Self-organized Ion Beam Pattern Formation on Si(001)

Self-organized ion beam pattern formation of Si(001) by 2 keV Kr+ ion bombardment was investigated in-situ with scanning tunnelling microscopy, and low energy electron diffraction and ex-situ with atomic force microscopy, scanning electron microscopy, transmission electron microscopy, and Rutherford backscattering spectrometry. It is known that metal impurities can induce pattern formation. The effect of co-depositing Pd, Ir, Fe, Ag, and Pb on ion beam pattern formation was analyzed. For the condition analyzed here, the ability of the metal to form a silicide is necessary for inducing pattern formation. However this is not sufficient. Comparing the effects of metals with similar nuclear charge and mass, but with different ability to form silicides, shows that collision kinetics are not decisive for pattern formation. To understand the observed phenomena one has to consider that the morphology and the composition of the surface are bidirectionally coupled. Due to this coupling the metal concentration depends on the surface history and it does not determine the resulting morphology. For ion incidence angles from 58° to 79° patterns develop on Si during 2 keV Kr+ ion bombardment at room temperature even without co-deposition of impurities. The evolution of the surface morphology was studied using in-situ scanning tunnelling microscopy for the ion incidence angles 63° and 75°. The fluence was varied by a factor of 1000. Two fluence regimes can be distiguished. While a similar ripple pattern evolves in the low fluence regime for both incidence angles, the evolution differs for both incidence angles in the high fluence regime. In the high fluence regime perpendicular mode ripples and a roof-tile morphology develop for 63° and 75° respectively. The observations will be compared to experimental data of ion beam patterning of Si and Ge from literature to identify universal phenomena. Comparing the results with theoretical models allows to asses their applicability to ion beam pattern formation of Si. Si(001) amorphizes under ion bombardment below a critical temperature and is crystalline above the critical temperature. For 2 keV Kr+ ions the critical temperature is (674 ± 10) K. In a limited temperature range of 674 K to 720 K the surface develops a pit and mound morphology with the step edges parallel to the ⟨110⟩ directions. The pattern formation is driven by the Ehrlich-Schwoebel barrier inducing an effective uphill diffusion current. The surface roughness is maximum at T ≈ 700 K. At this temperature the fluence dependence of the surface morphology was studied. For high fluences the pattern changes into a ridge and valley morphology where the directions of the ridges and valley is ≈ 45° rotated to the ⟨110⟩ directions

Computational mass spectrometry of linear binary synthetic copolymers

The accurate characterization of synthetic polymer sequences represents a major challenge in polymer science. We present a computational approach to quantify the abundances of all sequences in a measured copolymer sample. The first step in our workflow is transforming mass spectra into copolymer fingerprints. Our method is based on linear programming and is capable of automatically resolving overlapping isotopes and isobaric ions. Peak intensities in matrix-assisted laser desorption/ionization spectra are influenced by mass and composition-dependent ionization. We demonstrate a method to correct the abundance bias. The second step in our workflow is interpreting the computed copolymer fingerprints using new Markov chain models for copolymerization kinetics: The Bernoulli and Geometric models. In contrast to previous Markov chain approaches to copolymerization, both models take variable chain lengths and time-dependent monomer probabilities into account and allow computing sequence likelihoods and copolymer fingerprints. We find that computing the models is fast and memory efficient. Then, we focus on the Geometric copolymerization model with reactivity parameters. First, several approaches to identify the optimal model parameters from observed fingerprints are evaluated using Monte-Carlo simulated data. A compromise between robustness and running time is found by exploiting the relationship between ordinary differential equations and the Geometric model. Second, we show that the model is also useful for copolymerizations involving termination and depropagation reactions. We then compute several copolymer statistics and compared them to the statistics obtained from Monte-Carlo simulations. Last but not least, we present our software framework COCONUT, which implements all algorithms presented in this thesis. Our software is freely available and provides a graphical user interface. COCONUT represents a step towards comprehensive computational support in polymer science

Exploring the limits of the geometric copolymerization model

The geometric copolymerization model is a recently introduced statistical Markov chain model. Here, we investigate its practicality. First, several approaches to identify the optimal model parameters from observed copolymer fingerprints are evaluated using Monte Carlo simulated data. Directly optimizing the parameters is robust against noise but has impractically long running times. A compromise between robustness and running time is found by exploiting the relationship between monomer concentrations calculated by ordinary differential equations and the geometric model. Second, we investigate the applicability of the model to copolymerizations beyond living polymerization and show that the model is useful for copolymerizations involving termination and depropagation reactions

Morphological transitions in the patterning of the crystalline Ge(001) surface induced by ion irradiation

We investigate the morphologies of the Ge(001) surface that are produced by bombardment with a normally incident, broad argon ion beam at sample temperatures above the recrystallization temperature. Two previously-observed kinds of topographies are seen, i.e., patterns consisting of upright and inverted rectangular pyramids, as well as patterns composed of shallow, isotropic basins. In addition, we observe the formation of an unexpected third type of pattern for intermediate values of the temperature, ion energy and ion flux. In this type of transitional morphology, isolated peaks with rectangular cross sections stand above a landscape of shallow, rounded basins. We also extend past theoretical work to include a second order correction term that comes from the curvature dependence of the sputter yield. For a range of parameter values, the resulting continuum model of the surface dynamics produces patterns that are remarkably similar to the transitional morphologies we observe in our experiments. The formation of the isolated peaks is the result of a term that is not ordinarily included in the equation of motion, a second order correction to the curvature dependence of the sputter yield

Strong anisotropy in surface kinetic roughening: analysis and experiments

We report an experimental assessment of surface kinetic roughening properties that are anisotropic in space. Working for two specific instances of silicon surfaces irradiated by ion-beam sputtering under diverse conditions (with and without concurrent metallic impurity codeposition), we verify the predictions and consistency of a recently proposed scaling Ansatz for surface observables like the two-dimensional (2D) height Power Spectral Density (PSD). In contrast with other formulations, this Ansatz is naturally tailored to the study of two-dimensional surfaces, and allows to readily explore the implications of anisotropic scaling for other observables, such as real-space correlation functions and PSD functions for 1D profiles of the surface. Our results confirm that there are indeed actual experimental systems whose kinetic roughening is strongly anisotropic, as consistently described by this scaling analysis. In the light of our work, some types of experimental measurements are seen to be more affected by issues like finite space resolution effects, etc. that may hinder a clear-cut assessment of strongly anisotropic scaling in the present and other practical contexts

Systematic evaluation of particle loss during handling in the percutaneous transluminal angioplasty for eight different drug-coated balloons

Paclitaxel drug coated balloons (DCBs) should provide optimal drug transfer exclusively to the target tissue. The aim of this study was to evaluate the particle loss by handling during angioplasty. A robotic arm was developed for systematic and reproducible drug abrasion experiments. The contact force on eight different commercially available DCB types was gradually increased, and high-resolution microscopic images of the deflated and inflated balloons were recorded. Three types of DCBs were classified: no abrasion of the drug in both statuses (deflated and inflated), significant abrasion only in the inflated status, and significant abrasion in both statuses. Quantitative measurements via image processing confirmed the qualitative classification and showed changes of the drug area between 2.25 and 45.73% (13.28 ± 14.29%) in the deflated status, and between 1.66 and 40.41% (21.43 ± 16.48%) in the inflated status. The structures and compositions of the DCBs are different, some are significantly more susceptible to drug loss. Particle loss by handling during angioplasty leads to different paclitaxel doses in the target regions for same DCB types. Susceptibility to involuntary drug loss may cause side effects, such as varying effective paclitaxel doses, which may explain variations in studies regarding the therapeutic outcome

Exploiting cell cycle inhibitor genes of the KRP family to control root-knot nematode induced feeding sites in plants.

Made available in DSpace on 2018-08-11T00:42:06Z (GMT). No. of bitstreams: 1 Coelhoetal2017PlantCellampEnvironment.pdf: 5492267 bytes, checksum: 547162c264fe8e6c301bf52439d7d29d (MD5) Previous issue date: 2017-08-11bitstream/item/162650/1/Coelho-et-al-2017-Plant-Cell-amp-Environment.pd

Hybridization may aid evolutionary rescue of an endangered East African passerine

Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likelihood of such evolutionary rescue for individual species remains challenging. Here, we use the example of Zosterops silvanus, an endangered East African highland bird species suffering from severe habitat loss and fragmentation, to investigate whether hybridization with its congener Zosterops flavilateralis might enable evolutionary rescue of its Taita Hills population. To do so, we employ an empirically parameterized individual-based model to simulate the species' behaviour, physiology and genetics. We test the population's response to different assumptions of mating behaviour and multiple scenarios of habitat change. We show that as long as hybridization does take place, evolutionary rescue of Z. silvanus is likely. Intermediate hybridization rates enable the greatest long-term population growth, due to trade-offs between adaptive and maladaptive introgressed alleles. Habitat change did not have a strong effect on population growth rates, as Z. silvanus is a strong disperser and landscape configuration is therefore not the limiting factor for hybridization. Our results show that targeted gene flow may be a promising avenue to help accelerate the adaptation of endangered species to novel environments, and demonstrate how to combine empirical research and mechanistic modelling to deliver species-specific predictions for conservation planning.Peer reviewe

A neutron trigger detector for pulsed neutron sources

A variety of experiments investigating properties of neutrons can be performed at pulsed source facilities like the research reactor TRIGA Mainz. A typical problem faced by these experiments is the non-availibility of a reliable facility-provided trigger signal in coincidence with the neutron production. Here we present the design and implementation of a neutron pulse detector that provides a coincident trigger signal for experimental timing with a relative precision of 4.5 ms.Comment: 16 pages, 10 figure