estimate the prevailing channel bit error rate (BER). Senders use this BER estimate, calculated over each received packet (even when the packet has no bit errors), to pick good bit rates. SoftRate's novel BER computation works across different wireless environments and hardware without requiring any retraining. SoftRate also uses abrupt changes in the BER estimate to identify interference, enabling it to reduce the bit rate only in response to channel errors caused by attenuation or fading. Our experiments conducted using a software radio prototype show that SoftRate achieves 2X higher throughput than popular frame-level protocols such as SampleRate and RRAA. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4X higher throughput than an untrained SNR-based protocol. The throughput gains using SoftRate stem from its ability to react to channel variations within a single packet-time and its robustness to collision losses.National Science Foundation (U.S.) (Grant CNS-0721702)National Science Foundation (U.S.) (Grant CNS-0520032)Foxconn International Holdings Ltd

Network Intrusion Detection Method Using Stacked BILSTM Elastic Regression Classifier with Aquila Optimizer Algorithm for Internet of Things (IoT)

Globally, over the past ten years, computer networks and Internet of Things (IoT) networks have grown significantly due to the increasing amount of data that has been collected, ranging from zettabytes to petabytes. As a result, as the network has expanded, security problems have also emerged. The large data sets involved in these types of attacks can make detection difficult. The developing networks are being used for a multitude of sophisticated purposes, such as smart homes, cities, grids, gadgets, and objects, as well as e-commerce, e-banking, and e-government. As a result of the development of numerous intrusion detection systems (IDS), computer networks are now protected from security and privacy threats. Data confidentiality, integrity, and availability will suffer if IDS prevention efforts fail. Complex attacks can't be handled by traditional methods.  There has been a growing interest in advanced deep learning techniques for detecting intrusions and identifying abnormal behavior in networks. This research aims to propose a novel network namely stacked BiLSTM elastic regression classifier (Stack_BiLSTM-ERC) with Aquila optimizer algorithm for feature selection. This optimization method computes use of a cutting-edge transition function that enables it to be transformed into a binary form of the Aquila optimizer. A better solution could be secured once number of possible solutions are found from diverse regions of the search space utilizing the Aquila optimizer method. NSL-KDD and UNSW-NB15 are two datasets that enable learning characteristics from the raw data in order to detect harmful prerequisites characteristics and effective framework patterns. The proposed Stack_BiLSTM-ERC achieves 98.l3% of accuracy, 95.1% of precision, 94.3% of recall and 95.4 of F1-score for NSL-KDD dataset. Moreover, 98.6% of accuracy, 97.2% of precision, 98.5 of recall and 97.5% of F1-score

Analysis of non-stationary flow interaction with simple form objects

ArticleThe paper is devoted to the analysis of a non-stationary rigid body interaction in a fluid flow. Initially, an approximate method for determining the forces due to fluid interaction with the rigid body is offered. For this purpose, the plane movement of a mechanical system with an infinite DOF (degrees of freedom) is reduced to 5 DOF motion: 3 DOF for the body and 2 DOF for the areas of compression and vacuum in fluid flow. Differential equations of non-stationary motion are formed by the laws of classical mechanics. The use of an approximate method has been quantified by computer modelling. The average difference in results was found to be small (< 5%). The analysis of the fluid (air) interaction is carried out for a rigid body of two simple geometries - flat plate and diamond. The results obtained are used to refine the parameters of the proposed approximate method that is addressed in the present study for fluid interaction with the non-stationary rigid body. Theoretical results obtained in the final section are used in the analysis of the movement of prismatic bodies in order to obtain energy from the fluid flow

Straining the flatland: novel physics from strain engineering of atomically thin graphene and molybdenum disulfide

2D materials like graphene and MoS_2 are atomically thin, extremely strong and flexible, making them attractive for integration into strain engineered devices. Strain on these materials can change physical properties, as well as induce exotic physics, not typically seen in solid-state systems. Here, we probe the novel physics arising from distorted lattices of 2D materials, strained by nanopillars indentation and microelectromechanical systems (MEMS), using Raman and photoluminescence (PL) spectroscopy. From nanopillars strained multilayer MoS_2, we observe exciton and charge carrier funneling due to strain, inducing dissociation of excitons in to free electron-hole pairs in the indirect material. Using MEMS devices, we were able to dynamically strain monolayer and multilayer graphene. Multilayer graphene under MEMS strain showed signatures of loss in Bernal stacking due to shear of the individual layers, indicating that MEMS can be used to tune the layer commensuration with tensile strain. We further explore simulation of pseudo-magnetic fields (PMFs) generated in monolayer graphene strained by MEMS, using machine learning, to accelerate and optimize the strength and uniformity of the PMF in new graphene geometries. Nanopillars provide non-uniform, centrally biaxial strain to multilayer MoS_2 transferred on top. Raman E^1_2g and PL redshift across the pillar confirms 1-2% strain in the material. We also observe a softening in the A_1g Raman mode and an enhancement in the overall PL with an increase in radiative trions, under strain. The changes in these charge-dependent features indicates funneling of charge carriers and neutral excitons to the apex of the pillar, as strain locally deforms the band structure of the conduction and valence bands. DFT calculations of the band structure in bilayer MoS_2 under biaxial strain shows the conduction band is lowered, further increasing the indirectness of multilayer MoS_2. This should cause the PL intensity to decrease, whereas we observe an increase in MoS_2 PL intensity under strain. We theorize that this is due to a dissociation of excitons into free electron-hole pairs. The increase in charge carrier densities due to strain leads to a renormalization of the local band structure and increased dielectric screening, supporting free electron-hole recombination at the K-point without momentum restrictions. In turn, electron-hole recombination occurs around the K-point inducing a high intensity PL, which opens attractive opportunities for utilization in optoelectronic devices. MEMS chevron actuators can dynamically strain 2D materials, which we demonstrate through uniaxial strain in CVD and exfoliated graphene. We use a novel microstructure assisted transfer technique which can deterministically place materials on non-planar surfaces like MEMS devices. Building on previously reported 1.3% in monolayer MoS2 from our group, we report tunable 0.3% strain in CVD monolayer graphene and 1.2% strain in multilayer exfoliated graphene using MEMS chevron actuators, detected by Raman spectroscopy. The asymmetric-to-symmetric strain evolution of the 2D phonon line shape in multilayer graphene is evidence of changes in interlayer interactions, caused by shearing between layers. This demonstrates that MEMS can be used to tune the commensuration in few layer 2D materials, which is a promising avenue towards Moiré engineering. Using machine learning, we also simulate optimal monolayer graphene geometries for generating strong, uniform pseudo-magnetic fields by MEMS strain. The coupled use of finite-element methods, variational auto-encoder, and auxiliary neural network accelerates the search for PMFs in strained graphene, while optimizing the graphene shape for fabrication through electron-beam lithography. Our experimental and simulated work creates a road-map for rapid advancement in zero-field quantum Hall effect devices using graphene-integrated MEMS actuators

Monolayer MoS2 strained to 1.3% with a microelectromechanical system

We report on a modified transfer technique for atomically thin materials integrated onto microelectromechanical systems (MEMS) for studying strain physics and creating strain-based devices. Our method tolerates the non-planar structures and fragility of MEMS, while still providing precise positioning and crack free transfer of flakes. Further, our method used the transfer polymer to anchor the 2D crystal to the MEMS, which reduces the fabrication time, increases the yield, and allowed us to exploit the strong mechanical coupling between 2D crystal and polymer to strain the atomically thin system. We successfully strained single atomic layers of molybdenum disulfide (MoS2) with MEMS devices for the first time and achieved greater than 1.3% strain, marking a major milestone for incorporating 2D materials with MEMS We used the established strain response of MoS2 Raman and Photoluminescence spectra to deduce the strain in our crystals and provide a consistency check. We found good comparison between our experiment and literature.Published versio