Úroveň pokročilosti: Introductory Topic

Detection of pathogens or antibodies against pathogens using the series of LSPR active nanocomposites

The main aim of this study is to develop a new detection system for selected bacteria and viruses, as well as their proteins and antibodies against them. The detection system is focused on the localized surface plasmon resonance (LSPR) where pathogen/protein/antibody attached to the LSPR sensors (containing metal nanoparticles) changes the optical and electrical characteristics.…

Utilization of immobilized factors for the differentiation of primary osteoblasts

Tissue cultures are a focus of research in various fields as biology, chemistry, immunology, and medicine. Typically, so-called immortalized cultures are used—these are cell cultures that can multiply indefinitely but are modified in certain ways and therefore differ from cells in actual tissues, such as various cancer cells. Recently, the use of so-called primary cells,…

Functional nanolayers for the real world

The student will become familiar with the procedures for the preparation, characterization, and application of functional nanolayers with so-called antifouling properties during their internship, which can have wide applications in the real world. They will learn methods such as post-modification of polymer layers to anchor bioreceptors to the surface, achieving targeted functional properties of the…

Application of Cohesive Elements in Modeling Fracture of Heterogeneous Materials

The fracture process of concrete is a complex mechanism influenced by its highly heterogeneous internal structure: matrix/cement paste, aggregate, and pores. Damage development occurs at the interface between the cement paste and aggregate, where microcracks can form. The offered internship will focus on 2D/3D numerical modeling of this process using cohesive elements available in ANSYS…

Determining the endurance life of selected construction materials

Current methods for determining the fatigue life of concrete structures focus on reducing stresses in structural elements. However, this approach only considers the degradation of mechanical properties due to cyclic loading and not the gradual development of microcracks. This topic is primarily concerned with the experimental determination of the fatigue life of construction materials, particularly…

Materials for Efficient Hydrogen Storage

Efficient hydrogen storage is a challenge of the future. The aim of this work will be primarily the preparation of materials for hydrogen storage, creating graphs from measured data, and possibly assisting with their processing. At the same time, the student will also become familiar with working with an electron microscope. https://www.ipm.cz/

Measurement of the speed of crack propagation in a PE pipe

A well mapped crack propagation mechanism is the basis for accurate lifetime prediction of various components. While crack propagation rate measurement techniques are relatively well developed for metallic materials and the mechanisms are well described, this is not the case for polymeric materials. This work focuses on the measurement of crack propagation rate in various…

Local deformation mapping with 4D STEM software

4D STEM is an advanced transmission electron microscopy technique that simultaneously records a 2D diffraction pattern for each individual image point. Analysis of these patterns can then provide a wealth of information about the phase composition, crystallographic orientation and spatial distribution of microscopic deformations. During the internship the student will learn the basics of data…

Application of deep learning methods for simulation and data evaluation

During the internship, the student will be introduced to the basic algorithms of deep learning and the theoretical background of these algorithms. Using selected examples, you will learn how to use modern software tools to implement machine and deep learning algorithms on massively used hardware multiprocessor CPU/GPU platforms.The goal of the internship is to enable…

Explanatory models for the interactive development of scientific theories

Machine learning methods are already a common part of scientific practice. However, the most accurate models are currently black-box models, where it is not easy to determine how the model works. It is possible that even accurate predictions are based on misinterpretation of data, for example due to incomplete training data. Explanable machine learning models…