COHERENT/INCOHERENT MAGNETIZATION DYNAMICS OF NANOMAGNETIC DEVICES FOR ULTRA-LOW ENERGY COMPUTING

Nanomagnetic computing devices are inherently nonvolatile and show unique transfer characteristics while their switching energy requirements are on par, if not better than state of the art CMOS based devices. These characteristics make them very attractive for both Boolean and non-Boolean computing applications. Among different strategies employed to switch nanomagnetic computing devices e.g. magnetic field, spin transfer torque, spin orbit torque etc., strain induced switching has been shown to be among the most energy efficient. Strain switched nanomagnetic devices are also amenable for non-Boolean computing applications. Such strain mediated magnetization switching, termed here as “Straintronics”, is implemented by switching the magnetization of the magnetic layer of a magnetostrictive-piezoelectric nanoscale heterostructure by applying an electric field in the underlying piezoelectric layer. The modes of “straintronic” switching: coherent vs. incoherent switching of spins can affect device performance such as speed, energy dissipation and switching error in such devices. There was relatively little research performed on understanding the switching mechanism (coherent vs. incoherent) in xiv straintronic devices and their adaptation for non-Boolean computing, both of which have been studied in this thesis. Detailed studies of the effects of nanomagnet geometry and size on the coherence of the switching process and ultimately device performance of such strain switched nanomagnetic devices have been performed. These studies also contributed in optimizing designs for low energy, low dynamic error operation of straintronic logic devices and identified avenues for further research. A Novel non-Boolean “straintronic” computing device (Ternary Content Addressable Memory, abbreviated as TCAM) has been proposed and evaluated through numerical simulations. This device showed significant improvement over existing CMOS device based TCAM implementation in terms of scaling, energy-delay product, operational simplicity etc. The experimental part of this thesis answered a very fundamental question in strain induced magnetization rotation. Specifically, this experiment studied the variation in magnetization orientation for strain induced magnetization rotation along the thickness of a magnetostrictive thin film using polarized neutron reflectometry and demonstrated non-uniform magnetization rotation along the thickness of the sample. Additional experimental work was performed to lay the groundwork for ultra-low voltage straintronic switching demonstration. Preliminary sample fabrication and characterization that can potentially lead to low voltage (~10-100 mV) operation and local clocking of such devices has been performed

Image Processing with Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

Hardware based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a two-dimensional periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost

Image Processing With Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

Hardware-based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a 2-D periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks, such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost

State of knowledge on emergency response and crisis management: evidence of sample secondary students of Bangladesh

In the era of late modernity, individual vulnerability is affected by various threats and risks. Consequently, people need to be aware of these and fit in more than ever before. To help people become competent in this changing world and to prepare for future threats, academic institutions play a vital role. To understand such an academic role, a part of the literature has highlighted how a student can better learn emergency responses (ER) and crisis management (CM). Nevertheless, very little literature has focused on how a developing country’s students, particularly teenagers, learn and understand ER and CM. Focusing on such gaps in the literature, this study aims to understand a sample of Bangladeshi secondary students’ state of knowledge related to ER and CM. With the help of cluster sampling, the researcher distributed a survey among a sample of 360 students between 9th and 12th standard from two southern districts respectively Khulna and Noakhali, which are also disaster-prone areas of Bangladesh. Adopting Krathwohl’s model of knowledge typology, such as factual knowledge, conceptual knowledge, procedural knowledge, and metacognitive knowledge, the researcher collected and evaluated the data with descriptive statistics. The findings of this study show that even though most of the students are familiar with different ER- and CM-related keywords, they have limited deeper knowledge. Furthermore, there was a significant knowledge difference between the genders. Similarly, the lack of training in the academic environment also makes these young students vulnerable to any kind of threat from their surroundings that could affect the districts’ weak institutional and legislative structure. The scholarship of this study, which has policymakers and young academics as its possible audience, could assist them in raising the knowledge levels of students by adding new information to textbooks with illustrations and by setting up drills

Development of cluster-based energy management scheme for residential usages in the smart grid community

Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy sources (RESs), energy storage systems (ESS), and optimal energy allocation strategies are used to resolve these difficulties. In this paper, the development of a cluster-based energy management scheme for residential consumers of a smart grid community is proposed to reduce energy use and monetary cost. Normally, residential consumers deal with household appliances with various operating time slots depending on consumer preferences. A simulator is designed and developed using C++ software to resolve the residential consumer’s REM problem. The benefits of the RESs, ESS, and optimal energy allocation techniques are analyzed by taking in account three different scenarios. Extensive case studies are carried out to validate the effectiveness of the proposed cluster-based energy management scheme. It is demonstrated that the proposed method can save energy and costs up to 45% and 56% compared to the existing methods. © 2020 by the authors. Licensee MDPI, Basel, Switzerland