As there is a great demand of 2D metal networks, especially out of gold for a plethora of applications we show a universal synthetic method via phase boundary gelation which allows the fabrication of networks displaying areas of up to 2 cm . They are transferred to many different substrates: glass, glassy carbon, silicon, or polymers such as PDMS. In addition to the standardly used web thickness, the networks are parametrized by their fractal dimension. By variation of experimental conditions, we produced web thicknesses between 4.1 nm and 14.7 nm and fractal dimensions in the span of 1.56 to 1.76 which allows to tailor the structures to fit for various applications. Furthermore, the morphology can be tailored by stacking sheets of the networks. For each different metal network, we determined its optical transmission and sheet resistance. The obtained values of up to 97 % transparency and sheet resistances as low as 55.9 Ω/sq highlight the great potential of the obtained materials.
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http://dx.doi.org/10.1002/anie.202002951 | DOI Listing |
Chaos
January 2025
Emergent Complexity in Physical Systems Laboratory (ECPS), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
The Birman-Williams theorem gives a connection between the collection of unstable periodic orbits (UPOs) contained within a chaotic attractor and the topology of that attractor, for three-dimensional systems. In certain cases, the fractal dimension of a chaotic attractor in a partial differential equation (PDE) is less than three, even though that attractor is embedded within an infinite-dimensional space. Here, we study the Kuramoto-Sivashinsky PDE at the onset of chaos.
View Article and Find Full Text PDFFood Chem
January 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, Jiangsu 214122, China.
The effect of pores distribution on the multi-scale structure, enzyme accessibility, and pasting properties of the waxy maize starch granules with the same degree of hydrolysis were examined. Increased maltogenic α-amylase (MA) dosage obviously increased the shallow pores number and the roughness, whereas extended time increased the holes depth. Despite achieving the same hydrolysis degree and specific surface area, samples with numerous shallow holes exhibited a higher mass fractal dimension, a lower, peak viscosity, final viscosity and setback.
View Article and Find Full Text PDFAims: The aim of this study was to investigate the effect of two different bisphosphonate types on bone using dental panoramic radiographs (DPRs) and to compare these findings with a healthy cohort.
Study Design: Panoramic dental radiographs of bisphosphonate users (30) and healthy individuals (30) were retrospectively evaluated for the study. Regarding FA, standardized 50 × 50 pixel regions of interest (ROI) were identified for each patient.
J Neural Eng
January 2025
Center for Complex Systems and Brain Sciences, Universidad Nacional de San Martin Escuela de Ciencia Y Tecnologia, 25 de Mayo y Francia, San Martín, Buenos Aires, 1650, ARGENTINA.
Objective Magnetic resonance imaging (MRI), functional MRI (fMRI) and other neuroimaging techniques are routinely used in medical diagnosis, cognitive neuroscience or recently in brain decoding. They produce three- or four-dimensional scans reflecting the geometry of brain tissue or activity, which is highly correlated temporally and spatially. While there exist numerous theoretically guided methods for analyzing correlations in one-dimensional data, they often cannot be readily generalized to the multidimensional geometrically embedded setting.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.
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