Study of the Leidenfrost Effect on Heterogeneous Surfaces of Complex Structure

This work is devoted to a research of water droplets that are put in-between two parallel metal strings the distance between which is comparable to linear size of the droplet. Strings are heated by Joule heating to temperatures that exceed critical temperatures of nucleate and film boiling. Different configurations of strings’ side surface have been tested: smooth and with winding made of the same material (intermittent and uninterrupted). Experiments have shown that droplets on these types of surface do not boil away quickly or fall down. Instead they displayed behavior that can be described as floating, either stable or with directed motion, depending on surface structure or relief. Multiple experiments have shown that it is quite similar to Leidenfrost effect demonstrated on a flat overheated surface by liquids.

Mechanistic insights into the adsorption of methylene blue by particulate durian peel waste in water

This study aims to investigate the adsorption of methylene blue (MB) over particulate durian peel waste, which is chemically-activated with hydrogen peroxide. The equilibrium data is well-described by the Freundlich isotherm model, which outlines where the MB adsorption takes place predominantly on multilayers and heterogeneous surfaces of the biosorbent. The Freundlich adsorption constants, KF and n, are 11.06 L/g and 2.94, respectively. Thermodynamic data suggests that the MB adsorption occurs spontaneously and exothermically. The enthalpy and entropy for the MB adsorption are obtained as 10.26 kJ/mol and 0.058 kJ/mol K, respectively, in the temperature range of 303–323 K. Based on the stepwise desorption method, the adsorption of MB is dominated by physical interactions, particularly hydrogen bonding.

Solving the Issue of Discriminant Roughness of Heterogeneous Surfaces Using Elements of Artificial Intelligence

This work deals with investigative methods used for evaluation of the surface quality of selected metallic materials’ cutting plane that was created by CO2 and fiber laser machining. The surface quality expressed by Rz and Ra roughness parameters is examined depending on the sample material and the machining technology. The next part deals with the use of neural networks in the evaluation of measured data. In the last part, the measured data were statistically evaluated. Based on the conclusions of this analysis, the possibilities of using neural networks to determine the material of a given sample while knowing the roughness parameters were evaluated. The main goal of the presented paper is to demonstrate a solution capable of finding characteristic roughness values for heterogeneous surfaces. These surfaces are common in scientific as well as technical practice, and measuring their quality is challenging. This difficulty lies mainly in the fact that it is not possible to express their quality by a single statistical parameter. Thus, this paper's main aim is to demonstrate solutions using the cluster analysis methods and the hidden layer, solving the problem of discriminant and dividing the heterogeneous surface into individual zones that have characteristic parameters.