Skip directly to content

Coming dissertations at TekNat

  • On the System Optimization of Magnetic Circuit with Alternative Permanent Magnets and its Demagnetization

    Author: Jonathan Sjölund
    Publication date: 2021-05-11 08:58

    Permanent magnet (PM) machines are often associated with the usage of rare earth magnets, due to their high energy density. One such rare earth magnet is the neodymium-iron-boron (NdFeB), which is mainly produced in China. Due to the global scarcity of the rare earth magnets, much interest is put into utilizing other permanent magnet materials. Among those materials is the category of ferrite permanent magnets, known for having lower magnetic properties than NdFeB. Ferrites share some of the properties with NdFeB that makes simulations simpler, namely that they have, at least, partly linear behavior in the demagnetization curve. The lower coercive properties of ferrites can, however, force them more easily into the non-linear regions of the demagnetization curves, resulting in a gradual irreversible demagnetization that lowers the performance of the ferrites. 

    In this thesis, the magnetic circuits of electrical machines with ferrites are investigated. The implications of the reduced coercive properties are studied and means to account for the irreversible demagnetization when designing the magnetic circuit. An optimization methodology for the magnetic circuit in a linear...

  • Silicon Nanowire Based Electronic Devices for Sensing Applications

    Author: Qitao Hu
    Publication date: 2021-05-10 13:42

    Silicon nanowire (SiNW) based electronic devices fabricated with a complementary metal-oxide-semiconductor (CMOS) compatible process have wide-range and promising applications in sensing area. These SiNW sensors own high sensitivity, low-cost mass production possibility, and high integration density. In this thesis, we design and fabricate SiNW electronic devices with the CMOS-compatible process on silicon-on-insulator (SOI) substrates and explore their applications for ion sensing and quantum sensing. 

    The thesis starts with ion sensing using SiNW field-effect transistors (SiNWFETs). The specific interaction between a sensing layer and analyte generates a change of local charge density and electrical potential, which can effectively modulate the conductance of SiNW channel. Multiplexed detection of molecular (MB+) and elemental (Na+) ions is demonstrated using a SiNWFET array, which is functionalized with ionophore-incorporated mixed-matrix membranes (MMMs). As a follow-up, polyethylene glycol (PEG) doping strategy is explored to suppress interference from the hydrophobic molecular ion and expand the multiplexed detection range. Then, the SiNW is downscaled to sub-10 nm...

  • Chekanov-Eliashberg dg-algebras and partially wrapped Floer cohomology

    Author: Johan Asplund
    Publication date: 2021-05-06 08:52

    This thesis consists of an introduction and two research papers in the fields of symplectic and contact geometry. The focus of the thesis is on Floer theory and symplectic field theory.

    In Paper I we show that the partially wrapped Floer cohomology of a cotangent fiber stopped by the unit conormal of a submanifold, is equivalent to chains of based loops on the complement of the submanifold in the base. For codimension two knots in the n-sphere we show that there is a relationship between the wrapped Floer cohomology algebra of the fiber and the Alexander invariant of the knot. This allows us to exhibit codimension two knots with infinite cyclic knot group such that the union of the unit conormal of the knot and the boundary of a cotangent fiber is not Legendrian isotopic to the union of the unit conormal of the unknot union the boundary and the same cotangent fiber.

    In Paper II we study the Chekanov-Eliashberg dg-algebra which is a holomorphic curve invariant associated to a smooth Legendrian submanifold. We extend this definition to singular Legendrians. Using the new definition we formulate and prove a surgery formula relating the wrapped Floer cohomology algebra...

  • Robust Platforms for Superconductivity : Disorder Robustness and Topological Density of States Peaks

    Author: Tomas Löthman
    Publication date: 2021-05-04 13:50

    We explore the connection between robust material platforms for superconductivity and the modern condensed matter physics paradigms of two-dimensional materials, topological states of matter, and odd-frequency superconductivity. Specifically, the recent discoveries of gapless topological matter and truly two-dimensional materials with graphene have greatly expanded the class of materials for which topology produces large, robust, even singular, density of states (DOS) peaks in the electronic structure that in turn are highly susceptible to new ordered states of matter, including superconductivity. 

    In this thesis, we address the crucial question of superconductivity and competing orders near such DOS peaks, in addition to the stability of unconventional superconducting orders towards disorder. We show that DOS peaks are not only highly conducive to ordered states, but also that they are particularly favorable for superconductivity. We show that superconducting domes are especially likely to appear near DOS peaks. The result is fundamental, and stems from an inherent difference between the ordering susceptibilities towards superconductivity and all competing orders,...

  • Twisting it up the Quantum Way : On Matrix Models, q-deformations and Supersymmetric Gauge Theories

    Author: Rebecca Lodin
    Publication date: 2021-04-30 08:53

    The mathematical framework which quantum field theory constitutes has been very successful in describing nature. As an extension of such a framework, the idea of supersymmetry was introduced. This greatly simplified the mathematical description of the theories, making them more tractable. Recently, the method of supersymmetric localisation, in which one can compute infinite dimensional integrals exactly, enabled computations of partition functions for different supersymmetric gauge theories in various dimensions. Such partition functions sometimes resulted in the form of matrix models or even q-deformed matrix models, where the latter are not very well-studied. Classical, or un-deformed, matrix models on the other hand are studied in much greater detail. One particular tool that is used in the study of classical matrix models is the Ward identities called Virasoro constraints. Motivated by firstly the desire to understand q-deformed matrix models better and secondly the gauge theory applications of the results, we studied the derivation of and solution to such q-deformed Virasoro constraints. We also explored the implications of partition functions...

  • Electrochemical characterizations of conducting redox polymers with proton traps : Enabling proton cycling in aprotic systems for high potential energy storage

    Author: Lisa Åkerlund
    Publication date: 2021-04-29 14:44

    Floods, droughts and unpredictable weather could be the new reality for millions of people in a near future, unless we drastically decrease our greenhouse gas emissions to prevent the global average temperature from increasing even further. Material innovations will most certainly be essential for many of the technical solutions needed in order to tackle environmental issues. One major challenge is how to deal with the massive energy demand, following the average lifestyle of today, in a way that is both reliable and sustainable. Renewable energy sources have a varying output over time, hence cannot meet the demand for electricity by themselves. To buffer between demand and production, new ways to store the renewably produced energy are crucial. From a life cycle aspect conventional battery types are far from sustainable, and, with the increasing number of electronic devices for numerous applications, we need new options.

    This thesis explores conducting redox polymers (CRPs), which can be utilized as organic cathode materials in high potential energy storage. Hydroquinone (HQ) was applied as the capacity carrying pendant group, and by the introduction of a proton trap...

  • Dynamics of excited electronic states in functional materials

    Author: Raquel Esteban-Puyuelo
    Publication date: 2021-04-28 14:31

    Non-equilibrium processes involving excited electron states are very common in nature. This work summarizes some of the theoretical developments available to study them in finite and ex-tended systems. The focus lays in the class of Mixed Quantum-Classical methods that describe electrons as quantum-mechanical particles but approximate ionic motion to behave classically. In particular, Non-Adiabatic Molecular Dynamics and Real Time Density Functional Theory are described and applied to answer questions regarding non-equilibrium dynamics in diverse functional materials. First, the effect of phase boundaries and defects in monolayer MoS2 sam-ples is studied. This material has been suggested as a good candidate to substitute silicon in many applications, such as flexible electronics and solar cells. It is known that defects and dif-ferent polymorphs are present in experimental samples, and therefore it is extremely important to understand how realistic samples perform. We present how the electron-hole recombination times are accelerated in presence of defects, as well as how the structural changes in sam-ples that mix several phases of MoS2 affect their electronic structure. After...

  • Functionalized Graphene as Superlattice and Gas Sensor

    Author: Tianbo Duan
    Publication date: 2021-04-28 10:20

    Graphene, an atomic-thin carbon sheet with carbon atoms tightly packed honeycomb-like lattice, has attracted enormous interest due to its unique chemical and physical properties. However, the intrinsic zero bandgap characteristic of graphene has so far prevented graphene from building effective electronic and optoelectronic devices. To address this concern, different functionalization methods have been proposed to modify the electronic properties of graphene. This thesis focuses on different graphene surface functionalizations and their applications in gas detections and superlattices.

    First of all, the surface cleanness of graphene plays a crucial role in the performance of graphene devices. To achieve a controlled removal of polymer residues on graphene surface, a facile solvent based method has been proposed, which can drastically improve the charge carrier mobility of graphene devices by a factor of 3, indicating a potential ballistic transport of graphene under ambient condition. In addition, an electron beam induced fluorination cycle is proposed to eliminate the airborne hydrocarbon contamination related to aging effects on the graphene surface. Subsequent...

  • PARN - A Tale of A de-Tailor : Functional importance of poly(A) degradation in developmental and telomere biology disorders

    Author: Sethu Madhava Rao Gunja
    Publication date: 2021-04-28 09:45

    Poly(A)-specific ribonuclease (PARN) is a eukaryotic 3’-5’exoribonuclease that removes poly(A) tails of many coding and non-coding RNAs. In this thesis, we have studied the physiological role of PARN. We have found that genetic lesions in the human PARN gene are associated with a spectrum of human developmental disorders, including telomere biology disorders (TBDs). TBDs encompass a spectrum of developmental disorders associated with telomere dysfunction and include idiopathic pulmonary fibrosis (IPF), aplastic anaemic (AA), dyskeratosis congenita (DC) and Hoyeraal-Hreidarsson syndrome (HHS). Patients with mono-allelic mutations in PARN suffer from developmental and neurological disorders, whereas bi-allelic mutations are associated with severe disorders, e.g., DC or HHS.

    Transcriptome analysis revealed that PARN deficient patients were affected in a number of cellular pathways. The most affected were the ribosome/translation, cell-cell adhesion, cell cycle and cell signaling pathways. We also found that PARN deficient patients were defective in the biogenesis of a large number of non-coding RNAs (ncRNAs), including snoRNAs, scaRNAs,...

  • Image Processing, Machine Learning and Visualization for Tissue Analysis

    Author: Leslie Solorzano
    Publication date: 2021-04-27 14:32

    Knowledge discovery for understanding mechanisms of disease requires the integration of multiple sources of data collected at various magnifications and by different imaging techniques. Using spatial information, we can build maps of tissue and cells in which it is possible to extract, e.g., measurements of cell morphology, protein expression, and gene expression. These measurements reveal knowledge about cells such as their identity, origin, density, structural organization, activity, and interactions with other cells and cell communities. Knowledge that can be correlated with survival and drug effectiveness. This thesis presents multidisciplinary projects that include a variety of methods for image and data analysis applied to images coming from fluorescence- and brightfield microscopy.

    In brightfield images, the number of proteins that can be observed in the same tissue section is limited. To overcome this, we identified protein expression coming from consecutive tissue sections and fused images using registration to quantify protein co-expression. Here, the main challenge was to build a framework handling very large images with a combination of rigid and non-rigid...