We would like to thank all applicants for computation time within the 23^rd Open Access Grant Competition.

A total of 98 463 500 core hours were requested.  Considering productive use to the resources, several projects were subject to mild allocation reductions.

All projects underwent technical evaluations and evaluation of the registered publications per project ratio.

The Allocation Commission based the allocation decisions on scientific excellence, computational readiness, and socioeconomic impact. In addition to the score assigned by the reviewers, the Commission also took into account (with a weight of 50%) the registered publications per project ratio.  The registered publications per project ratio is defined as a number of publications registered in the last 3 years divided by the number of past OPEN projects that were concluded more than 1 year ago but less than 4 years ago. On average 1.0 publication is expected per completed project. Projects in the extent of 10% of requested resources were not subject to peer-review. In such a case, the committee assumed the highest score on scientific excellence, computational readiness, and socioeconomic impact. In case of new users, the committee assumed the highest score on theregistered publications per project ratio. Low registered publications per project ratio was the primary cause of significant allocation cuts.

The Allocation Commission acknowledged high scientific and technical level of the submitted projects. From the maximum score of 30 points, the projects averaged 24, at minimum of 17 points. Seven of the projects exceeded 25 points.

Among the 50 projects, including 2 multi-year in first period, a total of 93 146 000 core hours were allocated. Projects that were not subject to peer-review represent 8 759 000  (9.4%) of the allocated resources.

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The Allocation Commission decided on the allocations within the 23^nd Open Access Grant Competition as follows:

Researcher: Martin Friak
Project: Properties of Nanoparticles Intended for Medical Applications
Allocation: 1 800 000 jádrohodin
Abstract: Nanoparticles are currently intensively used in the medical science, for example, in the hyperthermia treatment, or for targeted drug delivery. It is expected that the use and importance of nanoparticles in medical science will only grow in future. As the chemical binding properties of nanoparticle surfaces with respect to the attached molecules of medicine depend on the local characteristics of surface atoms as well as nanoparticle size and shape, a detailed knowledge of these characteristics is needed. The proposed project aims at theoretically studying these properties in the case of magnetic magnetite nanoparticles that will be prepared by a novel preparation technique. The calculations will complement experiments that will be performed within a bilateral Czech-Russian project supported by the Czech Science Foundations till the end of December 2023.

 

Researcher: Jan Bohacek
Project: Centrum výzkumu nízkouhlíkových energetických technologií CZ.02.1.01/0.0/0.0/16_019/0000753
Allocation: 132 000 jádrohodin
Abstract: Shell-and-tube heat exchangers can be found in countless applications. Heat transfer surfaces are in many of them represented by a bank of tubes. The crossflow is subjected to a pressure drop, which is an essential parameter for an optimal design. For decades, a few empirical formulas from several handbooks have been continuously used by many engineers and researchers worldwide. The formulas were originally developed by fitting vast data collected from measurements with steel rods. Nowadays, the popularity of using non-metallic components such as those made of various plastics is on increase. Generally, they are significantly less stiff than metallic counterparts, which makes them more prone to flow-induced vibrations. Self-exciting oscillations will result in remarkable increase in drag coefficients. Therefore, it is of urgent interest to revise the existing formulas for pressure drop.

 

Researcher: Martin Beseda
Project: Modeling of Collision Processes in Low-Temperature Plasma II
Allocation: 4 367 000 jádrohodin
Abstract: This project is meant to cover the majority of the necessary computational expenses of the DGS project  Modeling of Collision Processes in Low-Temperature Plasma. Considering its similar content to OPEN-20-20 and OPEN-22-21, the relevant parts will be cited in this proposal. Nowadays, applications of low-temperature plasma are a topic of interest in areas like surface treatment [1], food industry [2], and medicine [3,4,5,6] with the last one motivating our current research efforts. This project will be a direct continuation of our previous research efforts, following up Van de Steen’s work [7,8,9,10] and several OPEN projects. As our current understanding of processes occurring in medicinal applications is not sufficient to tune the plasma for specific purposes[11], we aim to describe the processes in detail from the creation phase to the moment of application in the future. As the ionization and collisions of atomic and molecular ions have been covered already, we aim to continue with a) calculations of transport properties of collision complexes created by interactions of carrier-gas ions with the air and b) modeling of molecular ions formation. Both of these goals are tightly entangled with two double-degree Ph.D. theses co-directed by VSB-TUO and Université Toulouse III - Paul Sabatier, France, following the existing long-time collaboration of our team with LAPLACE, LCPQ, and LCAR research laboratories of the French university.

 

Researcher: Matúš Labaj
Project: Investigation of the Pulsar Radio Emission by the means of Electron-Positron Cyclotron Maser
Allocation: 250 000 jádrohodin
Abstract: The problem of power exhaust is one of the grand challenges of nuclear fusion research today. In order to understand the physics phenomena occurring in the scrape-off layer and divertor regions of tokamaks, it is essential to correctly determine the divertor plasma parameters, which are typically measured by electrostatic probes. However, different probe techniques and methods of analysis can yield conflicting results. The aim of this project is to use particle-in-cell modelling to investigate the peculiarities of Langmuir probe operation in magnetised plasma, in particular the sheath expansion effect for domed probes located in the divertor region of tokamak COMPASS.

 

Researcher: Michael Komm
Project: Particle-in-cell simulations of divertor Langmuir probes in COMPASS tokamak
Allocation: 268000 jádrohodin
Abstract: Skyrmions are particle-like topological defects in magnetic textures which emerge in certain class of magnetic materials under given external conditions. Due to their high stability, skyrmions can be efficiently manipulated by magnetic fields and electric currents. This makes skyrmions hot candidates for information carriers in future computational devices, which can operate at low energy costs and high efficiency. Therefore, research of skyrmions and their ability to move and interact is crucial for development of novel spintronic applications.
In our project, we focus on the study of ordered systems of skyrmions, which are known as skyrmion lattice. Hexagonal skyrmionic lattice can be stabilized in certain range of external magnetic field, and temperature. In order to identify the boundaries between the skyrmion lattice and other phases, we shall develop a new machine learning technique, which will be able to fasten the construction of the phase diagram. Second, we shall draw our attention to study of magnetization dynamics of a single topological defect inside a skyrmion lattice, which might open new possibilities towards utilizing skyrmion lattices in spintronic devices.

 

Researcher: Matus Dubecky
Project: Many-body physics of 2D materials II.
Allocation: 5 960 000 jádrohodin
Abstract: MXenes represent an important class of layered two-dimensional (2D) transition metal carbide/nitride materials, important for their advantegeous properties, like, e.g.,  structural stability or tunable band gap. Accurate modeling of their electronic and optical properties poses a challenge to the traditional mean-field methods like DFT for the presence of many-body effects. This project focuses on use of the reference stochastic quantum many-body method, fixed-node diffusion quantum Monte Carlo, for benchmark electronic structure computations of fundamental gap of promising MXene systems. In addition to the accurate estimate of a band gaps of practical importance and insights into MXene many-body physics, the results will serve as a guide toward selection of an appropriate mean-field model for scalable large-scale simulations of these promising materials.

 

Researcher: Michal Merta
Project: Development of BEM-based solvers V
Allocation: 250 000 jádrohodin
Abstract: One can choose from several numerical methods for modelling natural phenomena occurring in the real world, let us mention, e.g., the finite element method or the finite volume method. The main features of the boundary element method (BEM) make it well suited for problems stated on unbounded domains (such as sound or electromagnetic wave scattering) or shape optimization problems. Within the previous projects, we have developed a BEM-based solver for the time-dependent heat equation capable of parallelization across compute nodes of the cluster. The current project mainly aims at extending it to support solution with adaptive meshes. The global space-time approach leads to the possibility of parallelization both in space and time thus improves the scalability on current and future supercomputers. 

 

Researcher: Sergiu Arapan
Project: Predicting the solid-liquid transition in Li-Be-F systems: a combined DFT and ML approach
Allocation: 5 100 000 jádrohodin
Abstract: The melting phase transition is one of the most fundamental physical processes. The melting properties of materials are important in many fields, including metallurgy, nuclear technology, chemical engineering, etc. In the context of Earth sciences, the melting properties of minerals form the basis for understanding the Earth’s thermal structure, dynamics, and evolution. The melting point is a highly relevant quantity for the efficient and safe operation of the new generation of Molten Salt Nuclear Reactors (MSR), which are regarded as a reliable source of clean, safe, and cost-effective energy. MSRs are fueled with uranium or plutonium fluorides dissolved in a mixture of molten fluorides, with Li and Be fluorides considered to achieve the highest energy conversion. Within the current project, we aim to study the melting transition of LiF and BeF2 salts as well as their mixture by means of numerical simulations. A precise prediction of melting properties requires calculating highly accurate free energies. Ab-initio calculations can accurately describe the melting transition but are very time and resource consuming. From the other side, it is quite a challenge to quantitatively describe material melting within classical Molecular Dynamics because of the quality of the interatomic potentials. Here we intend to overcome this problem by using a Machine Learning approach to develop accurate inter-atomic potentials for Li-Be-F systems from ab-initio data.

 

Researcher: Luigi Cigarini
Project: Band nesting in strained monolayer nitrogen arsenide and nitrogen antimonide
Allocation: 277 000 jádrohodin
Abstract: Single atomic layer materials (2D materials) are promising candidates for a wide range of new generation devices. In future, research in this field will probably allow applications for 2D materials in fields like sensors, tunable optical devices, energy conversion, photovoltaics. Computational simulations like the ones proposed in this project are necessary to achieve these goals and allow a huge technological development.

 

Researcher: Vojtech Mlýnský
Project: Fine-tuning of AMBER RNA force field
Allocation: 4 000 000 jádrohodin
Abstract: Atomistic molecular dynamics (MD) simulations represent a helpful technique complementary to experiments for determination of ribonucleic acid (RNA) structural-dynamic. However, contemporary MD methods still suffer from limited accuracy of empirical potentials (force fields), including imbalances in the non-bonded force-field terms. We have demonstrated that some improvement of state-of-the-art AMBER RNA force field can be achieved by adding a new term for H-bonding called gHBfix (general H-bond fix), which increases tuning flexibility and reduces risk of side-effects. Recently, we have also modified the standard RESP charge derivation model to improve description of the electrostatic potential around molecules by the newly suggested WRESP-EP charges. Some minor force-field improvements can be achieved by modification of pairwise van der Waals parameters. However, simultaneous effect of all those recently introduced corrections has not been tested. In addition, while the contemporary force fields can describe local dynamics around the folded states, the biologically important large structural rearrangements remain challenge. Thus, the main aim of this project is to fine-tune the AMBER RNA force field by testing synergy of recently tweaked nonbonded terms, applied external potentials and also overall simulation conditions (e.g., counter ions, explicit water models). In order to do that, we plan to employ extensive set of folding simulations of RNA tetraloops, estimate folding free energies and identify, how each modification alter the folding/unfolding balance. Consequently, each force-field term will be tweaked in an attempt to introduce complete MD simulation package, i.e., improved AMBER RNA force field with clearly defined modifications and simulation settings.

 

Researcher: Rafael Dolezal
Project: Research of new AMPAR antagonists by dNN based QSAR analyses and molecular dynamics
Allocation: 10 000 000 jádrohodin
Abstract: Novel antagonists of AMPAR neuroreceptor will be studied by means of machine learning with deep neural networks (dNN) and QSAR methodology. Furthermore, the selected AMPAR/GluA2 receptor will be analyzed by molecular dynamics (MD) with multiple replicas, employing different force fields and coarse-grained MARTINI modelling. The multiple MD trajectory records of microsecond range will be analyzed with a Markov state modelling (MSM) approach to discover potential conformations predominantly occurring in different conductivity states of the AMPAR. Finally, the top scoring candidates of AMPAR antagonists predicted by dNN QSAR screening will be stepwisely docked into binding domains of AMPAR and the ligand-binding impact on the AMPAR behavior will be investigated by extensive MD simulations. This project will contribute to our research of antiepileptics and to in silico drug discovery in the area of treatment of neurodegenerative diseases.

 

Researcher: Aleksandra Dujovic
Project: HPC solver of Ising model: application in Material Design
Allocation: 300 000 jádrohodin
Abstract: Modeling thermal properties of new materials using computational methods based on Quantum Mechanics usually provides us with a well-defined ground state of the system, but not its transitional temperatures. For obtaining these properties, we propose a generic and high-performance method for mapping an ab-initio system onto the Heisenberg model using our original code (github.com/Mellechowicz/JorG). The most crucial part of the algorithm is identifying a set of metastable states of the system, which is achieved through simulated annealing of a ferromagnetic 3D Ising model. This being also the most resource-intensive part of the algorithm, parallelizing it would significantly accelerate the entire process. This project aims to parallelize the search for metastable states using a Message Passing Interface (MPI) and OpenACC. To accomplish this, we intend to implement a hybrid method that combines simulated annealing and a genetic algorithm, both to further increase efficiency and to iteratively improve the obtained results, speeding up convergence. In other words, we will provide researchers with a fast and automatic scheme for assessing transitional temperatures that is well-adjusted for running parallelly on supercomputers, accelerating the design of new materials.

 

Researcher: Martin Mrovec
Project: Efficient distribution of a numerical calculation of Two-Electron Integrals using MPI and OpenMP
Allocation: 247 000 jádrohodin
Abstract: Quantum Chemistry calculations belong to most time-consuming tasks performed on large supercomputers. The field of the Electronic Structure Calculations is quite broad and there have been developed many software packages. They often implement numerical methods that give a result in quite short time (taking into account the Electronic Structure Calculations are quite expensive). Unfortunately, a common feature of many such methods is the lack of theoretical results proving their convergence. This fact leads to many situations, where it is difficult for the user to obtain correct results. Our long-term goal is to develop robust mathematical methods that may serve as an alternative in such situations. Development of such methods require to perform many test calculations. As it is difficult to implement those methods within third-party open-source packages, we have created our own parallel software for these purposes. This software is capable of performing an entire Electronic Structure Calculation which includes several time consuming steps. During the ongoing development, improvements decreasing the computational demands are implemented, which, however, can have a negative effect on the efficiency of the utilization of the supercomputing infrastructure. Although the overall speed is increasing, it is desirable to optimize the code in order to reduce the consumption of computing resources. The aim of this project is to perform the optimization of the distribution of the work in the parallel regions leading to a better scalability. 

 

Researcher: Ctirad Cervinka
Project: Ab initio ranking of the predicted polymorph candidates for molecular crystals
Allocation: 4 000 000 jádrohodin
Abstract: Development of reliable methodologies for crystal structure prediction belongs to the most important challenges in the current material design. Crystal structure prediction consists in computational generation of candidate lists for crystal structures (polymorphs) only from the initial knowledge of chemical constitution of a molecule, without any other empiric information. Crystal engineering in various fields including pharmaceutics, agrochemistry or organic semiconductors would greatly benefit from establishing atomic-scale relationships between a chemical formula of a compound and energy ranking of a list of polymorphs it can form. Physico-chemical or biochemical properties of individual polymorphs can surprisingly vary due to different molecular packing motifs and molecular cohesion in the crystal lattice, so material design always faces a tedious stage of polymorph screening, required for selection of the most beneficial polymorph for a given application. This proposal aims at participation at the 7th crystal structure prediction blind test, organized by the Cambridge Crystallographic Data Centre, representing an established international authority. In the 2nd test stage, all participants are required to use their quantum-chemical or molecular-simulation methods to rank the stability of a list of candidate structures for several technologically relevant chemicals. Participants of the blind test do not know the experimental results at the time of their computations, which ensures a fair and stringent competition for various competition models and research groups in the world-wide context.

 

Researcher: Martin Labuta
Project: Modelling the influence of near-surface geology on 3D seismic waves propagation
Allocation: 330 000 jádrohodin
Abstract: The Urban areas suffer of significant casualties and earthquake damage caused to infrastructure in a number of locations over The World, every year. Strong ground motions, generated in earthquake source, travelling through regional geology, and finally reaching a local geological setting. The near-surface geology is the most critical point in terms of strong-ground motions. Its importance is amplified by the fact, that the 3D effects of the wave propagation, modeled here by Finite-differences (FD), are hence predictable quantity in the strong earthquake ground motion prediction. Added to that, the FD can also simulate ambient vibrations as part of the local geology research, either fundamental and applied. This allows to conduct large number of numerically simulated ground-shaking scenarios representing all earthquakes potentially appearing in a respective region. The synthetic data is then used to estimate earthquake impact on structures in metropolitan area. Our goals is to evaluate the influence of superficial geological structures (e.g., 3D solid bodies, surface layers shallow sedimentary basins) on local site effects due to large regional and subduction earthquakes for the Osaka Bay region. The scientific output of the expected simulations lies in their direct potential to efficiently mitigate and fight seismic hazard via engineering anti-seismic structure design, re-enforcement of existing structures, sophisticated urban projecting, and disaster mitigation planning. Lower damage to structures and consequent lower casualties are direct with important economical and societal impact of the methods.

 

Researcher: Jakub Sebesta
Project: Enhanced magnetism of High Entropy Alloys through f-element doping
Allocation: 4 000 000 jádrohodin
Abstract: One of the promising group of functional materials are High Entropy Alloys (HEAs). They represent multi-principal element alloys with a wide range of applications in engineering. A vast number of constituents, which for high temperatures brings a significant entropy term stabilizing the high-temperature phase, offers great variability of physical properties. Commonly, the HEAs are composed of d-elements with possible p-substitutions. The well-known prototype is the so-called Cantor alloy (CrMnFeCoNi). Although in this HEA all elements are magnetic, the alloy is not. Very often the magnetic interaction are not robust enough and do not survive over room temperature and therefore number of magnetic applications is limited. After our pioneering work of the magnetism of Cantor alloy and its p- and d- derivatives, we’d like to focus on the enhancement of the magnetism, employing f-element substitutions. Particularly, we are interested in the influence of Gd substitutions on the magnetic and elastic behavior of 3d-based HEAs employing the ab-initio calculations. We’d like to study the influence of the f-substitutions on the ground-state magnetic phase, magnetic anisotropic energy, magnetoelastic properties as well as magnetic ordering temperatures.

 

Researcher: Martin Blasko
Project: Computational modeling of in situ reduction of graphene oxide in a polymeric matrix via melting process
Allocation: 340 000 jádrohodin
Abstract: Graphene oxide (GO) is a graphene derivate that is promising for large-scale production. Its functionalization and easy dispersion allows to develop diverse graphene-based structures with controllable electronic, optoelectronic, mechanical, and transport properties. GO incorporates epoxide, carbonyl, carboxyl, and hydroxyl functional groups in the graphene structure. With the aim of restoring the properties of graphene, the oxygenated functional groups of GO are chemically or thermally removed. Regarding the in situ GO reduction in a polymeric matrix via melt process, the polymer chemical structure is a key factor alongside the temperature and morphology. Experimental findings reported in the current literature indicate that the presence of polymeric chains can influence the GO thermal reduction, nevertheless, the mechanism has not been satisfactorily explained yet. In this respect, a profound understanding of the aforesaid mechanism is critical for optimizing the final properties of the nanocomposites, and the large-scale production as well. This study will be centered on the in situ thermal reduction via melting process of GO incorporated into poly(vinyl alcohol) (PVA) by employing hybrid quantum mechanical/molecular mechanical computational simulations in order to shed light on the mechanism and role of polymer chains.

 

Researcher: Thomas Evangelidis
Project: Semiempirical Quantum Mechanical Scoring enhanced by Machine Learning.
Allocation: 2 354 000 jádrohodin
Abstract: As dictated by the laws of Thermodynamics, Binding Free Energy (?G) is an interplay of Enthalpy and Entropy. Despite the overall superiority of SQM scoring over docking, the current protocol ignores almost completely the Entropic contribution to ?G, which attenuates its predictive power in cases where binding is determined by Entropy. Since there is no direct way to estimate precisely the Entropy from first principles and we rely on implicit solvation models, a hybrid SQM/ML scoring function is being developed, named SQM-ML (Semiempirical Quantum Mechanical Machine Learning), which combines physical quantities with selected molecular and structural descriptors to predict the bioactivities of small molecules for a particular target receptor. The training data are produced by rigorous SQM calculations from existing protein-ligand/decoy sets. To date, data from 7 such sets were created on Salomon. It is widely known that the performance of ML algorithms is determined by the amount of good training data. As such, in order to create a general-purpose scoring function (SF) for virtual screening, a cunning selection of ~30 diverse protein-ligand/decoy sets must be made for subsequent high quality data preparation. Therefore I request 9-month access to it4i HPC in order to expand the training set and improve the SQM-ML scoring function. The final outcome will be new software for virtual screening and hit identification.

 

Researcher: Vladislav Pokorny
Project: Magnetic impurities on superconducting surfaces II
Allocation: 350 000 jádrohodin
Abstract: If a superconductor is put in contact with an insulating or semiconducting layer, we obtain a hybrid system in which various quantum mechanical phenomena as superconductivity, electron correlations and quantum tunneling can be separately tuned to obtain the desired properties for real-world applications. Such nanoscopic devices, e.g., Josephson junctions already became standard building blocks of various technologies including rapid single flux quantum (RSFQ) electronics and qubits for quantum computing. Understanding the complex interplay among the various phenomena is necessary step in developing a new generation of such devices. Supercomputers are now a necessary tool that helps us to build our theoretical understanding and explain the available experimental results before these systems can become the tools to extend the abilities of the current silicon-based electronics.

 

Researcher: Karel Carva
Project: Ultrafast magnetization dynamics – interpreting data from femtosecond spectroscopic ellipsometry
Allocation: 385 000 jádrohodin
Abstract: Magnetization can be modified on unprecedently short timescale employing femtosecond lasers. This ultrafast magnetization dynamics has been intensively studied in more than past 10 years. Recent advances have been made possible by utilizing advanced methods such as x-ray absorption spectroscopy or diffuse ultrafast x-ray and electron diffraction together with proper theoretical formalism. An important and not yet fully understood role in this process is played by phonons due to their interaction with magnetism. The PI has already studied the possibility of non-equilibrium phonon populations and was involved in the formulation of theoretical framework describing it [1, 2]. An insight into these populations and their interaction with electronic system can also be gained from femtosecond spectroscopic ellipsometry, which allows to observe directly the dielectric function, and most recent output from these measurements is available. Here we intend to use the above mentioned computational methods to interpret these novel data.

 

Researcher: Jiri Brabec
Project: Automatic design of the novel PAH materials with unconventional magnetic properties: Stage I - development of the tools
Allocation: 3 456 000 jádrohodin
Abstract: Polycyclic aromatic hydrocarbons (PAH) possessing (poly)-radical open shell electronic structure exhibit interesting physical properties, including magnetism, which critically depend on a topology of the p-electron network. Decades ago, it has been shown that the topological frustration in the electronic circuits could lead to non-Kekule structures with magnetic properties, where a non-trivial ground state involves one or more unpaired electrons. So far, however, room-temperature stable magnetic carbon nanostructures have only been theoretical constructs. Very recently, the researchers have succeeded in producing such a structure in practice and showed that the theory does correspond to reality. This was an important step in development of materials which could be applied, for example, in carbon-based spintronics. In this work, we propose to design new carbon-based candidates with magnetic properties using an automatic algorithm connecting reinforcement learning and the density functional theory (DFT) method with an exchange correlation functional optimized for such systems. In the first stage, we will develop the machine learning (ML) model of the exchange correlation (XC) DFT functional, trained on density matrix renormalization group (DMRG) electron densities of the artificial PAH systems.

 

Researcher: Pavel Praks
Project: Stochastic and deterministic methods for optimisation of distribution networks in the energy sector III
Allocation: 20 000 jádrohodin
Abstract: The electrical power consumption is gradually increasing over the years. In combination with the ageing of distribution grids and required integration of new uncontrolled sources (wind and solar systems), a higher emphasis is placed on power flow control and monitoring elements to ensure continued supply and required quality of the provided electrical energy for the society. However, the purchase price and the maintenance cost of the switching and monitoring devices is high, therefore discrete optimization must be employed to identify optimal placement and operating mode of the control devices. The stochastic approach is very robust but extremely time-consuming. Fortunately, the performance of stochastic methods can be accelerated by a parallel implementation. It is the third project for testing of HPC infrastructure of IT4innovations for modelling and optimisation of Czech distribution networks. The novelty of the project includes testing the Ray Tune Python library for large-scale distributed hyperparameter optimization of energy networks. Moreover, the PySR library will be used as a tool for Explainable AI of selected waste to energy processes.

 

Researcher: Jiri Jaros
Project: Modeling of Low Intensity Focused Ultrasound for Intracranial Neuromodulation
Allocation: 400 000 jádrohodin
Abstract: Neurological and psychiatric disorders present an immense challenge for health services globally, with epidemiological studies showing these conditions affect as many as one third of the adult population. Current treatment methods are limited in their efficacy, particularly for patients with advanced or drug-resistant disorders, leaving a critical need to develop effective new treatment pathways. One rapidly emerging therapeutic is neuromodulation using low-intensity focused ultrasound (LIFU). The enormous potential of LIFU stems from the ability to focus ultrasound through the intact skull to a millimeter-sized focal spot size anywhere in the brain. However, there are two significant obstacles preventing routine LIFU applications, the skull scattering and the variability of ultrasound parameters. The ultimate goal of this new project is to develop, validate and optimize new acoustic models allowing near real time prediction of ultrasound focus and the treatment outcome. To achieve this goal, it is necessary to accelerate current state-of-the-art models by two orders of magnitude. Based on our previous experience, we intend to target on mutli-GPU nodes and develop a new multi-model decomposition, optimize derivative operators inside the acoustic solver and introduce mixed precision calculations. This project thus opens a new research area that will continue in following years.

 

Researcher: Jan Rezac
Project: Large-scale benchmarking of non-covalent interactions – non-equilibrium geometries and metal ions
Allocation: 2 900 000 jádrohodin
Abstract: To apply computational chemistry to real-world chemical problems, it is often necessary to work with large systems with thousands of atoms. This is especially true in the two currently most prominent research directions, in the applications of computational methods to biochemistry and to (nano)materials. This requires the use of approximate methods, often including empirical parameters. The development of such method then relies on accurate reference data that can be used for their parametrization and validation. Also, the emerging applications of machine learning to molecular systems require enormous amounts of data for their development. Here, we focus on non-covalent interactions, an effect of key importance in larger molecular systems. This proposal is a part of a larger project that aims to build a state-of-the-art database of accurate calculations that can serve this propose.  First four data sets had been already published and made openly available at a dedicated website www.nciatlas.org, and several more sets are in development. This project brings two important extensions of the NCIA database: first, we will sample additional non-equilibrium geometries of the complexes selected from the current data sets – this is extremely important for the development of robust empirical computational methods. Second, we will build a data set covering interactions of simple metal ions with organic ligands – these data are needed to complete the coverage of interactions occurring in biomolecular systems.

 

Researcher: Pavlo Polishchuk
Project: De novo design of synthetically feasible compounds
Allocation: 500 000 jádrohodin
Abstract: Development of new drugs is the search of small molecules which interact with a particular target and produce a desired response. The complexity of this task is greatly determined by the vastness of the drug-like chemical space which size is estimated as ~1033 compounds. In the nearest future, it will be impossible to enumerate this space or perform any kind of exhaustive search. One of the popular strategies to explore and navigate chemical space is de novo design - model-driven generation of new chemical structures with promising predicted properties. It can go far beyond of the currently available libraries and can discover new chemical entities. The key feature of de novo approaches is structure generation. However, synthetic accessibility of generated structures remains the main issue. We combined the previously developed approach to structure generation CReM, which allows to control synthetic feasibility of generated molecules, with molecular docking in order to generate compounds fitting to a binding site of a chosen protein. The current study will be focused on investigation of the developed tool and its application to search for new ligands of clinically relevant protein targets, in particular MARK4 kinase and tubulin.

 

Researcher: Ahmed Alasqalani
Project: TailOring Metallic Alloys for TribOlogical and nuclear Applications(TOMATO)
Allocation: 2 200 000 jádrohodin
Abstract: It was estimated that about 23% of the world’s energy consumption results from losses due to friction and wear, thus, great and continuous efforts are devoted to the search for new materials with improved wear resistance. In this project two different classes of metallic alloys are considered, namely multilayered system and high entropic alloys (HEAs). Recent studies have shown that multilayered coatings at nanoscale, owning excellent anti-wear performance making them good candidates for a wide range of tribological applications. Similarly, HEAs have gained increased attention, due to their excellent mechanical properties and improved wear resistance. Zr/Nb and quinary AlCrMoTiW alloys have been selected, as models for multilayered and HEAs metallic alloys, respectively. Both system exhibit enhanced strength and hardness, wear resistance. Thus, we aim at investigating the optimal tribological performance of these two classes via atomistic modeling. The outcomes of this research are especially important for alloy design to acquire desired mechanical properties.

 

Researcher: Martin Hanek
Project: Multilevel Domain Decomposition simulations of Incompressible flows for vortex identification
Allocation: 518 000 jádrohodin
Abstract: The main objective of this project is to perform high-resolution fluid dynamics simulations of problems of unsteady incompressible viscous flows.  The goal of these simulations is to obtain high-resolution 3-D data for vortex identification and visualization.  These simulations considering very fine meshes. The computation will be performed using an in-house parallel finite element solver with the pressure correction method and multilevel domain decomposition, with the aid of an existing parallel implementation of the method in the open-source BDDCML library. The project's next goal is to further develop the method and optimization of the BDDCML library for a large number of subdomains.  We also want to investigate the benefits of the recycling of the Krylov subspace across time steps.

 

Researcher: Kryštof Mráz
Project: Fluid Flow Simulations in a Complex Computational Domains
Allocation: 530 000 jádrohodin
Abstract: Porous structures and products with a complex inner geometry are still considered as a great challenge for conventional CFD (computational fluid dynamics). Unlike classical CFD methods (e.g., the finite volume method), the Lattice Boltzmann has proven itself as a promising option for such complex computational domains. The aim of this project is to utilize the Lattice Boltzmann method for numerical simulation of flow through hollow fiber heat exchangers. These heat exchangers contain hundreds or thousands of hollow fibers with outer diameter approx. 1 mm. Such a complex geometry of a heat exchanger made it impossible to simulate it by the conventional CFD. However, the comprehensive numeric simulation of the whole heat exchanger is highly desirable, because it would fill the gap between rather simplifying analytical models and empirical experiments. The local and explicit nature of the Lattice Boltzmann method makes it more than suitable for a massive parallelization and high-performance computing.

 

Researcher: Tomas Karasek
Project: Aeronautics Large-scale Pilot of LEXIS project
Allocation: 553 000 jádrohodin
Abstract: Avio Aero has launched a challenging research activity aimed at significantly improving the feasibility and exploitation of advanced numerical modeling capabilities for critical engine components. The synergy between new generation HPC platforms and Big Data management technologies will open new scenery for the design and optimization of aeroengines, enabling innovative investigation strategies and providing unprecedented levels of accuracy and detail. Avio Aero will leverage the state-of-the-art HPC resources available at IT4Innovations to verify the feasibility of this ambitious objective. The industrial applicability of last generation HPC, Cloud and Big Data platforms will be investigated by means of two aeronautical engineering case studies: one regarding a turbomachinery application and the other one referring to mechanical rotating parts. Both numerical investigations are based on complex Computational Fluid Dynamics (CFD) analyses and rely on HW-intensive and time-consuming routines. The objective is to demonstrate the speed-up opportunities given by state-of-the-art HPC Systems and to develop and deploy an efficient management of numerical results.  

 

Researcher: Antonio Cammarata
Project: harnEss Nanofriction with LIGHT (ENLIGHT)
Allocation: 2 125 200 jádrohodin
Abstract: Nanodevices in static or dynamic conditions experience nanotribological effects leading to major challenges for the proper design, control, and reliability of, for instance, nanoelectromechanical systems. Hence, the friction behavior of wheels and belts in nanocoveyor belt systems may limit the mechanical transmission at the nanoscale. This behavior is emphasized by the high area/volume ratio, where surface phenomena control the nano-systems properties and performance. The ideal way to modify friction is to do it in a reversible way, i.e., avoiding permanent modifications to the atomic structure. A promising solution is to use ultraviolet and visible light to control the frictional properties. Despite the promising experimental results already available, the microscopic mechanisms determining the frictional response in the presence of light are still unclear. To this end, the final goal of this project is to shed light on the coupling phenomena occurring between the ultraviolet/visible light and the nanoscale friction response of tribological materials. To this aim, we will consider TiO2 thin films and transition metal dichalchogenides as case studies, because they find large applicability in many nanotribological devices.

 

Researcher: Pavel Balaz
Project: Dynamics of topological defects in a skyrmion lattice
Allocation: 905 000 jádrohodin
Abstract: Magnetic skyrmions, as quasi-particle objects, have been observed in noncentrosymmetric magnetic materials. Their high topological stability and ability to move under the effect of electric current make skyrmions hot candidates for information carriers in novel spintronic devices operating at room temperature. Skyrmions do not only occur as isolated objects on uniform magnetic background. More often number of skyrmions form large ordered 2-dimensional clusters known as skyrmion lattice or skyrmion crystal. Recently, it has been demonstrated experimentally as well as theoretically that, as any other crystal, skyrmion lattice undergo phase transition and melts under the influence of thermal fluctuations. Contrary to known 3-dimensional crystals, 2D skyrmion lattice melts by unbinding of topological defect via so called hexatic phase characterized by productions of defect pairs known as dislocations. In our project, we focus on study of the defect dynamics inside a skyrmion lattice close to the hexatic phase. Dislocation defects in crystals can move as a response to external stresses and thermal fluctuations. By means of atomistic spin dynamics, we shall simulate skyrmion lattices under the influence of external torques due to the spin transport at nonzero temperatures. The aim of our study is to estimate the possibilities of manipulation with dislocations in skyrmion lattice.

 

Researcher: Martin Kolisko
Project: Lateral gene transfer and evolution of Apicomplexa
Allocation: 1 220 800 jádrohodin
Abstract: The role of lateral gene transfer (LGT) in the evolution of microbial eukaryotes remains a hotly debated topic. Here we propose to research LGT in the across the phylum Apicomplexa, a group of obligatory intracellular parasites with complex life cycles that infect diverse animals in nearly all host environments. Identification of LGTs within Apicomplexa will help us understand the extent of lateral transfers within their genomes. Functional annotation of these LGTs will help us understand the impact of LGT on the evolution and adaptation of Apicomplexa to specific hosts, host environments, and life cycles.

 

Researcher: Judita Nagyova
Project: Movement characteristics of models with closed curve equilibria
Allocation: 26 000 jádrohodin
Abstract: The main aim of this study is to continue the analysis of the dynamical properties of two models with closed curve equilibrium. The first model was studied in [1], and the second model in [2]. It is a generalization of the first one, with a right-hand side containing non-smooth functions. The corresponding three-variable models are given as a set of nonlinear differential equations. The nature of these models makes the simulations problematic for certain combination of parameters as the computation require higher precision. The dynamics of the model are studied depending on these particular values of parameters. For investigating the dynamical properties of these models, new methods, as the 0-1 test for chaos and approximate entropy, are applied. Using these tools, the dynamics are quantified and qualified. It will be shown that depending on the system's parameters, the system exhibits both irregular (chaotic) and regular (periodic) character.

 

Researcher: Valeria Butera
Project: Photochemical CO2 Conversion on Pure and Metal-Doped Gallium Nitride (GaN): a DFT study
Allocation: 1 150 000 jádrohodin
Abstract: The photochemical reduction of carbon dioxide (CO2) into methanol is very appealing since it requires sunlight as the only energy input. However, the development of highly selective and efficient photocatalysts is still very challenging. It has been reported that CO2 can be spontaneously activated on gallium nitride (GaN). Moreover, the photocatalytic activity for CO2 conversion into methanol can be drastically enhanced by incorporating a small amount of Mg dopant. In this work, Density Functional Theory (DFT) based on cluster model approach has been applied to further explore the photocatalytic activity of bare GaN towards CO2 adsorption and conversion. We extended the investigation of Mg-doping replacing one Ga atom with Mg on three different sites, and evaluating the consequent effects on the band gaps and CO2 adsorption energies. Eventually, we explore different routes leading to the production of methanol and evaluate the catalytic activity of the bare GaN by applying the energetic span model (ESM) in order to identity the rate-determining states which are fundamental for suggesting modifications that can improve the photocatalytic activity of this promising material.

 

Researcher: Tomas Brzobohaty
Project: Simulation of NOx reduction by SCR method
Allocation: 447 000 jádrohodin
Abstract: Role of nitrogen oxides in the formation of photochemical smog has been discussed since 1952. These chemical species are considered as potential air pollutants. The presence of NOX, which includes nitric oxide NO and the nitrogen dioxides NO2, contribute to acid rain, reduced visibility and fine particle too. This project is aimed at numerical simulation of reduction of NOx by Selective Catalytic Reduction (SCR) technology. Numerical simulation will be performed for several boilers with different type of fuel, e.g. Natural gas, biomass etc., and various type of catalyst. As a main result, reduction of NOx as a function of type of catalyst, type of fuel and operating condition will be analyzed. These data are very useful for design and optimization of SCR technology, which is one of possible method how to reach low NOx emission for power and or thermal plants. This project build upon the proof-of-the-concept (POC) carried out within the scope of the EuroCC project and aim to support project of collaborative research within the call of Ministry of Industry and Trade Aplikace IX CZ.01.1.02/0.0/0.0/21_374/0026707.

 

Researcher: Martin Matys
Project: Plasma shutter in laser-matter interaction with preplasma profile
Allocation: 1 006 000 jádrohodin
Abstract: A plasma shutter is usually a thin solid foil placed in front of the main target in the laser-target interaction. The laser pulse then needs to burn through it before reaching the target. The intensity of the laser pulse transmitting through the plasma shutter can increase by optical processes, which may be beneficial for subsequent interaction with the main target. In this research, we use a combination of demanding  particle-in-cell and hydrodynamic simulations to investigate the double shutter scenario. The first shutter is  pre-expanded  by the residual prepulses of the main laser pulse and creates a low density region called preplasma. As the laser pulse undergoes a process of self-focusing while transmitting through the preplasma, the final laser pulse intensity can increase even more, when this process is assumed. The laser pulse with increased intensity can find applications in ion acceleration, gamma-ray production and eventually even in the generation of the electron-positron pairs.

 

Researcher: Marek Ingr
Project: Multiply substituted hyaluronan oligosaccharides in mixed water:organic solvents.
Allocation: 1 500 000 jádrohodin
Abstract: Hyaluronan (HA), a key component of the extracellular matrix of skin and connective tissues, is widely used in cosmetics and pharmacology as a compound supporting the tissue regeneration and wound healing. Its biocompatibility predestines it for applications in drug-delivery systems or artificial tissues design, often modified by hydrophobic aliphatic substituents. For their synthesis and processing non-aqueous environment is often necessary. Recently, we showed that the composition of the solvent can strongly influence the chemical reactivity as well as the properties of the modified HA. In this project we propose to study the conformation and dynamics of multiply substituted HA oligosaccharides by means of molecular-dynamics (MD) simulations in different mixed solvents. Following our previous project, we plan to carry out simulations of HA oligosaccharides with varying numbers of aliphatic substituents in water:organic mixed solvents of different compositions. The conformation changes will be investigated in dependence on the degree of substitution. Additionally, the influence of a moderate concentration of salt on both non-substituted and substituted HA chain will be investigated. The structure of solvation shells of the molecules will be studied in order to explain the essence of the forces responsible for the conformational changes. The results of the study may be utilized in the design of new biocompatible materials in the stages of their synthesis and processing.

 

Researcher: Diego Lopez
Project: Continuation of the extensive Pursuit of Singlet Fission Sensitizers (CEPSFS)
Allocation: 1 474 000 jádrohodin
Abstract: The transformation of sunlight into electricity represents one of the major tasks that scientists are facing  nowadays. The expensive and polluting fabrication of the traditional silicon-based photovoltaic (PV) devices, as well as their low performance in low-light conditions increased the interest to improve this technology. Improving the efficiency of PV devices will drastically reduce the cost of the electricity, and strategies such as the downconversion of short wavelength photons were proposed. One of the main phenomena under investigation nowadays is called Singlet Fission (SF), a spin-allowed photophysical process in which one singlet excited state splits into two triplet states. Hence, this process enables the generation of two low-energy excitons per absorbed photon. However, the development of this new technology is still impeded because the number of molecules in which SF was experimentally found is still small, and only a few new systems could be added to the paradigmatic acene derivatives. Under those circumstances, it is captivating the approach recently published by Padula et. al. in which the Cambridge Structural Database (CSD) was computationally screened. Padula finally suggested a final set of around 200 SF absorbers among the initial list composed by 1 million candidates. Encouraged by this inspiring contribution,  a partial screening of the PUBCHEM database10 already have been started seeking for new singlet fission sensitizers with the resources granted by the OPEN-21-2 it4ifree project. This project aims to achieve the screening of the full PUBCHEM database by means of DFT in order to obtain the best candidates for SF 

 

Researcher: Hermann Detz
Project: Anion interactions during MBE growth
Allocation: 900 000 jádrohodin
Abstract: Compact mid-infrared spectroscopy systems, based on interband cascade lasers and detectors, open up the potential for a plenitude of sensing and diagnostic applications. Portable solutions for the identification of diseases, the sensing of vital parameters, quality control in food production, as well as environmental monitoring of industrial processes will have an impact on daily life. In order to realize this vision, it is imperative to improve the active semiconductor materials that provide a flexible basis, where the target wavelength to detect a specific substance is a design parameter that can be tailored towards specific applications. This requires both, experimental efforts as well as a detailed understanding, provided by different electronic and structural models. This density functional theory-based approach will facilitate the understanding of growth processes for active materials and therefore a faster and cost-effective optimization of future device generations.

 

Researcher: Raúl Ortega Chametla
Project: Effects of thermal torques on the formation and migration of Earth-like planets
Allocation: 1 300 000 jádrohodin
Abstract: Cores of low-mass planets and possibly many super-Earths form and migrate within protoplanetary disks which are subject to heat transport, largely facilitated by radiative transfer. Thermal diffusion depends on a number of parameters such as the disk’s temperature and density, and the opacity of its dust component. Recent efforts to find a suitable model to correctly describe the formation and migration of planets like Earth have shown that the accretion of solid material (pebbles or planetesimals) by a low-mass planet can markedly change its migration direction by so-called  thermal torques. The main objective of this project is to study the effect of thermal torques by means of high-resolution three-dimensional hydrodynamic simulations with radiative transfer. Compared to previous studies of thermal torques, the aim here is to significantly improve the resolution to reduce numerical noise and also to account for stellar irradiation. The latter effect can modify temperature and opacity gradients in the disk and the resulting model for thermal torques will therefore be more realistic. 

 

Researcher: Jan Kotek
Project: Discontinuous Galerkin Finite Element Magneto-Hydrodynamic Simulations in Solar Atmosphere
Allocation: 970 000 jádrohodin
Abstract: Processes in the Solar atmosphere and as a consequence magnetic storms are of significant importance for the safety of spacecraft, astronauts and in case of severe storms also power grids and electrical appliances on the Earth. One of the most rapid and energetic processes that can also lead to these storms by starting so-called Coronal Mass Ejection are solar flares.  Solar flares themselves are triggered by a process of magnetic reconnection. During this process, plasma is significantly accelerated and creates outflow/jet whose implications can be observed. To interpret these observations, we want to do parametric MHD studies of the outflow. We want to use the simulated data to interpret certain types of structures in the radio spectrum and to determine general behavior of the outflow in a stratified atmosphere.

 

Researcher: Maria Saija
Project: Interactions of surfactant-coated triglyceride nanodroplets with the tear film lipid layer in the context of dry eye disease.
Allocation: 600 000 jádrohodin
Abstract: The tear film lipid layer (TFLL) is a multilayer structure of lipids that separate the aqueous tear film of the eye from the external environment. TFLL is the outermost layer of the human eye, directly exposed to air and interacting with pollutants, pathogens and topical drugs. Alterations of TFLL are related to the dry eye disease which nowadays is becoming a common health issue. State-of-the-art topical therapies against dry eye disease are based on oil-in-water nanoemulsions loaded with active drug molecules. To design improved nanoemulsion-based topical drugs, a detailed knowledge of  TFLL interactions with topical drugs is required. In particular, molecular-level details regarding interactions of different lipid classes of TFLL with lipids and the lipophilic drugs present in the nanoemulsions are needed to fine tune the nanoemulsion formulations. Such optimization would improve drug stability and action on the eye. Molecular dynamics simulations are the best tool for studying lipid-lipid and drug-lipid interactions at a microscopic level, they provide direct information needed for improvement of topical ophthalmologic drugs used in dry eye disease. The goals of this project involve characterization of interactions of lipid nanoaggregates carrying small drugs with the in silico TFLL model that we previously developed. Such aggregates (mainly oil-in-water nanodroplets coated with cationic lipids) are used in new ophthalmic formulations. The results of molecular simulations will be corroborated by in-vitro experiments. The expected impact of this project, apart from purely biophysical aspects, involves a practical outcome related to fine-tuning of the oil-in-water-based formulations used for dry eye disease treatment.

 

Researcher: Marek Lampart
Project: Dynamics of a free-body colliding mechanical system with a friction II
Allocation: 100 000 jádrohodin
Abstract: The main aim of the project is to analyse the dynamic properties of a mechanical system described by a mathematical model. The investigated system consists of a cylinder freely joined on a horizontal string fixed on the wall and of a moving belt. Such a system with impacts and dry friction is an image of many industrial applications, like stones falling on a conveyor moving belt. The mathematical model of the system has two degrees of freedom from which one corresponds to the position of the cylinder centre and the second one to its angular rotation. The studied system is excited by a slider moving in the vertical direction and by impacts between the cylinder and the belt. As a main result, it will be observed that the cylinder exhibits movement with both regular (periodic) and irregular (chaotic) patterns depending on the excitation amplitude and frequency. The goal of the research is to qualify and quantify the movement character. For this purpose, the 0-1 test for chaos together with approximate entropy will be utilized to find the regions of parameters for which chaos or regularity will be observed.

 

Researcher: Vojtech Cima
Project: Deep Learning for Diabetic Retinopathy Detection II
Allocation: 98 000 jádrohodin
Abstract: Eye retina provides a unique non-invasive direct insight into the human body’s bloodstream. It is currently being used in medicine to diagnose a number of diseases. It has been proved that retina artifacts may help to discover the early stages of diseases such as diabetic retinopathy, age-related macular degeneration, glaucoma, and other common diseases. Nowadays, the diagnosis of these diseases is conducted mainly by highly-specialized medical professionals - doctors based on a thorough visual evaluation of various eye-segment screens. In recent years, deep learning-based approaches have surpassed human performance in many domains including image recognition, object detection, or image segmentation also applied in the context of medical data. With this domain progressing swiftly forward, we aim to research, design and develop a deep learning-based solution that makes the diagnosis more efficient, more accurate and faster than the current manual process.

 

Researcher: Dominik Legut
Project: Detection of the magnons by STEM from HPC calculations
Allocation: 10 000 000 jádrohodin
Abstract: Machine learning and artificial intelligence are among new technologies, which are penetrating into our everyday life. Their common feature is that they call for large computational resources, which is connected with high energy consumption. Therefore researchers are continuously seeking for new technologies that could lead to faster, cheaper, and more energy-efficient computers. One such field of research is magnonics, where information is transferred via waves of atomic spins, without physically moving electrons – as is the case in conventional electronics. Magnonics has the potential to bring information technologies to terahertz speeds at a fraction of the energy consumption of today’s computers. Before having magnonics-based computers, several challenges need to be faced. One of them is a direct imaging of magnons. In this proposal, we come forward with a suggestion, how to realize that in a modern transmission electron microscope. We will computationally evaluate the feasibility of such an approach and, if successful, we will come with detailed suggestions to experimentalists, how to set up an experiment that could detect magnons with a nanometer-scale precision.

 

Researcher: Jana Pavlu
Project: Diffusion on phase boundaries in disilicide nanocomposites
Allocation: 7 240 000 jádrohodin
Abstract: Our modern society based on the utilisation of advanced materials requires the development of new structural materials that could be used at higher operational temperatures or reveal unique properties. Nevertheless, their properties are significantly affected by structural defects such as interfaces and the processes taking place on them. The proposed project aims to understand how the atoms of the constituents of the disilicide nanocomposites diffuse across the interphase boundary. This would not be possible without a deeper understanding of the relations between microstructure and macroscopic properties of a material. Unfortunately, these relations very often touch the experimentally unreachable areas. However, they can be studied through theoretical approaches such as computational modelling. These methods will also be used in this study. 

 

Researcher: Ivan Kolos
Project: Numerical modeling of load of structures in quasi-static effect of wind
Allocation: 150 000 jádrohodin
Abstract: The project is focused on numerical modeling of flow around objects in the atmospheric boundary layer. This issue is complicated mainly due to the atmospheric turbulence, which requires the use of advanced numerical models of the flow coupled with detailed computational mesh of the domain. This research will contribute to bigger efficiency in design of building structures.