Separation of motions and vibrational separation of fractions for biocide brass

Sonochemical fabrication of gradient antibacterial materials based on Cu-Zn alloy

At present research, we highlight ultrasonic treatment as a new way to create materials with a gradient change of chemical or physical properties. We demonstrate the possibility to fabricate novel materials with biocide activity based on simple and cheap Cu-Zn alloy. In this research, we propose a green preparative technique for the sonication of an alloy in an alkali solution. The method leads to a significant visual change and differentiation of particles into three different fractions. Due to the chemical micro gradients in media near the solid surface under intensive sonication, fast formation of specific functional groups occurs on the particles' surface. The particles were studied X-ray diffraction analysis (XRD) analysis, the field-emission scanning electron microscope (SEM) as well as electron backscatter diffraction (EBSD) mode, X-ray Photoelectron Spectroscopy (XPS), the differential pulse anodic stripping voltammetry (DPASV) technique. A strong correlation of both methods proves a redistribution of copper ions from Fraction I to Fraction III that influence for the antibacterial properties of the prepared material. The different biocidal activity was demonstrated for each separated Fraction that could be related to their different phase content and ability to release the different types of ions.

When Bubbles Are Not Spherical: Artificial Intelligence Analysis of Ultrasonic Cavitation Bubbles in Solutions of Varying Concentrations

Ultrasonic irradiation of liquids, such as water-alcohol solutions, results in cavitation or the formation of small bubbles. Cavitation bubbles are generated in real solutions without the use of optical traps making our system as close to real conditions as possible. Under the action of the ultrasound, bubbles can grow, oscillate, and eventually collapse or decompose. We apply the mathematical method of separation of motions to interpret the acoustic effect on the bubbles. While in most situations, the spherical shape of a bubble is the most energetically profitable as it minimizes the surface energy, when the acoustic frequency is in resonance with the natural frequency of the bubble, shapes with the dihedral symmetry emerge. Some of these resonance shapes turn unstable, so the bubble decomposes. It turns out that bubbles in the solutions of different concentrations (with different surface energies and densities) attain different evolution paths. While it is difficult to obtain a deterministic description of how the solution concentration affects bubble dynamics, it is possible to separate images with different concentrations by applying the artificial neural network (ANN) algorithm. An ANN was trained to detect the concentration of alcohol in a water solution based on the bubble images. This indicates that artificial intelligence (AI) methods can complement deterministic analysis in nonequilibrium, near-unstable situations.

Topological Data Analysis of Nanoscale Roughness in Brass Samples

Rough surfaces possess complex topographies, which cannot be characterized by a single parameter. The selection of appropriate roughness parameters depends on a particular application. Large datasets representing surface topography possess orderliness, which can be expressed in terms of topological features in high-dimensional dataspaces reflecting properties such as anisotropy and the number of lay directions. The features are scale-dependent because both sampling length and resolution affect them. We study nanoscale surface roughness using 3 × 3, 4 × 4, and 5 × 5 pixel patches obtained from atomic force microscopy (AFM) images of brass (Cu Zn alloy) samples roughened by a sonochemical treatment. We calculate roughness parameters, correlation length, extremum point distribution, persistence diagrams, and barcodes. These parameters of interest are discussed and compared.