Carbon nanotubes (CNTs) have attracted an immense attention of the research community since reporting on this system by S. Ijima in 1991. A "single-walled" CNT (SWCNT) can be considered as a rolled-up single-layer graphene - a one atom-thick layer of carbon atoms arranged in a hexagonal lattice. This cylindrical object being just about 1 nm in diameter and up to a few centimeters long can be considered as a quasi-one-dimensional system. Several nanotubes "inserted" one into another build a so-called multi-walled CNT. CNTs exhibit outstanding mechanical, thermal and electronic properties which make this material a promising candidate for numerous applications - reinforced composite materials, nano-electronics, molecular sensors and drug delivery systems to name just a few. CNTs possess tensile strength 10 and 5 times higher than that of steel and Kevlar, respectively, that creates a great prospective for their use as reinforcing units in materials subjected to high-impact dynamic loads/stress (bullet-proof jackets, for example). Nonetheless, to date there are no reports on experimental study of CNTs behavior at extreme dynamic loads which may substantiate such prospective. In addition, several theoretical predictions indicate a possibility of CNTs transformation into new structural forms at extreme pressures. The goal of this work is a systematic study of structural properties and exploration possibility of synthesis of new materials from CNTs under extreme pressures/stress.In a set of experiments purified SWCNTs were subjected to high dynamic (shock) pressures up to 52 GPa. Recovered from each pressure step sample was characterized by High Resolution Transmission Electron Microscopy (HRTEM) and Raman spectroscopy. We observed a gradual increase of defects concentration on the CNT surface with pressure along with shortening and "un-zipping" of the tubes and an onset of the complete CNT destruction at 26 GPa shock which sets-up a limit for certain practical applications of this kind of material. Further increase of the dynamic load to 35 and 52 GPa led to CNT transformation into a mixture of disordered sp²/sp³- bonded carbon atoms with nano-sized graphene clusters. No CNT polymerization or coalescence was observed contrary to some theoretical predictions. For comparison, we conducted a separate experiment on the same CNT material under static compression up to 36 GPa in a diamond anvil cell (DAC). The system evolution was monitored in-situ during the high-pressure run using Raman spectroscopy. Examination of the material recovered from high pressure revealed that certain fraction of the CNTs survived exposure to 36 GPa though similar damages were introduced to the nanotubes as in the shock experiments evidenced by the Raman spectra. This result testifies a substantial difference in the processes of CNT destruction by dynamic vs static compression.A separate set of experiments in DACs was aimed at in-situ monitoring of the Raman spectra (in particular G-band) during pressure evolution and establishing the level of static pressure which causes a complete destruction of SWCNTs from the same batch as used in similar experiments at the dynamic compression. Pressure dependence of G-band, G(p), exhibited several peculiarities at approximately 15, 45 and 60 GPa which we associate with collapse of large (1.2 nm) and small (∼1 nm) diameter CNTs, and an onset of nanotubes transformation to a new phase respectively. Raman spectra of the sample recovered after 58 GPa static compression exhibit no RBM signal, large G-band broadening and high D/G peak intensity ratio that testifies for CNT destruction. Pressure increase to 100 GPa resulted in a substantial altering of Raman spectrum of the recovered sample - appearance of characteristic features of highly disordered sp²-and sp³-bonded carbons which may stem from interlinked nano-sized graphene clusters.Change of CNTs structure results in the altering of their electronic properties thus structure evolution of the CNTs with pressure may be followed by monitoring electrical resistance change with pressure. In a series of experiments we conducted in-situ electrical resistance (R) measurements of the SWCNTs under static pressures up to 45 GPa (temperature range 293 - 395 K) in a conductive DAC. Isobaric temperature dependence of the resistance indicated that the nanotube sample is comprised predominantly of semiconducting CNTs. A set of anomalies observed in R(p) at room temperature we interpret as a sequential, diameter-dependent collapse of the CNTs. Raman characterization of the samples after the pressure cycling confirmed reversibility of these structural transitions for at least certain CNT species accompanied by a substantial increase of CNT defects density. No indication of nanotubes polymerization was observed.Although thermal conductivity of individual CNTs is excellent (5 times better than that of copper) heat conduction becomes far less efficient in "conventional" system, i.e. when the tubes form bundles/ropes which may lead to a risk of CNT destruction by overheating. Therefore probing CNTs response to extreme heat (temperature) is important both for testing capabilities of the nanotube material and developing methods of its proper characterization. We followed temporal evolution of the Raman spectra of bundled SWCNTs exposed to high laser irradiance in both air and argon atmosphere. Temperature threshold for CNT destruction in air appeared to be lower than that in Ar, the fact indicating importance of the CNTs oxidation for their structural integrity. We show that primary damage occurs in resonant with excitation laser CNTs which act as photon energy absorbers. We show that smaller diameter and metallic nanotubes are less stable to high irradiance/heat flux than their large diameter/semiconducting counterparts. Remarkably, some small diameter, non-resonant CNTs were destroyed indirectly, i.e. via overheating induced by neighbor CNTs in resonance (photon absorbers). We demonstrate the importance of laser heating effects on Raman characterization of nanotubes.Even though carbon nanotubes exhibit susceptibility to extreme pressure/stress and high laser irradiance/overheating their potential for use in very demanding applications is not yet challenged: for example SWCNT destruction under dynamic compression occurs at pressure exceeding 20 times the typical threshold levels in ballistic impact. Cold compression of nanotubes also opens up perspectives of synthesis of new carbon phases with superior mechanical properties. / Godkänd; 2014; 20141216 (maxnoe); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Maxime Noël Ämne: Fysik/Physics Avhandling: Physical Properties and Structural Stability of Carbon Nanotubes Under Extreme Conditions Opponent: Professor David Dunstan, School of Physics and Astronomy, Queen Mary, University of London, London, Ordförande: Professor Alexander Soldatov, Avd för materialvetenskap, Institutionen för teknikvetenskap och matematik, Luleå tekniska universitet Tid: Fredag den 30 januari, kl 10.00 Plats: E231, Luleå tekniska universitet

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Background: Fluoroscopy is a common imaging technique which uses X-ray to derive a real time imaging of patient anatomy to determine diagnosis and positioning of patients for interventional procedures. It is therefore important that the fluoroscopy systems maintain their performance. Assessment of image quality parameters (such as: low contrast resolution, uniformity, homogeneity and detection of defective pixels and artifacts) is one way to assess if they maintain their performance. This study aims to develop and implement a Matlab script to do a remote Quality Control (QC) and set up tolerance levels on different types of fluoroscopy systems.                                        Method: Three fluoroscopy systems were used in this project, Siemens Axiom Artis Zee MP, Siemens Cios Alpha and Ziehm Vision RFD. There were two setups used in the study for image acquisition by adding a 2 mm Cu filter as the attenuating material placed directly on the X-ray tube. A Cylindrical aluminum contrast detail of dimension 4 mm thick and 6 mm diameter was placed in the middle of X-ray field (Setup 1 on patient couch and setup 2 directly on the flat panel detector). The fluoroscopic images were acquired with and without contrast detail over a period of six month. The image quality parameter SNR2rate was determined from signal and background images while other quality parameters such as kerma-area product rate PKA, rate, uniformity, homogeneity, low contrast resolution, SNR, defective pixels and artefact detection were examined and determined from the background images. Two additional supporting experiments were performed, one with a chest phantom and 13 cm PMMA and the other one a human visual detection 4-AFC experiment.                 Result: The image quality index SNR2rate and the dose rate index PKA, rate, the low contrast resolution parameter (LCRP), uniformity, homogeneity and SNR values were within ±2 standard deviation for repeated measurements in each system. Nevertheless, the result indicates that Siemens Axiom Artis Zee MP has the best performance while Ziehm Vision RFD has the worst performance between these three systems. The result from the defective pixel method indicate that for 20 % tolerance there were no defective pixels for Siemens Axiom and Cios Alpha. Ziehm Vision had also no defective pixels for 30 % tolerance. The artefact detection shows that artefact level is high for fluoroscopy systems and Ziehm Vision RFD has artefact level more than 50 % tolerance.  The chest phantom experiment indicate that SNR2rate varies considerably over the lung anatomy as expected.           The 4-AFC experiment indicates that the effective time was 0.14 s for human observers to integrate the information in the live image.           Conclusion: The methods developed and implemented in this project were successfully able to determine and assess the image quality parameters such as SNR2rate,PKA, rate, low contrast resolution, uniformity, homogeneity, SNR and detection of defective pixels. Further effort is needed for installation of Matlab script on our local server, connection with Excel program and internal website (SharePoint) and adding more clinical fluoroscopy systems to do remote QC in Region Östergötland.

Macrocoherence is the concept of quantum mechanics being scaled up to the macroscopic level where everyday physical systems should inhibit quantum mechanical properties, however this is not what is observed. Through the use of Leggett-Garg inequalities, one can infer if there is a fundamental quantum mechanical behavior of the system being observed. Then, using violations of these inequalities, this paper discusses the possibility of extracting useful measures of how macroscopic a system can be. Utilizing an analogy with the measures of locality through Bell's inequalities, the scope of what a measure should consist of is discussed. A measure should be proper in the sense that a baseline of 0 should be obtained from system that never violates an LGI. Further, it is proposed that a measure should extend naturally to all orders of LGIs without ranking quantum systems differently. With these in mind two measures are proposed, one utilizing the integral over the violated area of a LGI over time whereas the other uses inner products over a matrix defined elementwise as a specified LGI. The measures scopes are discussed and their applications are showcased for some analytical quantum systems. Though functional, the measures are found to lack a resource tied to its value complicating the conceptualization of what is being measured. It is concluded that a new effort to find a true measure of macrocoherence should start from the concept of a resource.

This work explores the possibilities to use quantum computers and quantum based language models for machine translation. Precise translation requires vast expertise and knowledge of various languages, thus machine translationis still far from superseding humans. Quantum computers could improve machine translation due to their high computational power, as they benefit from properties such as superposition and entanglement to process data faster and in parallel. We focused our work on the DIStributional COmpositional CATegorical (DisCoCat) semantics and its python toolbox DisCoPy developed by [1]. We built and transformed simple, complex, and negative English and Spanish sentences to DisCoCat diagrams. Those diagrams are then used as input to quantum circuits, allowing us to perform calculations in NISQ devices providedby IBMQ. The calculations show that a quantum computer can understand the meaning of simple and complex sentences in different languages, and this is the first step to perform translation with Quantum Computers. In addition, we worked on preserving sentence meaning by measuring the cosine similarity between two vectorised sentences and obtained sentence similarities scores of 95%.

Dark matter is required in the universe to explain certain phenomenona, like the dynamics of stars and temperature fluctuations of the cosmic microwave background. This thesis focuses on the production of dark matter in the ATLAS experiment at the Large Hadron Collider, where the dark matter is detected through momentum conservation. The models of interest are simplified dark matter models consisting of a pair of top quarks produced together with a mediator. It is the mediator, scalar or pseudoscalar having a mass of 20 GeV  that decays to dark matter particles each having a mass of 1 GeV. The final state considered in this thesis consists of jets, one lepton and missing transverse momentum.  The coupling constants between the mediator and the top quarks and the mediator and the dark matter particles is set to 1.  The goal of the work presented in this thesis is  to improve the searches for dark matter of dark matter, by studying the distributions of variables that can separate the signal from various background processes. This is done by loosening the requirement on missing transverse momentum in the dark matter searches from 230 GeV to 70 GeV and study the low missing transverse momenta samples. This thesis then finds that the low missing transverse momentum scalar sample has the highest yield of all samples studied. Moreover, the transverse mass selection efficiency for the low missing transverse momentum sample is found to be low and needs to be improved. The last conclusion presented is that the azimuthal angle between the lepton and the missing transverse momentum can be used to differentiate the mediator types in both the low and high missing transverse momentum samples.

Equivariant localization is a technique can be used to reduce the dimensionality of integral for the manifold with a Lie group action on. Such technique can beapplied to simply the calculation of path integral with certain type of symmetries.In this thesis, we will first introduce the language of super algebra and supergeometry, then discuss the localization formula and Mathai-Quillen formalismaccording to supergeometry.In the last chapter, we will equivariantize the formalism we made and discuss how this being manifested in odd tangent bundleand holomorphic line bundle. Such methodology is very powerful in providing areasonable regularization to eradicate divergence and such regularization is basedon the intrinsic property of the system, in other word the symmetry.

Grasping and dexterous manipulation is a huge area in the current robotic research field. Traditionally in industrial environments, robots are customized for a certain task and work well with repetitive movements where the entire process is predetermined and deterministic. The possibility for a robot to adapt to its surroundings and manipulate objects with unknown properties is very limited and requires new models and methods. It is advantageous to explore and test new algorithms and models in a simulated environment before building physical systems. This thesis focuses on making the development, design and control of dexterous robot hands easier by exploring the benefits and challenges to use simulation in Algoryx's physics engine AGX Dynamics for experimentation and evaluation of design, motion planning, contact models, geometry, etc. The goal is to simulate complex grasping situations in AGX Dynamics and to build knowledge about contact mechanics to fully capture the dynamics of grasping in simulation. The work consists of validating the simulation library with regards to fundamental physics characteristics involved in grasping by a series of benchmark tests. The validation process aims to verify the models and numerical methods in AGX Dynamics to ensure sim2real transfer. The work has exposed friction as one of the biggest challenges in simulation. Developments of the current friction models that better represent the reality have been implemented and tested in AGX. They both show promising results for further development.

Early detection of cancer is necessary to minimize mental and physical distress. Therefore, this report investigated the possibilities of using machine learning methods to detect glioma in an early stage. This by looking at genetic data from real patients. This data consists of more than 14 million genetic features called SNP:s, and is therefore considered highly dimensional. However, the question is if these genetic data can be used for prediction of glioma?   The approach used was to first reduce the dimension by methods such as weighted cosine similarities, PCA, undercomplete autoencoder, t-SNE and sum pooling. To make prediction, k-means, naive bayes, kNN and neural networks were used.  The results of this study show that the methods mentioned above can be difficult to use in determining the risk of cancer. However, this may depend on the hyperparameters used in the models as these play a major role in performance. Some important hyperparameters were the number of nodes and layers in the undercomplete autoencoder and the neural network. Using too many nodes or layers may cause these models to overfit. Contrary, using too few nodes or layers may instead cause them to underfit. The perplexity in the t-SNE and the number of blocks in the sum pooling were also key parameters, these two hyperparameters were hard to tune well since the grid search was very costly time-wise.

The intense increase in energy consumption around the world has prompted a great deal of research on alternative and sustainable energy storage systems such as organic batteries. The fundamental understanding of the physics of organic salts and the ion insertion mechanism plays a key role in the development of electrode materials used in such sustainable batteries. The system studied in this project is of Lithium (2,5-dilithium-oxy)-terephthalate where a previous project studied this system from a different angle.  The electronic structure generation of the system is based on Density Functional Theory (DFT) along with an evolutionary algorithm to find the structures with minimum energy. The effects of varying the description of the exchange-correlation interaction were studied while introducing lithium ions to the system. This was done while also monitoring the repercussions of crystal structure optimization on the voltages, charge redistribution, and bonds of the system. The geometrical optimization of the hybrid functional resulted in the potential of the 2-electron step between Li2-p-DHT/ Li4-p-DHT of 2.6 V being closer to the experimental value recorded at 2.7 V.