Nikkelimangaanioksidien atomitasokasvatus

Ternary metal oxides are among the most researched areas in inorganic chemistry. They are interesting because they offer a wide range of functionalities and their properties can be controlled with correct fabrication methods. One such method is atomic layer deposition (ALD) which, in theory, makes it possible to control the structure of the material down to the level of atom layers. In general, the atomic layer deposition of ternary oxides is challenging but the problems can be overcome with careful design of the ALD reactor and its parameters. One of the interesting materials in ternary oxides is the nickel manganese oxides which have three different structures: Spinel structure (NiMn2O4), ilmenite structure (NiMnO3) and murdochite structure (Ni6MnO8). The spinel structured NiMn2O4 has been the most interesting one and shown good results in practical applications such as an electrode material for lithium ion batteries. The other structures have been researched as potential catalysts for oxygen evolution and reduction reactions for devices like fuel cells. Nickel manganese oxide thin films have been fabricated before but not with ALD. In this work, ALD is used to fabricate nickel manganese oxide thin films and their crystal structures are determined with grazing angle incidence x-ray diffraction (GIXRD). Mn(thd)3, Ni(thd)2 and ozone are used as precursor materials. Different ratios of nickel and manganese are deposited in various temperatures to see if this causes any difference to the structure. In addition, the thin films are heat-treated and their crystal structures are examined afterwards. Some magnetic and optical measurements are also taken.Ternääriset metallioksidit ovat tutkituimpia alueita epäorgaanisessa kemiassa. Ne ovat erityisen kiinnostavia funktionaalisuuksiensa takia ja siksi, että niiden ominaisuudet ovat säädeltävissä oikeilla valmistustekniikoilla. Eräs tällainen valmistustapa on atomitasokasvatus (ALD), jonka avulla on teoriassa mahdollista kontrolloida materiaalin rakennetta jopa atomitasoille asti. Yleisesti ottaen ternääristen metallioksidien atomitasokasvatus on haastavaa, mutta sen ongelmat voidaan usein ratkaista muuttamalla ALD-reaktorin kokoonpanoa tai sen parametreja. Yksi kiinnostava osa ternäärisiä metallioksideja on nikkelimangaanioksidit, joille on kolme eri rakennetta: spinellirakenne (NiMn2O4), ilmenite-rakenne (NiMnO3) ja murdochite-rakenne (Ni6MnO8). Spinellirakenteinen NiMn2O4 on rakenteista tutkituin ja osoittanut hyvää suorituskykyä käytännön sovelluksissa kuten elektrolyyttimateriaalina litiumioniakuissa. Muita rakenteita on tutkittu potentiaalisina katalysaattoreina hapen kehitys- ja pelkistysreaktioille esimerkiksi polttokennoihin. Nikkelimangaanioksidi ohutkalvoja on valmistettu ennen, mutta ei käyttäen atomitasokasvatusta. Tässä työssä nikkelimangaanioksidi ohutkalvoja valmistetaan atomitasokasvatuksella ja niiden kiderakenne määritetään röntgenkristallografialla. Mn(thd)3, Ni(thd)2 ja otsoni toimivat lähtöaineina. Nikkelin ja mangaanin määrää sekä kasvatuslämpötilaa vaihdellaan, jotta nähdään näiden vaikutus rakenteeseen. Lisäksi ohutkalvoja lämpökäsitellään ja niiden kiderakenteet tutkitaan tämän jälkeen. Joitain magneettisia ja optisia ominaisuuksia myös mitataan

Sensor-based machine olfaction with neuromorphic models of the olfactory system

Electronic noses combine an array of cross-selective gas sensors with a pattern recognition engine to identify odors. Pattern recognition of multivariate gas sensor response is usually performed using existing statistical and chemometric techniques. An alternative solution involves developing novel algorithms inspired by information processing in the biological olfactory system. The objective of this dissertation is to develop a neuromorphic architecture for pattern recognition for a chemosensor array inspired by key signal processing mechanisms in the olfactory system. Our approach can be summarized as follows. First, a high-dimensional odor signal is generated from a chemical sensor array. Three approaches have been proposed to generate this combinatorial and high dimensional odor signal: temperature-modulation of a metal-oxide chemoresistor, a large population of optical microbead sensors, and infrared spectroscopy. The resulting high-dimensional odor signals are subject to dimensionality reduction using a self-organizing model of chemotopic convergence. This convergence transforms the initial combinatorial high-dimensional code into an organized spatial pattern (i.e., an odor image), which decouples odor identity from intensity. Two lateral inhibitory circuits subsequently process the highly overlapping odor images obtained after convergence. The first shunting lateral inhibition circuits perform gain control enabling identification of the odorant across a wide range of concentration. This shunting lateral inhibition is followed by an additive lateral inhibition circuit with center-surround connections. These circuits improve contrast between odor images leading to more sparse and orthogonal patterns than the one available at the input. The sharpened odor image is stored in a neurodynamic model of a cortex. Finally, anti-Hebbian/ Hebbian inhibitory feedback from the cortical circuits to the contrast enhancement circuits performs mixture segmentation and weaker odor/background suppression, respectively. We validate the models using experimental datasets and show our results are consistent with recent neurobiological findings

Fantastic ribonucleoprotein complexes and how to study them. Architectural principles of regulatory assemblies in bacteria.

The fate of a bacterial RNA transcript is controlled by three key players: ribonucleases, RNA binding proteins (RBPs) and small regulatory RNAs (sRNAs). Together these form an information-rich regulatory network that exercises post-transcriptional control of gene expression. A key RBP in bacteria is Hfq, which is best studied as a facilitator for sRNA-mRNA pairing. In Pseudomonas aeruginosa, however, Hfq is known to modulate translation of more than 100 genes in cooperation with an effector protein, Crc, by sequestering the ribosome binding site of the corresponding mRNA molecules. In this thesis, Cryo-EM studies on target RNAs such as amiE and rbsB, reveal how Hfq presents multiple A-rich motifs in the mRNA 5ʹ-end to Crc and triggers assembly of higher order complexes. The structures suggest that secondary structure elements and the sequence of the target RNA determine the quaternary structure of the Hfq-Crc translation-repression assembly, introducing a degree of structural diversity that is accommodated by polymorphic interaction surfaces on both Hfq and Crc. In Escherichia coli, the homolog of the same RBP (Hfq) can modulate sRNA lifetime by repurposing the conserved ribonuclease PNPase (polynucleotide phosphorylase) into an RNA chaperone. Cryo-EM structures presented here show how the flexible KH-S1 portal of PNPase generally guides the 3ʹ-end of the sRNA sponge 3ʹETSleuZ to the catalytic core for digestion but reroutes the sRNA when bound to Hfq. In particular, an A-rich motif in the 5ʹ-end of 3ʹETSleuZ is presented to the KH and S1 domains by the Hfq distal side, while the 3ʹ-end is sequestered on the proximal side. Gel shift- and activity assays suggest that these repurposed ‘RNA carrier’ complexes protect sRNAs from other ribonucleases such as RNase E and RNase III, and potentially lend their KH-S1 portal as an interaction platform to promote sRNA/RNA target pairing. A fraction of PNPase in the cell associates with the endoribonuclease RNase E to form the E. coli ‘RNA degradosome’, a multi-enzyme ribonuclease assembly responsible for the bulk RNA turnover in the cell. Other partner enzymes include the DEAD-box helicase RhlB and Enolase. The core of the assembly, RNase E, has a long C-terminal scaffold domain that has a conserved natively unstructured character. The subcellular localization of the RNA degradosome, anchored to the cell membrane, provides a spatial component to post-transcriptional gene regulation. In this work, holistic experimental strategies to study this molecular machine are developed. Reproducible reconstitution of a truncated version of the RNA degradosome was achieved with a mix of detergents. Using small angle X-ray solution scattering (SAXS) combined with conformational ensemble computation indicates that the truncated degradosome is a highly flexible system with extended scaffold domains but can adopt more compact conformations when 9S rRNA is bound. Complementary cryo-EM studies of the catalytic core and subsequent 3D variability analyses reveal three modes of molecular motion of the RNase E protomers, adding to the overall flexibility of the RNA degradosome. Lastly, cryo-electron tomography studies of the truncated degradosome tethered to lipid vesicles provide the first visualization of the degradosome in its native environment and hint towards a degree of structural order in its components. Subsequent sub-tomogram averaging approaches to investigate putative membrane-bound RNA surveillance complexes set a foundation for future structural studies

Variational image fusion

The main goal of this work is the fusion of multiple images to a single composite that offers more information than the individual input images. We approach those fusion tasks within a variational framework. First, we present iterative schemes that are well-suited for such variational problems and related tasks. They lead to efficient algorithms that are simple to implement and well-parallelisable. Next, we design a general fusion technique that aims for an image with optimal local contrast. This is the key for a versatile method that performs well in many application areas such as multispectral imaging, decolourisation, and exposure fusion. To handle motion within an exposure set, we present the following two-step approach: First, we introduce the complete rank transform to design an optic flow approach that is robust against severe illumination changes. Second, we eliminate remaining misalignments by means of brightness transfer functions that relate the brightness values between frames. Additional knowledge about the exposure set enables us to propose the first fully coupled method that jointly computes an aligned high dynamic range image and dense displacement fields. Finally, we present a technique that infers depth information from differently focused images. In this context, we additionally introduce a novel second order regulariser that adapts to the image structure in an anisotropic way.Das Hauptziel dieser Arbeit ist die Fusion mehrerer Bilder zu einem Einzelbild, das mehr Informationen bietet als die einzelnen Eingangsbilder. Wir verwirklichen diese Fusionsaufgaben in einem variationellen Rahmen. Zunächst präsentieren wir iterative Schemata, die sich gut für solche variationellen Probleme und verwandte Aufgaben eignen. Danach entwerfen wir eine Fusionstechnik, die ein Bild mit optimalem lokalen Kontrast anstrebt. Dies ist der Schlüssel für eine vielseitige Methode, die gute Ergebnisse für zahlreiche Anwendungsbereiche wie Multispektralaufnahmen, Bildentfärbung oder Belichtungsreihenfusion liefert. Um Bewegungen in einer Belichtungsreihe zu handhaben, präsentieren wir folgenden Zweischrittansatz: Zuerst stellen wir die komplette Rangtransformation vor, um eine optische Flussmethode zu entwerfen, die robust gegenüber starken Beleuchtungsänderungen ist. Dann eliminieren wir verbleibende Registrierungsfehler mit der Helligkeitstransferfunktion, welche die Helligkeitswerte zwischen Bildern in Beziehung setzt. Zusätzliches Wissen über die Belichtungsreihe ermöglicht uns, die erste vollständig gekoppelte Methode vorzustellen, die gemeinsam ein registriertes Hochkontrastbild sowie dichte Bewegungsfelder berechnet. Final präsentieren wir eine Technik, die von unterschiedlich fokussierten Bildern Tiefeninformation ableitet. In diesem Kontext stellen wir zusätzlich einen neuen Regularisierer zweiter Ordnung vor, der sich der Bildstruktur anisotrop anpasst

Variational image fusion

The main goal of this work is the fusion of multiple images to a single composite that offers more information than the individual input images. We approach those fusion tasks within a variational framework. First, we present iterative schemes that are well-suited for such variational problems and related tasks. They lead to efficient algorithms that are simple to implement and well-parallelisable. Next, we design a general fusion technique that aims for an image with optimal local contrast. This is the key for a versatile method that performs well in many application areas such as multispectral imaging, decolourisation, and exposure fusion. To handle motion within an exposure set, we present the following two-step approach: First, we introduce the complete rank transform to design an optic flow approach that is robust against severe illumination changes. Second, we eliminate remaining misalignments by means of brightness transfer functions that relate the brightness values between frames. Additional knowledge about the exposure set enables us to propose the first fully coupled method that jointly computes an aligned high dynamic range image and dense displacement fields. Finally, we present a technique that infers depth information from differently focused images. In this context, we additionally introduce a novel second order regulariser that adapts to the image structure in an anisotropic way.Das Hauptziel dieser Arbeit ist die Fusion mehrerer Bilder zu einem Einzelbild, das mehr Informationen bietet als die einzelnen Eingangsbilder. Wir verwirklichen diese Fusionsaufgaben in einem variationellen Rahmen. Zunächst präsentieren wir iterative Schemata, die sich gut für solche variationellen Probleme und verwandte Aufgaben eignen. Danach entwerfen wir eine Fusionstechnik, die ein Bild mit optimalem lokalen Kontrast anstrebt. Dies ist der Schlüssel für eine vielseitige Methode, die gute Ergebnisse für zahlreiche Anwendungsbereiche wie Multispektralaufnahmen, Bildentfärbung oder Belichtungsreihenfusion liefert. Um Bewegungen in einer Belichtungsreihe zu handhaben, präsentieren wir folgenden Zweischrittansatz: Zuerst stellen wir die komplette Rangtransformation vor, um eine optische Flussmethode zu entwerfen, die robust gegenüber starken Beleuchtungsänderungen ist. Dann eliminieren wir verbleibende Registrierungsfehler mit der Helligkeitstransferfunktion, welche die Helligkeitswerte zwischen Bildern in Beziehung setzt. Zusätzliches Wissen über die Belichtungsreihe ermöglicht uns, die erste vollständig gekoppelte Methode vorzustellen, die gemeinsam ein registriertes Hochkontrastbild sowie dichte Bewegungsfelder berechnet. Final präsentieren wir eine Technik, die von unterschiedlich fokussierten Bildern Tiefeninformation ableitet. In diesem Kontext stellen wir zusätzlich einen neuen Regularisierer zweiter Ordnung vor, der sich der Bildstruktur anisotrop anpasst

From locomotion to dance and back : exploring rhythmic sensorimotor synchronization

Le rythme est un aspect important du mouvement et de la perception de l’environnement. Lorsque l’on danse, la pulsation musicale induit une activité neurale oscillatoire qui permet au système nerveux d’anticiper les évènements musicaux à venir. Le système moteur peut alors s’y synchroniser. Cette thèse développe de nouvelles techniques d’investigation des rythmes neuraux non strictement périodiques, tels que ceux qui régulent le tempo naturellement variable de la marche ou la perception rythmes musicaux. Elle étudie des réponses neurales reflétant la discordance entre ce que le système nerveux anticipe et ce qu’il perçoit, et qui sont nécessaire pour adapter la synchronisation de mouvements à un environnement variable. Elle montre aussi comment l’activité neurale évoquée par un rythme musical complexe est renforcée par les mouvements qui y sont synchronisés. Enfin, elle s’intéresse à ces rythmes neuraux chez des patients ayant des troubles de la marche ou de la conscience.Rhythms are central in human behaviours spanning from locomotion to music performance. In dance, self-sustaining and dynamically adapting neural oscillations entrain to the regular auditory inputs that is the musical beat. This entrainment leads to anticipation of forthcoming sensory events, which in turn allows synchronization of movements to the perceived environment. This dissertation develops novel technical approaches to investigate neural rhythms that are not strictly periodic, such as naturally tempo-varying locomotion movements and rhythms of music. It studies neural responses reflecting the discordance between what the nervous system anticipates and the actual timing of events, and that are critical for synchronizing movements to a changing environment. It also shows how the neural activity elicited by a musical rhythm is shaped by how we move. Finally, it investigates such neural rhythms in patient with gait or consciousness disorders

Pathways toward controlled assembly of functional polymer-based nanostructures

This thesis deals with a common drawback that is often encountered in self-assembled nanostructured soft matter. Even though spontaneous self-assembly can be used to create diverse nanostructures, the structures, as such, are typically polydomain, consisting of locally ordered small domains that lack mutual orientation and/or long range correlation. As a result, the material remains macroscopically isotropic and disordered. The aim here is to explore feasible ways, on one hand, to control the assembly and, on the other hand, to obtain macroscopically anisotropic materials and functions. We show the first example of how charge-transfer complexation between C60 fullerenes and electron-donating units of block copolymers can enable control of the morphology and properties of fullerene based materials. We also study the alignment of randomly oriented domains of nanostructured material over macroscopic length scales by using a real-time rheo-optical apparatus in combination with more detailed ex-situ structural characterization. Alignment of randomly oriented domains is not only useful for obtaining macroscopically anisotropic materials and functions but it can also be a prerequisite for detailed characterization of the local structures. This aspect is demonstrated for hierarchical liquid crystalline (LC) diblock copolymer structures which, upon inducing shear alignment, exhibit coexistence of two orthogonal orientations of the LC phase within the copolymer lamellae. Furthermore we demonstrate that ionic complexes forming a columnar LC phase can be efficiently aligned within polymer blends upon shearing, taken that the matrix polymers have sufficiently high molecular weight. This concept allows a simple route for macroscopically aligned nanocomposites with conjugated columnar LC functional additives. Finally, control of the nanoscale morphology in polymer/fullerene nanocomposite thin film devices is shown to allow tuning of the electrical switching that can enable construction of a memory unit. The working principles of such thin film organic memory devices have remained debated and the first systematic approach is here undertaken to tailor the active material composition and to study the morphology vs. functionality relationship