Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive and selective technique. It greatly enhances the signal of an analyte compared to classical Raman spectroscopy, due to analyte-substrate interactions. A promising substrate for SERS is boron-doped graphene (B-graphene). At low boron concentrations of โผ1.39 at.%, it has been shown to enhance the Raman signal of simple organic...
NiTi shape memory alloy has become the most widely used shape memory material in industrial, high-tech, and medical applications due to its unique thermal and mechanical properties, primarily represented by the shape memory effect and superelasticity. Due to these unique characteristics, this alloy has been used in numerous practical applications since its discovery in 1963. Despite having...
This study proposes a novel framework for clustering dynamical systems to identify parameter combinations that elicit comparable responses of dependent variables under specified initial conditions. Using self-organizing map (SOM) clustering, trajectories are categorized into distinct behavioral regimes determined by parameter variations. A systematic sampling of parameter spaces produces...
Thermal stability and mechanical performance are crucial criteria in the design of next-generation protective coatings for cutting, drilling, and forming applications. Currently, TiAlN serves as the benchmark coating due to its excellent chemical, mechanical, and thermal stability. Titanium aluminium oxynitride (TiAlON), however, has emerged as a promising alternative, offering an increase in...
Membrane-binding peptides hold considerable promise for applications such as antimicrobials, biosensors, and extracellular vesicle purification. However, their successful implementation in biotechnology requires careful consideration of membrane selectivity. The Opi1 peptide has demonstrated a selective affinity for phosphatidic acidโcontaining membranes, as shown experimentally by Ernst et...
Lipid nanoparticles (LNPs) are widely used as drug delivery systems and have been successfully applied in vaccines such as Onpattro, Comirnaty, and Spikevax. Despite their global success, key questions remain regarding the mechanisms of endosomal drug release from LNPs. Numerous experimental and theoretical studies have addressed this topic. Most previous theoretical studies have been...
For years, the ATLAS experiment is running selection of its workflows (mostly Monte Carlo simulations, which have small inputs and outputs and can run even on tens of cores for hours) at IT4Innovation. As the experiment and its computing evolves, so does constitution of its workflows. Recently, we are more often getting into a situation when there is insufficient number of these jobs while...
Diamond is a wide-bandgap semiconductor with exceptional physical properties, making it highly attractive for applications in power electronics, photovoltaics, nanophotonics, and quantum technologies. Its functionality is often engineered through the introduction of defects such as dopants or vacancies; however, accurate description of defect states remains challenging. Density functional...
Ferrimagnetic iron oxides such as magnetite or maghemite find many applications in magnetic recording, spin-based electronics and biomedicine. However, when reduced to the nanoscale, their long-range spin ordering often collapses, giving rise to surface-driven magnetic disorder. This disruption originates from broken interactions, symmetry and reduced atomic coordination at facets and edges of...
Accurate prediction of physical properties is necessary when developing high-value materials such as pharmaceuticals. At the same time, methods needed to achieve required accuracy, such as periodic density functional theory (DFT), remain commonly used despite being computationally demanding. Given that interest in modelling even larger and more complex systems has only continued to grow, these...
EasyDock 1.0 - an open-source and scalable Python-based tool for fully automated molecular docking. The current version supports popular docking programs, namely Autodock Vina, gnina, and smina. The tool automatically prepares ligands by removing salts, generating initial conformers and stereoisomers, using RDKit, and performing protonation with the open-source program MolGpKa. Ring sampling...
Wave propagation simulations are crucial for planning non-invasive medical treatments such as focused ultrasound therapy. However, these procedures often require multiple high-resolution simulations, leading to significant resource consumption and potential delays in critical treatments. This work presents a method to accelerate simulations performed using the k-Wave toolbox while maintaining...
Transition metal dichalcogenides (TMDs) on metallic substrates, such as Au, exhibit unique interfacial interactions that influence their structural and tribological properties. In this study, we developed a machine learning-based force field using Deep Potential Molecular Dynamics (DPMD) to model TMDs on an Au substrate and the Si tip. The generated force field was validated by computing the...
Investigating hydrogen sorption in hydride-forming materials is essential for advancing a wide range of industrial technologies. Among such materials, LaNi$_5$ is a common candidate due to its ability to accommodate multiple hydride phases. Upon full hydrogenation, LaNi$_5$ forms the stable hydride phase LaNi$_5$H$_7$. Its properties such as lowering absorption and desorption pressures and...
The main challenge in analyzing nonlinear dynamical systems lies in the repetitive and inefficient need to simulate each initial condition and parameter configuration separately. This approach not only increases computational cost but also limits scalability when exploring large parameter spaces. To address this issue, we developed a loop-based numerical methodology that automates the...
Interlayer exchange coupling between two ferromagnetic layers across a spacer layer has been intensively investigated within the last few decades. It was discovered that the interlayer exchange coupling across most 3d, 4d, and 5d nonmagnetic metallic spacer layers oscillates between antiferromagnetic and ferromagnetic as a function of spacer layer thickness (1,2). This discovery enabled the...
Since ab initio molecular dynamics (AIMD) simulations are computationally very expensive to study the properties of 2D layered materials, we utilize machine learning force fields (MLFF) to reduce these high costs. This approach improves the process of force field development without significantly diminishing the accuracy of the quantum-mechanical calculations. Our study focuses on four...
Very strong electromagnetic fields can induce electron-positron pair creation predicted by quantum electrodynamics. A possible way to demonstrate it is via the multiphoton Breit-Wheeler process in strong laser fields. The challenge in this setup is to hold seed particles in the hot-spot region of the reaction. This method using radially polarised laser pulses to trap seed electrons is studied...
With machine learning and its use in science rapidly growing in popularity, the need for high-quality training data is increasing. Most researchers however train their models either on their own data or on curated databases. With the growing emphasis on open science, a large amount of data from other researchers is now openly available, but such data often come without any guarantee of...
Shape-memory alloys are unique materials capable of undergoing large reversible strains and exhibiting the shape-memory effect, which is driven by external changes of temperature. These remarkable properties are based on a martensitic transformation between austenite (high-temperature phase) and martensite (low-temperature phase). The NiTi shape memory alloy has become the most widely used...
Docking and molecular dynamics (MD) are widely used to predict drugโprotein interactions. While docking provides rapid starting structures, MD can equilibrate ligand binding poses at the cost of greater computational demand. Automated pipelines remain limited, particularly for systems with covalently bound cofactors or metals, or for flexible protein docking.
We present an automated workflow...
The ribosome is a macromolecular complex that catalyzes all protein synthesis. It is composed of ribosomal RNA and proteins, which contribute to both its shape and function. The catalytic center of the ribosome, the peptidyl transferase, is where peptide bond formation occurs, and ribosomal proteins were gradually incorporated into this core during evolution. Whether the proteins associated...
Simulating wave propagation with the Fourier collocation method
is computationally intensive due to its reliance on discrete Fourier
transforms (DFTs). While DFTs enable near-minimal spatial dis-
cretization, they scale poorly on modern high-performance com-
puting systems. This work evaluates two multi-GPU strategies for
three-dimensional simulations: a Global FFT approach using...
The protoribosome, carrying the peptidyl transferase center, represents an ancestral core of modern ribosomes. Fragments of several ribosomal proteins, so called rPeptides, extend toward the PTC and stabilize protoribosomal RNA (1).
In this work, we investigate the conformational stability of a protoribosome model from T. thermophilus upon replacement of lysine and arginine residues to...
Atomistic simulations provide a way to observe atomic behavior at the nanoscale level. There are two main approaches: the first is based on quantum mechanics (ab initio simulations), and the second relies on Newton's mechanics (molecular dynamics). However, despite advancements in computer science, including quantum computing, both approaches remain limited. Ab initio simulations are...
Transition metal dichalcogenides (TMDs) are a class of layered materials in which weak interlayer van der Waals forces enable facile sliding, giving rise to an exceptionally low coefficient of friction which effectively vanishes (< 10$^{-3}$) when measured in vacuum. In humid environments, however, frictional properties degrade due to oxidisation at the sliding interface, which increases...
COMPASS Upgrade will be a new tokamak-type device in Prague that is used to maintain plasma reaching extreme temperatures of several keV using magnetic fields of several teslas. Tokamaks (and other devices) aim to enable the possibility of clean, globally available and almost inexhaustible nuclear fusion energy. However, there are many obstacles in the way. This work focuses on erosion of the...
Advances in the development of ultrafast lasers have made picosecond ultrasonics a novel research field which alows to generate and detect acoustic waves with frequencies up to terahertz and wavelengths down to nanometers. Picosecond laser ultrasonics is successfully applied for experimentally study of nanostructures, adhesion of monolayers, and profile inhomogeneity [1, 2]. However, due to...
We are developing an open-source numerical computational suite (https://github.com/HHG-modelling/MMA-HHG-pre-release-2) for modelling high-harmonic generation (HHG) in gaseous media. This process provides a tuneable source of highly coherent XUV radiation, forming attosecond pulses that allow the probing of atomic and molecular processes (such as chemical reactions) at their natural temporal...
Ribosomes are large ribonucleoprotein complexes that drive protein synthesis, a fundamental process for all living systems. During translation, the nascent polypeptide traverses the ribosomal exit tunnel, a narrow passage shaped by both ribosomal RNA and proteins. The tunnel's architecture influences nascent chain folding, interactions, and even stalling (Kolรกล et al., 2024). The narrowest...
Magnetic materials represent a key component in the industry. One of the most common and used magnetic material parameters is magneto-crystalline anisotropy, which takes place in permanent magnets, storage devices, etc. In addition, magnetoelastic behavior is widely used in many applications, such as acoustic actuators, transducers, or sensors, providing desirable fast response and high...
Machine learning based potentials represent a new powerful tool for accurate modelling of complex interatomic interactions in materials. In our work, we apply the high-dimensional neural network (HDNNP) methodology using the atom-centred symmetry function descriptors for the shape memory alloy NiTi in the martensitic phase.
NiTi is a system that poses significant challenges for both...
Many existing tools analyze anisotropic elastic properties using the elastic stiffness tensor, but they often overlook the direct relationship between crystal structure and elastic behavior. Most operate in Cartesian coordinates, which work well for high-symmetry lattices but are less intuitive for lower-symmetry systems where crystallographic directions and planesโdefined by Miller...
We study transverse (kink mode) oscillations in threads of solar prominences, which are large dense, cool plasma structures suspended in the Sunโs corona by magnetic fields. These threads can show both collective and individual behaviour, when threads or groups of threads oscillate with their own periods independently from the rest of the prominence.
Several studies have suggested that...
The aim of this study is to assess how changes in emissions can affect future air-quality in Central Europe, without consideration of changes in future meteorology conditions. In order to do so, two future scenarios were used (RCP4.5 and RCP8.5) for the periods 2026-2035 and 2046-2055. We simulated the current and future air pollution levels using the Weather Research and Forecasting model...
