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Search for "normal distribution" in Full Text gives 37 result(s) in Beilstein Journal of Nanotechnology.

“Sticky invasion” – the physical properties of Plantago lanceolata L. seed mucilage

  • Agnieszka Kreitschitz,
  • Alexander Kovalev and
  • Stanislav N. Gorb

Beilstein J. Nanotechnol. 2016, 7, 1918–1927, doi:10.3762/bjnano.7.183

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  • 7.10 (The MathWorks, Natick, NA, USA). Statistical analysis Statistical analyses were performed with OriginPro 8 (OriginLab Corporation, Northampton, MA, USA). Comparison of means was performed with a two-sample t-test. Normal distribution and constant variance of data were verified before statistical
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Published 05 Dec 2016

Biomechanics of selected arborescent and shrubby monocotyledons

  • Tom Masselter,
  • Tobias Haushahn,
  • Samuel Fink and
  • Thomas Speck

Beilstein J. Nanotechnol. 2016, 7, 1602–1619, doi:10.3762/bjnano.7.154

Graphical Abstract
  • vascular bundles not all groups showed normal distribution, therefore the statistics were computed by Kruskal–Wallis test on mean ranks and only three groups differed significantly (chi-squared = 25.00, 7, P less than 0.001; see Supporting Information File 4 - Inferential statistics). No significant
  • differences in group means were obtained for critical strain (Figure 6B) of the vascular bundles, where normal distribution was not rejected and the multiple comparisons was based on an ANOVA on means (ANOVA; F7,66 = 1.36, P = 2.3) and a post hoc test with Bonferroni adjustment. The normality assumption was
  • each plant species the descriptive statistics for the MoE, including mean, standard error of the mean (SE), standard deviation (STD), median, quartiles, interquartile range (IQR) and a Lilliefors test for normal distribution (H0: normal distribution), were computed in axial and radial direction (see
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Published 07 Nov 2016

Microwave synthesis of high-quality and uniform 4 nm ZnFe2O4 nanocrystals for application in energy storage and nanomagnetics

  • Christian Suchomski,
  • Ben Breitung,
  • Ralf Witte,
  • Michael Knapp,
  • Sondes Bauer,
  • Tilo Baumbach,
  • Christian Reitz and
  • Torsten Brezesinski

Beilstein J. Nanotechnol. 2016, 7, 1350–1360, doi:10.3762/bjnano.7.126

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  • can be fitted by a log-normal distribution with a mean of 3.3 nm and standard deviation of 0.2 nm. The microstructure of the as-prepared ZFO nanoparticles was analyzed in more detail by powder X-ray diffraction (XRD). The XRD pattern in Figure 2 corroborates the SAED results, showing only reflections
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Published 27 Sep 2016

Impact of ultrasonic dispersion on the photocatalytic activity of titania aggregates

  • Hoai Nga Le,
  • Frank Babick,
  • Klaus Kühn,
  • Minh Tan Nguyen,
  • Michael Stintz and
  • Gianaurelio Cuniberti

Beilstein J. Nanotechnol. 2015, 6, 2423–2430, doi:10.3762/bjnano.6.250

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  • approached the 90% quantile, x90,int, which is 90% of the intensity-weighted cumulative distribution. For a log–normal distribution x90,int is derived from the median of the intensity-weighted distribution function x50,int and the standard deviation, σLN [36][37]: The influence of agglomerate size on MB
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Published 17 Dec 2015

Evidence for non-conservative current-induced forces in the breaking of Au and Pt atomic chains

  • Carlos Sabater,
  • Carlos Untiedt and
  • Jan M. van Ruitenbeek

Beilstein J. Nanotechnol. 2015, 6, 2338–2344, doi:10.3762/bjnano.6.241

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  • giving rise to variations in the barrier. The tensile force was assumed to be given by a normal distribution centred at 0.95 nN, and a width of 0.3 nN. A simulation of breaking events based on these assumptions reproduces the main characteristics of the second peak in the experimental distribution
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Published 09 Dec 2015

Electrical properties and mechanical stability of anchoring groups for single-molecule electronics

  • Riccardo Frisenda,
  • Simge Tarkuç,
  • Elena Galán,
  • Mickael L. Perrin,
  • Rienk Eelkema,
  • Ferdinand C. Grozema and
  • Herre S. J. van der Zant

Beilstein J. Nanotechnol. 2015, 6, 1558–1567, doi:10.3762/bjnano.6.159

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  • conductance axis. The histograms show regions of high counts above 1G0, due to stable atomic configurations of the gold electrodes. In the sub-G0 region, the most probable conductance value of each molecule is extracted from the peaks in the histograms, fitted by a log-normal distribution. In this
  • distribution, the logarithm of the random variable is normally distributed and the two fit parameters are μ, the location parameter, and σ, the scale parameter, respectively related to the mean and the geometric standard deviation of the normal distribution. The parameters extracted from the fit are listed in
  • an asymmetric peak, with a tail at larger energies. To quantify injection barrier and coupling we fit each parameter distribution to a log-normal distribution, as shown in Section 3 of Supporting Information File 1. We calculate subsequently the geometric mean of each distribution corresponding in a
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Published 17 Jul 2015

The convenient preparation of stable aryl-coated zerovalent iron nanoparticles

  • Olga A. Guselnikova,
  • Andrey I. Galanov,
  • Anton K. Gutakovskii and
  • Pavel S. Postnikov

Beilstein J. Nanotechnol. 2015, 6, 1192–1198, doi:10.3762/bjnano.6.121

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  • an organic layer coating of 10 ± 2 nm. The ZVI NP size distribution was calculated by visual particle counting with no less than 500 particles and fitted to a log–normal distribution with a number-based geometric standard deviation of 1.6 according to [22][31]. The mean particle core size was
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Published 21 May 2015

Observing the morphology of single-layered embedded silicon nanocrystals by using temperature-stable TEM membranes

  • Sebastian Gutsch,
  • Daniel Hiller,
  • Jan Laube,
  • Margit Zacharias and
  • Christian Kübel

Beilstein J. Nanotechnol. 2015, 6, 964–970, doi:10.3762/bjnano.6.99

Graphical Abstract
  • ultrathin layers suffer from significant electron beam damage that needs to be minimized in order to image the pristine sample morphology. Finally we demonstrate how the silicon nanocrystal size distribution develops from a broad to a narrow log-normal distribution, when the initial precipitation layer
  • -normal distribution. The results strongly reflect the ability to control the Si NC size by geometrical one-dimensional confinement of the SRON layers. Furthermore, the influence of the SRON stoichiometry on Si nanoparticle formation is demonstrated in Figure 4c–e. Interestingly, increasing the Si excess
  • nm SiO0.93), (b) S6 (4.5 nm SiO0.93), (c) S7 (3.5 nm SiO0.93), (d) S8 (3.5 nm SiO0.85), (e) S9 (3.5 nm SiO0.64). List of TEM membrane samples fabricated within this work. Extracted parameters from the EFTEM analysis, dNC indicates the maximum of the log-normal distribution fit, whereas ANC is the Si
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Published 15 Apr 2015

Ni nanocrystals on HOPG(0001): A scanning tunnelling microscope study

  • Michael Marz,
  • Keisuke Sagisaka and
  • Daisuke Fujita

Beilstein J. Nanotechnol. 2013, 4, 406–417, doi:10.3762/bjnano.4.48

Graphical Abstract
  • dimensions were determined by fitting these cross sections with a rectangular function. After fitting a large number (79–150) of clusters randomly selected from several scanning areas for each experiment, height and width histograms were plotted (not shown). The resulting histograms showed a monomodal normal
  • distribution for the diameter and the height of the clusters. To determine the mean values for each experiment, the histograms were fitted with Gaussian curves, and details are given below. The relative coverage of the surface and the number of clusters were extracted by implementing the appropriate options in
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Published 28 Jun 2013

Formation of SiC nanoparticles in an atmospheric microwave plasma

  • Martin Vennekamp,
  • Ingolf Bauer,
  • Matthias Groh,
  • Evgeni Sperling,
  • Susanne Ueberlein,
  • Maksym Myndyk,
  • Gerrit Mäder and
  • Stefan Kaskel

Beilstein J. Nanotechnol. 2011, 2, 665–673, doi:10.3762/bjnano.2.71

Graphical Abstract
  • equation describes the growth rate of larger particles, which is known as Ostwald ripening, resulting in the well-known log-normal distribution of the particle sizes. Taking into account, that D = ƒ(1 = ptotal, Tx), with 1 ≤ x ≤ 2, one can give the following proportionalities for the growth rate of a
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Published 07 Oct 2011

Effect of large mechanical stress on the magnetic properties of embedded Fe nanoparticles

  • Srinivasa Saranu,
  • Sören Selve,
  • Ute Kaiser,
  • Luyang Han,
  • Ulf Wiedwald,
  • Paul Ziemann and
  • Ulrich Herr

Beilstein J. Nanotechnol. 2011, 2, 268–275, doi:10.3762/bjnano.2.31

Graphical Abstract
  • distribution generated under these conditions was examined by scanning electron microscopy (SEM) and atomic force microscopy (AFM). Figure 1 shows a representative sample of Fe nanoparticles deposited on a silicon wafer. The particle diameters follow a log-normal distribution, typical for the gas condensation
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Published 01 Jun 2011

Functional morphology, biomechanics and biomimetic potential of stem–branch connections in Dracaena reflexa and Freycinetia insignis

  • Tom Masselter,
  • Sandra Eckert and
  • Thomas Speck

Beilstein J. Nanotechnol. 2011, 2, 173–185, doi:10.3762/bjnano.2.21

Graphical Abstract
  • ). Therefore parametric tests (normal distribution) or non-parametric tests (no normal distribution) were used for calculating statistical significance of parameter correlation or difference amongst groups (Table 1). - The (parametric) ‘One Way Analysis of Variance’ or the (non-parametric) ‘Kruskal–Wallis One
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Published 24 Mar 2011
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