Effect of nanostructured carbon coatings on the electrochemical performance of Li_1.4Ni_0.5Mn_0.5O_2+x-based cathode materials

• Konstantin A. Kurilenko,
• Oleg A. Shlyakhtin,
• Oleg A. Brylev,
• Dmitry I. Petukhov and
• Alexey V. Garshev

Beilstein J. Nanotechnol. 2016, 7, 1960–1970, doi:10.3762/bjnano.7.187

• lithium diffusion coefficient, a higher specific capacity and lower values of charge transfer resistance, which can be related to the more uniform carbon coatings and to the significant content of sp2-hybridized carbon detected by XPS and by Raman spectroscopy. Keywords: carbon coatings; electrode

• the apparent diffusion coefficient of lithium ions for the pure Li1.4Ni0.5Mn0.5O2+x are in the range from 10−17 to 10−15 cm2·s−1 with a minimal value of 6.8 × 10−17 cm2·s−1 at 3.67 V (Figure 6). Concerning the LNM/C nanocomposites, the variations of D with the applied potential are substantially

• conductivity of this material and the higher values of the Li+ diffusion coefficient. Figure 8 displays the XRD patterns of electrode materials after electrochemical cycling at high discharge currents. It can be seen that the splitting of (018)/(110) reflections is much higher in carbon-coated materials

The self-similarity theory of high pressure torsion

• Yan Beygelzimer,
• Roman Kulagin,
• Laszlo S. Toth and
• Yulia Ivanisenko

Beilstein J. Nanotechnol. 2016, 7, 1267–1277, doi:10.3762/bjnano.7.117

• the concentration, and the function Φ, which depends on the absolute value of the gradient of the concentration and on the radius r, serves as the diffusion coefficient. According to Equation 9, the boundary conditions for Equation 32 are the following: The equation gives another boundary condition

Experimental and simulation-based investigation of He, Ne and Ar irradiation of polymers for ion microscopy

• Lukasz Rzeznik,
• Yves Fleming,
• Tom Wirtz and
• Patrick Philipp

Beilstein J. Nanotechnol. 2016, 7, 1113–1128, doi:10.3762/bjnano.7.104

• , the MSD is then averaged over all diffusing atoms of a given species. The calculated MSD for He, Ne and Ar in HD-PE, HD-PS, HD-PMMA and HD-PFTE are shown in Figure 4. The linear regime in the MSD lasts for 2–3 ns depending on the polymer. For this time range, the diffusion coefficient D can be

• polymers. Before, we will investigate by SD_TRIM_SP how the diffusion coefficient influences the rare gas concentration in the polymers during ion bombardment. Therefore their values have been changed from 1.67 × 10−17 to 1.67 × 10−17 cm2 s−1 . It should be noted that the experimental diffusion

• to 1.67 × 10−12 cm2 s−1 (Figure 6). The transition from swelling to sputtering occurs at a diffusion coefficient of 1.67 × 10−11 cm2 s−1. For diffusion coefficients of 1.67 × 10−11 cm2 s−1 and 1.67 × 10−10 cm2 s−1, implantation profiles with maximum concentrations which do not exceed 20% and 3% are

Voltammetric determination of polyphenolic content in pomegranate juice using a poly(gallic acid)/multiwalled carbon nanotube modified electrode

• Refat Abdel-Hamid and
• Emad F. Newair

Beilstein J. Nanotechnol. 2016, 7, 1104–1112, doi:10.3762/bjnano.7.103

• reversible and diffusion-controlled process according to the Randles–Sevcik [28] equation, where ip is the peak current, n is the number of electron transfers in the reaction (which is equal to 1), D is the molecular diffusion coefficient (cm2/s) in solution, A is the active surface area (cm2), Co is the

• solution at a scan rate of 50 mV/s. It was known that the electrochemical reduction of the ferricyanide ion at the GCE is diffusion-controlled. From Equation 1, the electroactive surface area of the subject electrodes was evaluated taking into account a diffusion coefficient for ferricyanide ion of 7.6

• . The current that passes during τ is measured. The current corresponding to the electrochemical reaction is described by Cottrell's equation [28]: where D is the diffusion coefficient (cm2/s), C is the bulk concentration (mol/dm3), τ is the step duration and n, F, and A have their usual significance

Determination of the compositions of the DIGM zone in nanocrystalline Ag/Au and Ag/Pd thin films by secondary neutral mass spectrometry

• Gábor Y. Molnár,
• Shenouda S. Shenouda,
• Gábor L. Katona,
• Gábor A. Langer and
• Dezső L. Beke

Beilstein J. Nanotechnol. 2016, 7, 474–483, doi:10.3762/bjnano.7.41

• obtained for the effective diffusion coefficient at 280 °C. Since this value is about eight orders of magnitude (!) larger than the bulk diffusion coefficient of Pd in Ag at 280 °C [26] and about two to three orders of magnitude smaller than the Ag GB self-diffusion [29] at the same temperature, they

• concluded that the observed phenomena can be explained by activated bulk diffusion due to a structure of nano-grains with an increased number of defects. We suggest a different explanation, because it is difficult to offer any mechanism for an increase of the bulk diffusion coefficient of many orders of

Molecular machines operating on the nanoscale: from classical to quantum

• Igor Goychuk

Beilstein J. Nanotechnol. 2016, 7, 328–350, doi:10.3762/bjnano.7.31

• probability density P(x,t), which can be written as a continuity equation, , with the probability flux J(x,t) written in the transport form This Smoluchowski equation is an ensemble description and counter-part to the Langevin equation (Equation 11). Here, D is the diffusion coefficient related to temperature

Hydration of magnesia cubes: a helium ion microscopy study

• Ruth Schwaiger,
• Johannes Schneider,
• Gilles R. Bourret and
• Oliver Diwald

Beilstein J. Nanotechnol. 2016, 7, 302–309, doi:10.3762/bjnano.7.28

• reaction can significantly exceed the theoretical value of a complete solid-to-solid transformation. Differences in diffusion coefficient between the reacting species (here Mg2+, and H2O molecules/hydroxide ions) are thus expected to lead to the growth of the Mg(OH)2 layer outwards the cubes, explaining

Continuum models of focused electron beam induced processing

• Milos Toth,
• Charlene Lobo,
• Vinzenz Friedli,
• Aleksandra Szkudlarek and
• Ivo Utke

Beilstein J. Nanotechnol. 2015, 6, 1518–1540, doi:10.3762/bjnano.6.157

• ), the models must be modified to account for the diffusion of all mobile species at the surface. In the case of FEBID or FEBIE performed using a single species of physisorbed precursor molecules “a”, this is achieved simply by adding a diffusion term to Equation 12 [19]: Da is the diffusion coefficient

Current–voltage characteristics of manganite–titanite perovskite junctions

• Benedikt Ifland,
• Patrick Peretzki,
• Birte Kressdorf,
• Philipp Saring,
• Andreas Kelling,
• Michael Seibt and
• Christian Jooss

Beilstein J. Nanotechnol. 2015, 6, 1467–1484, doi:10.3762/bjnano.6.152

• homojunction can then be described within the Shockley theory [37]: where the saturation current density, JS, can be written as Here Dn,p is the diffusion coefficient and Ln,p is the diffusion length for electrons and holes. Far from the junction, the density of charge carriers for completely ionized donors

• the lifetime is determined by recombination and relaxation processes, the mobility is inherent to the material system. From the simple Einstein relation, the diffusion coefficient is proportional to the mobility. This leads to typical diffusion lengths in the µm and nm range for inorganic and organic

The Kirkendall effect and nanoscience: hollow nanospheres and nanotubes

• Abdel-Aziz El Mel,
• Ryusuke Nakamura and
• Carla Bittencourt

Beilstein J. Nanotechnol. 2015, 6, 1348–1361, doi:10.3762/bjnano.6.139

• their early report, Nakamura et al. concluded that the formation of an off-centered, single void during oxidation of nickel is related to the intrinsic properties of nickel itself [32]. They came to such a conclusion by comparing the ratio between the diffusion coefficient of Ni in NiO and the self

• -diffusion coefficient of Ni (i.e., diffusion of Ni ions in Ni) (Figure 5f). Since this ratio is quite low compared to other metals, they concluded that the generation/migration rate of vacancies is well-balanced [32]. This led to the conclusion that when the generation and the migration rate of vacancies

• . This effect was not observed with Cu because the generation rate of vacancies in Cu during oxidation was found to be much faster than the migration rate since the diffusion coefficient of Cu in Cu2O is much higher (up to nine times at 100 °C) than the self-diffusion coefficient of Cu. Thus, in the case

Multiscale modeling of lithium ion batteries: thermal aspects

• Arnulf Latz and
• Jochen Zausch

Beilstein J. Nanotechnol. 2015, 6, 987–1007, doi:10.3762/bjnano.6.102

• at concentrations beyond the dilute limit [9]. To obtain the collective diffusion coefficient is crucial since there is a difference between the self-diffusion coefficients and the collective diffusion coefficient [10]. As will be shown below, it is the collective diffusion coefficient that is

• relevant for the transport of lithium ions in the solid active particle as well as in the liquid electrolyte. The collective diffusion coefficient can be written as a product of a thermodynamic factor, which can be obtained from the chemical potential, and a kinetic coefficient, which is a measure of the

• variables. In this formulation it can be easily seen as well that the diffusion coefficient D at vanishing current j is proportional to the determinant of the mobility matrix B. The requirement of positive entropy production mentioned above is therefore the equivalent of having a positive collective

Nanoporous Ge thin film production combining Ge sputtering and dopant implantation

• Jacques Perrin Toinin,
• Alain Portavoce,
• Khalid Hoummada,
• Michaël Texier,
• Maxime Bertoglio,
• Sandrine Bernardini,
• Marco Abbarchi and
• Lee Chow

Beilstein J. Nanotechnol. 2015, 6, 336–342, doi:10.3762/bjnano.6.32

• diffusion length (cm), and D = 0.06 × exp(−2.47 eV/kT) is the Ge surface diffusion coefficient (cm2 s−1) on Si [33], depending on both the temperature and the annealing time, t. Table 2 presents the annealing parameters. One can distinguish three ranges of thermal treatments: (i) a low annealing TB with TB

The effect of surface charge on nonspecific uptake and cytotoxicity of CdSe/ZnS core/shell quantum dots

• Vladimir V. Breus,
• Anna Pietuch,
• Marco Tarantola,
• Thomas Basché and
• Andreas Janshoff

Beilstein J. Nanotechnol. 2015, 6, 281–292, doi:10.3762/bjnano.6.26

• QDs inside the cellular interior. We use the fast component (typically the first 5–6 data points) to calculate the diffusion coefficient. In the early stages of interaction (4 h after addition), the mobility of particles taken up by the cells was lowest in case of positively-charged QDs (CA–QDs) with

• effect of surface charge was also observed for random and organized motions of internalized particles in the cellular interior, with both the diffusion coefficient and the velocity increasing in the following order: CA–QDs, DHLA–QDs, DPA–QDs. This result could be attributed to a decrease of the vesicle

Characterization of 10,12-pentacosadiynoic acid Langmuir–Blodgett monolayers and their use in metal–insulator–metal tunnel devices

• Saumya Sharma,
• Mohamad Khawaja,
• Manoj K. Ram,
• D. Yogi Goswami and
• Elias Stefanakos

Beilstein J. Nanotechnol. 2014, 5, 2240–2247, doi:10.3762/bjnano.5.233

• polymerization during the formation of the Langmuir layer (shown in Figure 1). The vinyl group of the PDA-polymerized molecules exhibits redox properties when interacting with the HCl molecules in the electrolyte. However, even though it is difficult to calculate the diffusion coefficient, the voltammogram is

Effects of surface functionalization on the adsorption of human serum albumin onto nanoparticles – a fluorescence correlation spectroscopy study

• Pauline Maffre,
• Stefan Brandholt,
• Karin Nienhaus,
• Li Shang,
• Wolfgang J. Parak and
• G. Ulrich Nienhaus

Beilstein J. Nanotechnol. 2014, 5, 2036–2047, doi:10.3762/bjnano.5.212

• obtain the correlation time, τD, of translational diffusion. We precisely measure the diffusion coefficient, D, which changes as protein molecules adsorb onto the NPs, via an increase in τD, by using non-fluorescent proteins and fluorescent NPs. From the Stokes–Einstein equation (see Experimental), the

• . The diffusion time τD is related to the translational diffusion coefficient of the NPs, D = r02/4τD. Before fitting the FCS autocorrelation data to the NP-protein association using Equation 3, the FCS curves of the rhodamine 6G reference sample (with known diffusion coefficient, D = (4.14 ± 0.05) × 10

Rapid degradation of zinc oxide nanoparticles by phosphate ions

• Rudolf Herrmann,
• F. Javier García-García and
• Armin Reller

Beilstein J. Nanotechnol. 2014, 5, 2007–2015, doi:10.3762/bjnano.5.209

• certain intrinsic porosity, which allows water and oxygen to pass at a limited rate (the diffusion coefficient of water being ten times lower than for unhindered diffusion [36]). Only silica layers with a thickness of about 100 nm or more were expected to be completely impenetrable for water and oxygen

The surface properties of nanoparticles determine the agglomeration state and the size of the particles under physiological conditions

• Christoph Bantz,
• Olga Koshkina,
• Thomas Lang,
• Hans-Joachim Galla,
• C. James Kirkpatrick,
• Roland H. Stauber and
• Michael Maskos

Beilstein J. Nanotechnol. 2014, 5, 1774–1786, doi:10.3762/bjnano.5.188

• autocorrelation function, g1(τ), which is a mathematical description of how the scattering signal at a given time t is related to the signal at a later time, t + τ. Information about the self-diffusion coefficient (Ds) is gained from the decay of the autocorrelation function by applying the so-called Siegert

• where slow axial flow velocities are present. Retention will occur according to the average distance of the sample to the accumulation wall, which is determined by the cross flow induced drift and the size-dependent diffusion coefficient of the particles. Thus, particles separate according to their

Magnesium batteries: Current state of the art, issues and future perspectives

• Rana Mohtadi and
• Fuminori Mizuno

Beilstein J. Nanotechnol. 2014, 5, 1291–1311, doi:10.3762/bjnano.5.143

• during magnesium deposition. Another important result was related to the measured low transport numbers of the magnesium ions. For example, the diffusion coefficient of the magnesium ionic species (i.e., Mg2Cl3+) was very low (2.26 × 10−7 cm2 s−1 in 0.2 M solution which is 10 times lower than that

Nanocavity crossbar arrays for parallel electrochemical sensing on a chip

• Enno Kätelhön,
• Dirk Mayer,
• Marko Banzet,
• Andreas Offenhäusser and
• Bernhard Wolfrum

Beilstein J. Nanotechnol. 2014, 5, 1137–1143, doi:10.3762/bjnano.5.124

• /s the diffusion coefficient, F = 96485 C/mol the Faraday constant, and h = 65 nm the nanocavity height. Deviations between expected and recorded current responses in nanocavity devices have been observed previously and are thought to depend on fabrication inhomogeneities and residues as well as

Characterization and photocatalytic study of tantalum oxide nanoparticles prepared by the hydrolysis of tantalum oxo-ethoxide Ta₈(μ₃-O)₂(μ-O)₈(μ-OEt)₆(OEt)₁₄

• Subia Ambreen,
• N D Pandey,
• Peter Mayer and
• Ashutosh Pandey

Beilstein J. Nanotechnol. 2014, 5, 1082–1090, doi:10.3762/bjnano.5.121

• to its distinct properties such as large ion diffusion coefficient and high electrochromic reversibility, high dielectric constant, high refractive index, high chemical stability, large band gap [13][14][15] and photocatalytic activity for overall water decomposition and organic pollutant degradation

Optical modeling-assisted characterization of dye-sensitized solar cells using TiO₂ nanotube arrays as photoanodes

• Jung-Ho Yun,
• Il Ku Kim,
• Yun Hau Ng,
• Lianzhou Wang and
• Rose Amal

Beilstein J. Nanotechnol. 2014, 5, 895–902, doi:10.3762/bjnano.5.102

• diffusion length from Equation 3. where τ, fpeak, L, and D represent the electron lifetime in TiO2, the peak frequency of a large semicircle in Figure 4a, the electron diffusion length, and the diffusion coefficient, respectively. Optical modeling of TNT-based dye-sensitized solar cells The generalized

Modeling and optimization of atomic layer deposition processes on vertically aligned carbon nanotubes

• Nuri Yazdani,
• Vipin Chawla,
• Eve Edwards,
• Vanessa Wood,
• Hyung Gyu Park and
• Ivo Utke

Beilstein J. Nanotechnol. 2014, 5, 234–244, doi:10.3762/bjnano.5.25

• the CNT arrays, we can represent the precursor number density per unit volume, n(x,t), as a function of time, t, and the distance into the CNT array, x. The function n(x,t) obeys the following transport equation: where D(x) is the diffusion coefficient of the precursor molecules inside the CNT array

• that are adsorbed in the volume ΔVi, giving Diffusion coefficient From the kinetic theory of an ideal gas, the mean free path is given by , where d is the molecular diameter, and n is the gas number density. Most precursor molecules have diameters in the range of 10−8–10−7 cm, while precursor

• than the average distance between the CNTs of the vertical array, which is typically smaller than 10−5 cm. The gas transport of this system is thus in the regime of free molecular flow, in which the effective diffusion coefficient for this porous medium is described by Knudsen diffusivity, where dpore

Charge and spin transport in mesoscopic superconductors

• M. J. Wolf,
• F. Hübler,
• S. Kolenda and
• D. Beckmann

Beilstein J. Nanotechnol. 2014, 5, 180–185, doi:10.3762/bjnano.5.18

• length at low temperature where N1 is the density of states in the superconductor, N2 is the real part of the anomalous Green’s function, is the dirty-limit coherence length, and DN is the normal-state diffusion coefficient. The nonlocal conductance due to charge imbalance within the same approximation

• with the simple “no-cooling” approximation Equation 1. Here, we assume that the pair-breaking strength follows the relation ζ = (B/Bc)2/2 for a magnetic field applied parallel to a thin film, and use the diffusion coefficient DN as the single free fit parameter for all curves. These fits are shown as

Constant-distance mode SECM as a tool to visualize local electrocatalytic activity of oxygen reduction catalysts

• Michaela Nebel,
• Thomas Erichsen and
• Wolfgang Schuhmann

Beilstein J. Nanotechnol. 2014, 5, 141–151, doi:10.3762/bjnano.5.14

• inspection under the microscope and by cyclic voltammetry with [Ru(NH3)6]3+ as redox mediator. The size of the disk shaped electrodes was calculated using the diffusion limited steady state current and i = 4nFDcr (n: number of electrons transferred per molecule, F: Faraday constant, D: diffusion coefficient

• , c: bulk concentration of the electroactive species and r: radius of the active electrode surface). A diffusion coefficient of 9.1 × 10−6 cm2s−1 for [Ru(NH3)6]3+ in KCl [43] was used. In all experiments a coiled Pt-wire (Ø 250 µm) counter electrode and a home build miniaturized Ag/AgCl (3 M KCl

The role of electron-stimulated desorption in focused electron beam induced deposition

• Willem F. van Dorp,
• Thomas W. Hansen,
• Jakob B. Wagner and
• Jeff T. M. De Hosson

Beilstein J. Nanotechnol. 2013, 4, 474–480, doi:10.3762/bjnano.4.56

• in the reaction with the electrons and desorption to the gas phase: where g is the sticking factor, F is the gas flux, N0 is the density of adsorption sites in a monolayer, D is the diffusion coefficient, σ(E) is the cross section for dissociation, J is the electron flux, and τ is the residence time