Morphology-driven gas sensing by fabricated fractals: A review

• Vishal Kamathe and
• Rupali Nagar

Beilstein J. Nanotechnol. 2021, 12, 1187–1208, doi:10.3762/bjnano.12.88

• , morphologies, and gas analytes. The focus is to investigate the morphology-driven gas response of these fab-fracs and identify key parameters of fractal geometry in influencing gas response. Fab-fracs with roughened microstructure, pore-network connectivity, and fractal dimension (D) less than 2 are projected

• to be possessing better gas sensing capabilities. Fab-fracs with these salient features will help in designing the commercial gas sensors with better performance. Keywords: adsorption sites; fabricated fractal; fractal dimension; gas sensor; morphology; pore network; recovery time; response time

• , namely fractal dimension (D), lacunarity (L), and connectivity (Q), that describe geometric features. Figure 2a shows the examples of different fractal clusters with varying values of D and L [48]. While D measures the complexity of a system, L measures the morphological inhomogeneity of fractals. The

Irradiation-driven molecular dynamics simulation of the FEBID process for Pt(PF₃)₄

• Alexey Prosvetov,
• Alexey V. Verkhovtsev,
• Gennady Sushko and
• Andrey V. Solov’yov

Beilstein J. Nanotechnol. 2021, 12, 1151–1172, doi:10.3762/bjnano.12.86

The different ways to chitosan/hyaluronic acid nanoparticles: templated vs direct complexation. Influence of particle preparation on morphology, cell uptake and silencing efficiency

• Arianna Gennari,
• Julio M. Rios de la Rosa,
• Erwin Hohn,
• Maria Pelliccia,
• Enrique Lallana,
• Roberto Donno,
• Annalisa Tirella and
• Nicola Tirelli

Beilstein J. Nanotechnol. 2019, 10, 2594–2608, doi:10.3762/bjnano.10.250

• all a higher aspect ratio (Rg/RH) and a lower fractal dimension. We then compared the kinetics of uptake and the (antiluciferase) siRNA delivery performance in murine RAW 264.7 macrophages and in human HCT-116 colorectal tumor cells. The preparative method (and therefore the internal particle

• for a hard, uniform sphere, 1.0 for vesicles with thin walls (hollow spheres), close to 1.5 for random polymer coil conformations [23][24]. Fractal dimension (D). When applied to particulates, the fractal geometry analysis is another important morphological indicator. For example, aggregation of

• colloidal suspensions typically produces objects for which the mass can be expressed as fractal power of the size (mass fractals [25][26]), i.e., where Dm (≤3) is the so-called mass fractal dimension of the particle aggregate system [27]. For instance, this parameter takes values greater than 2.5 for

The importance of design in nanoarchitectonics: multifractality in MACE silicon nanowires

• Stefania Carapezzi and
• Anna Cavallini

Beilstein J. Nanotechnol. 2019, 10, 2094–2102, doi:10.3762/bjnano.10.204

• from aggregative processes, which are omnipresent in nature, have been characterized by their fractal dimension [21][22][23] that contains information about their geometrical structure at multiple scales. However, sometimes the richness of the organization of shape is such that it is impossible to

• Analysis Let the fractal object F be a subset of the d-dimensional Euclidean space , which is the physical support of F, and be covered by a d-dimensional grid of length scale ε. The box-counting (BC) fractal dimension, or capacity, DBC is defined as where N(ε) is the number of grid elements that overlap

• )fractal a single fractal dimension is able to characterize it across all the length scales [20]. For the deterministic fractals, which are mathematically constructed objects, the scale invariance holds for all scales. Well-known examples are Cantor set and Koch’s curve [20]. Instead, natural objects and

Features and advantages of flexible silicon nanowires for SERS applications

• Hrvoje Gebavi,
• Vlatko Gašparić,
• Dubravko Risović,
• Nikola Baran,
• Paweł Henryk Albrycht and
• Mile Ivanda

Beilstein J. Nanotechnol. 2019, 10, 725–734, doi:10.3762/bjnano.10.72

• . The morphology changes were described by fractal dimension and lacunar analyses and correlated with the duration of Ag plating and SERS measurements. SERS examination showed the optimal intensity values for SiNWs thickness values of 60–100 nm. That is, when the flexibility of the self-assembly SiNWs

• all experiments, a long-working-distance 50×/0.75 objective was used. The exposition time was 10 or 20 s per scan. For the determination of fractal dimension and lacunarity, we used the ImageJ software [25] with the FracLac plugin. The data were extracted from grey-scale images using ‘Box Counting

• – ‘Differential volume Plus1’ for grey-scale image analyses with “black background” as fixed option. The program operates with the equation: D = 3 − (s/2), where s is the regression-line slope, and for the average fractal dimension, where the summation is over all grids. Results and Discussion Dependence of SERS

Heating ability of magnetic nanoparticles with cubic and combined anisotropy

• Nikolai A. Usov,
• Mikhail S. Nesmeyanov,
• Elizaveta M. Gubanova and
• Natalia B. Epshtein

Beilstein J. Nanotechnol. 2019, 10, 305–314, doi:10.3762/bjnano.10.29

• structure of a fractal cluster of nanoparticles is characterized by the relation where Np is the total number of the nanoparticles in the cluster, Df is the fractal dimension, and kf is the the fractal prefactor. The radius of gyration Rg is defined as the mean square of the distances between the particle

• with fractal dimension Df = 1.9 and prefactor kf = 1.7. The inset shows an isolated magnetite nanoparticle of diameter D covered with a nonmagnetic shell of thickness tsh. a) Low frequency hysteresis loops of dilute clusters of spherical magnetite nanoparticles with cubic anisotropy and nonmagnetic

Mechanism of silica–lysozyme composite formation unravelled by in situ fast SAXS

• Tomasz M. Stawski,
• Daniela B. van den Heuvel,
• Rogier Besselink,
• Dominique J. Tobler and
• Liane G. Benning

Beilstein J. Nanotechnol. 2019, 10, 182–197, doi:10.3762/bjnano.10.17

• for Seff(q,ri) (Equation 17) is expressed as the sum between the structure function of an aggregate (“template”), Sagg(q), and the structure factor of the internal arrangement of the aggregate, Sint(q), which in our case becomes subsisted by SSHS(q) (Equations 5–14): where D is a fractal dimension

• evolution of the fractal dimension (parameter D; Figure 4E) suggests that initially (up to 50 s), the aggregates have a relatively open morphology with D < 2.4 and characterized by a limited contribution of due to ν < 0.1 (Figure 4C). Afterwards (after more than 50 s), the aggregates reached an

• , indicates an internal densification and ordering. This is also reflected by the fact that parameter D reaches a stable and relatively high value of ca. 2.4, which is characteristic for denser mass fractals. Such a fractal dimension for silica–lysozyme aggregates was previously reported [16][23] and can be

A comparative study of the nanoscale and macroscale tribological attributes of alumina and stainless steel surfaces immersed in aqueous suspensions of positively or negatively charged nanodiamonds

• Colin K. Curtis,
• Antonin Marek,
• Alex I. Smirnov and
• Jacqueline Krim

Beilstein J. Nanotechnol. 2017, 8, 2045–2059, doi:10.3762/bjnano.8.205

• σ LH, where H is the roughness exponent whose value lies between 0 and 1. Fractal surfaces are often characterized by self-affine fractal dimension D = 3 − H [31][32][33]. Self-affine surfaces have an upper horizontal cut-off length (the lateral correlation length (ξ)) above which the rms roughness

• substantial increases in µk. Substantial increases in µk were observed for the stainless steel surfaces exposed to the +ND suspensions while alumina surfaces showed only modest to negligible increases in µk. The data do not appear to correlate with the σs or fractal dimension D of the samples [42], which were

• ); −ND and water (e and f). QCM frequency (+/−15 Hz) and resistance shifts (+/−1 Ω) in air before and after 60 min of oscillation in aqueous ND suspensions. The equivalent surface coverage of 25 nm clusters is also reported (+/−1 × 1010 clusters/cm2). Saturated rms roughness σs (+/−0.1 nm) and fractal

Needs and challenges for assessing the environmental impacts of engineered nanomaterials (ENMs)

• Michelle Romero-Franco,
• Hilary A. Godwin,
• Muhammad Bilal and
• Yoram Cohen

Beilstein J. Nanotechnol. 2017, 8, 989–1014, doi:10.3762/bjnano.8.101

Effect of Anderson localization on light emission from gold nanoparticle aggregates

• Mohamed H. Abdellatif,
• Marco Salerno,
• Gaser N. Abdelrasoul,
• Ioannis Liakos,
• Alice Scarpellini,
• Sergio Marras and
• Alberto Diaspro

Beilstein J. Nanotechnol. 2016, 7, 2013–2022, doi:10.3762/bjnano.7.192

• particles aggregate, the aggregate mass m increases with the aggregate radius r according to rD, where D is the fractal dimension, which describes the complexity of the fractal object [7]. The interaction of two aggregates [23][24] of mass m and m’ can be described in terms of a kinetic parameter KB defined

• as follows [25]: where μ is the viscosity of the medium, k is the Boltzmann constant, and T is the absolute temperature. KB describes the Brownian aggregation rate at temperature T as a function of both m and D, the fractal dimension of the aggregate. Accordingly, the shift in spectral absorption due

• case of aggregated systems, the appearance of the localized surface plasmon is related the fractal dimension of the aggregates. Anderson localization is responsible for enhancing the localized field, and hence, it appears in the PL emission [43]. The localized enhanced field gives rise to a PL emission

A new approach to grain boundary engineering for nanocrystalline materials

• Shigeaki Kobayashi,
• Sadahiro Tsurekawa and
• Tadao Watanabe

Beilstein J. Nanotechnol. 2016, 7, 1829–1849, doi:10.3762/bjnano.7.176

• boundary network, as seen from Figure 12. The longer percolation path composed of intergranular corrosion susceptive, random boundaries is characterized by the higher fractal dimension of MRBC. This finding has provided us with experimental evidence that the fractal dimension for MRBC, DR is useful as a

• tool for quantitative evaluation of the random boundary connectivity controlling the intergranular corrosion susceptibility in polycrystalline materials. Figure 13 shows the relationship between the fractal dimension for MRBC, DR and the fraction of random boundaries, FR, or low-Σ CSL boundaries, FΣ

• , even if the value of FR or FΣ would be kept similar, suggesting the path of percolation is more irregularly bent depending on the connectivity of random weak boundaries. The fractal dimension for MRBC, DR may include the effect of a spread of the grain size distribution together with the effect of GBCD

Surface topography and contact mechanics of dry and wet human skin

• Alexander E. Kovalev,
• Kirstin Dening,
• Bo N. J. Persson and
• Stanislav N. Gorb

Beilstein J. Nanotechnol. 2014, 5, 1341–1348, doi:10.3762/bjnano.5.147

• dashed line denoted by b is the power spectra used in the calculations presented below in Figure 9), and correspond to a self-affine fractal surface with a fractal dimension of Df = 3 – H = 2.14 in the AFM region, a total surface area of Atot = 1.3A0 (where A0 is the nominal or projected surface area