Effects of axial torsion on sp carbon atomic nanowires

Ab-initio calculations within Density Functional Theory combined with experimental Raman spectra on cluster-beam deposited pure carbon films provide a consistent picture of sp-carbon chains stabilized by sp^3 or sp^2 terminations, the latter being sensitive to torsional strain. This unexplored effect promises many exciting applications since it allows one to modify the conductive states near the Fermi level and to switch on and off the on-chain pi-electron magnetism.Comment: in print in Phys Rev Let

Growth of sp-sp² nanostructures in a carbon plasma

The growth of sp and sp² nanostructures in a carbon plasma is simulated by tight-binding molecular dynamics. The simulations are arranged so as to mimic the cluster formation conditions typical of a pulsed microplasma cluster source which is used to grow nanostructured sp-sp² carbon films [L. Ravagnan et al., Phys. Rev. Lett. 98, 216103 (2007)]. The formation of linear, ring, and fullerenelike objects in the carbon plasma is found to proceed through a very long multistep process. Therefore, tight-binding simulations of unprecedented duration have been performed by exploiting the disconnected topology of the simulated carbon plasma which made it possible to implement a computationally efficient divide-and-diagonalize procedure. Present simulations prove that topologically different structures can be formed in experiments, depending on the plasma temperature and density. A thorough characterization of the observed structures as well as their evolution (caused both by thermal annealing and by cluster ripening) is provided.Yasutaka Yamaguchi, Luciano Colombo, Paolo Piseri, Luca Ravagnan, and Paolo Milani. Phys. Rev. B 76, 134119, 2007. Copyright 2007 by the American Physical Society

Fractal analysis of sampled profiles: Systematic study

A quantitative evaluation of the influence of sampling on the numerical fractal analysis of experimental profiles is of critical importance. Although this aspect has been widely recognized, a systematic analysis of the sampling influence is still lacking. Here we present the results of a systematic analysis of synthetic self-affine profiles in order to clarify the consequences of the application of a poor sampling (up to 1000 points) typical of scanning probe microscopy for the characterization of real interfaces and surfaces. We interpret our results in terms of a deviation and a dispersion of the measured exponent with respect to the "true" one. Both the deviation and the dispersion have always been disregarded in the experimental literature, and this can be very misleading if results obtained from poorly sampled images are presented. We provide reasonable arguments to assess the universality of these effects and propose an empirical method to take them into account. We show that it is possible to correct the deviation of the measured Hurst exponent from the "true" one and give a reasonable estimate of the dispersion error. The last estimate is particularly important in the experimental results since it is an intrinsic error that depends only on the number of sampling points and can easily overwhelm the statistical error. Finally, we test our empirical method calculating the Hurst exponent for the well-known 1 + 1 dimensional directed percolation profiles, with a 512-point sampling

<i>De novo</i> synthesis of budding yeast DNA polymerase alpha and <i>POL1</i> transcription at the G₁/S boundary are not required for entrance into S phase

The POL1 gene, encoding DNA polymerase α(pol α) in Saccharomyces cerevisiae, is transiently transcribed during the cell cycle at the G1/S phase boundary. Here we show that yeast pol α is present at every stage of the cell cycle, and its level only slightly increases following the peak of POL1 transcription. POL1 mRNA synthesis driven by a GAL1 promoter can be completely abolished without affecting the growth rate of logarithmically growing yeast cultures for several cell divisions, although the amount of the pol α polypeptide drops below the physiological level. Moreover, α-factor-arrested cells can enter S phase and divide synchronously even if POL1 transcription is abolished. These results indicate that the level of yeast pol α is not rate limiting and de novo synthesis of the enzyme is not required for entrance into S phase

sp hybridization in free carbon nanoparticles-presence and stability observed by near edge X-ray absorption fine structure spectroscopy

The presence and stability of sp hybridized atoms in free carbon nanoparticles was investigated by NEXAFS spectroscopy. The experiments show that a predominant fraction of carbon atoms is found in linear sp-chains and that conversion into sp(2) structures proceeds already at low temperature and in the gas phase

Poly(methyl methacrylate) - Palladium clusters nanocomposite formation by supersonic cluster beam deposition: a method for microstructured metallization of polymer surfaces

Nanocomposite films were fabricated by supersonic cluster beam deposition (SCBD) of palladium clusters on Poly(methyl methacrylate) (PMMA) surfaces. The evolution of the electrical conductance with cluster coverage and microscopy analysis show that Pd cluster are implanted in the polymer and form a continuous layer extending for several tens of nanometers beneath the polymer surface. This allows the deposition, using stencil masks, of cluster-assembled Pd microstructures on PMMA showing a remarkably high adhesion compared to metallic films obtained by thermal evaporation. These results suggest that SCBD is a promising tool for the fabrication of metallic microstructures on flexible polymeric substrates.Comment: 11 pages, 3 figure

Three-Dimensional Shapes of Spinning Helium Nanodroplets

A significant fraction of superfluid helium nanodroplets produced in a free-jet expansion have been observed to gain high angular momentum resulting in large centrifugal deformation. We measured single-shot diffraction patterns of individual rotating helium nanodroplets up to large scattering angles using intense extreme ultraviolet light pulses from the FERMI free-electron laser. Distinct asymmetric features in the wide-angle diffraction patterns enable the unique and systematic identification of the three-dimensional droplet shapes. The analysis of a large dataset allows us to follow the evolution from axisymmetric oblate to triaxial prolate and two-lobed droplets. We find that the shapes of spinning superfluid helium droplets exhibit the same stages as classical rotating droplets while the previously reported metastable, oblate shapes of quantum droplets are not observed. Our three-dimensional analysis represents a valuable landmark for clarifying the interrelation between morphology and superfluidity on the nanometer scale

High-Gain Harmonic Generation with temporally overlapping seed pulses and application to ultrafast spectroscopy

Collinear double-pulse seeding of the High-Gain Harmonic Generation (HGHG) process in a free-electron laser (FEL) is a promising approach to facilitate various coherent nonlinear spectroscopy schemes in the extreme ultraviolet (XUV) spectral range. However, in collinear arrangements using a single nonlinear medium, temporally overlapping seed pulses may introduce nonlinear mixing signals that compromise the experiment at short time delays. Here, we investigate these effects in detail by extending the analysis described in a recent publication (Wituschek et al., Nat. Commun., 11, 883, 2020). High-order fringe-resolved autocorrelation and wave-packet interferometry experiments at photon energies > $23\,$eV are performed, accompanied by numerical simulations. It turns out that both the autocorrelation and the wave-packet interferometry data are very sensitive to saturation effects and can thus be used to characterize saturation in the HGHG process. Our results further imply that time-resolved spectroscopy experiments are feasible even for time delays smaller than the seed pulse duration.Comment: This is accepted version of the article. The Version of Record is available online at https://doi.org/10.1364/OE.40124

Deep neural networks for classifying complex features in diffraction images

Intense short-wavelength pulses from free-electron lasers and high-harmonic-generation sources enable diffractive imaging of individual nano-sized objects with a single x-ray laser shot. The enormous data sets with up to several million diffraction patterns represent a severe problem for data analysis, due to the high dimensionality of imaging data. Feature recognition and selection is a crucial step to reduce the dimensionality. Usually, custom-made algorithms are developed at a considerable effort to approximate the particular features connected to an individual specimen, but facing different experimental conditions, these approaches do not generalize well. On the other hand, deep neural networks are the principal instrument for today's revolution in automated image recognition, a development that has not been adapted to its full potential for data analysis in science. We recently published in Langbehn et al. (Phys. Rev. Lett. 121, 255301 (2018)) the first application of a deep neural network as a feature extractor for wide-angle diffraction images of helium nanodroplets. Here we present the setup, our modifications and the training process of the deep neural network for diffraction image classification and its systematic benchmarking. We find that deep neural networks significantly outperform previous attempts for sorting and classifying complex diffraction patterns and are a significant improvement for the much-needed assistance during post-processing of large amounts of experimental coherent diffraction imaging data.Comment: Published Version. Github code available at: https://github.com/julian-carpenter/airyne

Miniaturized supercapacitors: key materials and structures towards autonomous and sustainable devices and systems

© 2016 The Authors Supercapacitors (SCs) are playing a key role for the development of self-powered and self-sustaining integrated systems for different fields ranging from remote sensing, robotics and medical devices. SC miniaturization and integration into more complex systems that include energy harvesters and functional devices are valuable strategies that address system autonomy. Here, we discuss about novel SC fabrication and integration approaches. Specifically, we report about the results of interdisciplinary activities on the development of thin, flexible SCs by an additive technology based on Supersonic Cluster Beam Deposition (SCBD) to be implemented into supercapacitive electrolyte gated transistors and supercapacitive microbial fuel cells. Such systems integrate at materials level the specific functions of devices, like electric switch or energy harvesting with the reversible energy storage capability. These studies might open new frontiers for the development and application of new multifunction-energy storage elements