The ability to control the morphology of the nanotube deposit formed during the evaporation of a sessile droplet on a substrate is of theoretical and practical interest. Such deposits is required for various applications including nanotechnology, medicine, biotechnology, and optronics. In the experiment of Zhao et al. [J. Colloid Interface Sci. 440, 68 (2015)], an annular deposit was formed near the contact line. The deposition geometry is caused by the coffee-ring effect. This deposit is unusual in its morphology. It changes gradually in space from a disordered structure in the inner part of the ring to an aligned structure of nanotubes close to the periphery. To understand the mechanisms that lead to this, we have developed a mathematical model that takes into account the effects of advection, diffusion, and electrostatic interactions on particle transport. Results of numerical calculations have confirmed that all these factors together have an influence on the formation of such a variable morphology. Qualitative agreement with the experiment is shown for some values of the model parameters.

The work is devoted to the development of an information system ISANM that will be useful for teaching students and applicable in the work of engineers and researchers for automating the analysis of colloidal structure morphology. The ISANM system integrates various analysis methods and is designed prioritize usability, catering primarily to users rather than software developers. This paper outlines the scope of the subject area, reviews selected methods for morphology analysis, and presents the scripts developed for implementing these methods in Python. In the future, new methods and tools will be gradually added to the system for chemical engineers, physicists, and materials scientists. We hope that the system implementation methodology described here will be useful in the implementation of other projects related to training chemical engineers and beyond. The system core is implemented in C#, utilizing the .NET Framework and the MS SQL Server, and is developed within the Microsoft Visual Studio 2019 environment on Windows 10 using the client-server architecture. The system has been deployed on a VDS server using the Ubuntu 20.04 distribution. MS SQL Server is used as the database management system. The system can be accessed at this https URL. Geometric analysis of colloidal structures is significant in applications such as photonic crystals for optoelectronics and microelectronics, functional coatings in materials science, and biosensors for medical and environmental applications. This demonstrates the importance of digitalization in this area to improve the quality of student education.

A number of geometric and topological properties of samples of crack-template based conductive films are examined to assess the degree to which Voronoi diagrams can successfully model structure and conductivity in such networks. Our analysis suggests that although Poisson--Voronoi diagrams are only partially successful in modeling structural features of real-world crack patterns formed in films undergoing desiccation, such diagrams can nevertheless be useful in situations where topological characteristics are more important than geometric ones. A phenomenological model is proposed that is more accurate at capturing features of the real-world crack patterns.

We propose an algorithm generating planar networks which structure resembles a hierarchical structure of desiccation crack patterns.

Using computer simulation, we investigated the dependence of the electrical conductivity of random two-dimensional systems of straight nanowires on the main parameters. Both the resistance of the conductors and the resistance of the contacts between them were taken into account. The dependence of the resistance, $R$, between network nodes on the distance between nodes, $r$, is $R(r) = R_\Box/\pi \ln r + \mathrm{const}$, where $R_\Box$ is the sheet resistance.

The control of the thermocapillary assembly of colloidal particle clusters is important for a variety of applications, including the creation of photonic crystals for microelectronics and optoelectronics, membrane formation for biotechnology, and surface cleaning for laboratory-on-chip devices. It is important to understand the main mechanisms that influence the formation of such clusters. This article considers a two-dimensional mathematical model describing the transfer of particles by a thermocapillary flow in an unevenly heated cell during the evaporation of a liquid. This gave us the opportunity to study one of the main processes that triggers the formation of a particle cluster. Whether the particle will move with the flow or stop at the heater, becoming the basis for the cluster, is determined by the ratio between gravity and the drag force. The results of numerical calculations show that, for small particle concentrations, their fraction entering the cluster decreases as the volumetric heat flux density $Q$ increases. The reason for this is an increase in the thermocapillary flow with an increase in the volumetric heat flux $Q$. It reduces the probability of particles entering the cluster.

Interest in studying the conductive properties of networks made from randomly distributed nanowires is due to their numerous technological applications. Although the sheet resistance of such networks can be calculated directly, the calculations require many characteristics of the system (distributions of lengths, diameters and resistances of nanowires, distribution of junction resistance), the measurement of which is difficult. Furthermore, such calculations can hardly offer an analytical dependence of the sheet resistance on the basic physical parameters of the systems under consideration. Although various theoretical approaches offer such analytical dependencies, they are often based on more or less reasonable assumptions rather than rigorously proven statements. Here, we offer an approach based on Foster's theorem to reveal a dependence of the sheet resistance of dense nanowire networks on the main parameters of such networks. This theorem offers an additional perspective on the effective medium theory and extends our insight.