Project: DRVOSTEP – Open Translation
Allocation: 1609000 core hours
Abstract: DrVostep will investigate the limits of machine translation for hundreds of languages. The first output will be the analysis of translation quality with and without intermediate languages, such as CZ->DE versus CZ->EN->DE. A second result, benefiting the wider European community, will be an open machine translation website like google translate, but unlimited and free by performing computations client-side.
Primary Investigator: Michael Komm
Project: Particle-in-cell studies of shaping of the plasma-facing components for the COMPASS-U tokamak
Allocation: 661000 core hours
Abstract: One of the outstanding issues on the way towards power harnessing from nuclear fusion reactions is the problem of power exhaust – how to effectively remove the heat delivered by hot plasma to the plasma-facing components (PFCs) of the reactor. In order to study this problematics, a new tokamak COMPASS-U (supported by the OP VVV project COMPASS-U: Tokamak for cutting-edge fusion research) is currently in the design phase at the Institute of Plasma Physics of the CAS. The heat load in the divertor of COMPASS-U are expected to reach several tens of MW/m2, which requires careful considerations of the shaping of its divertor components to avoid hot spot formation and subsequent melting of the components. Within this project, studied of the heat flux distribution on the PFCs will be performed by means of particle-in-cell simulations.
Primary Investigator: Vojtech Betak
Project: LEGiT (Low emission technology for aerospace gas turbines )
Allocation: 44000 core hours
Abstract: This project is focused on modeling of liquid fuel combustion in the combustion chamber of gas turbines for aerospace applications. Application of the experimental method is limited due to the conditions inside the chamber(e.g. shape of the chamber, temperature over 2000 K, high pressure, …). Therefore, the application of the computational method is necessary. Modeling of liquid fuel combustion is quite complex because it is necessary to simulate the highly unsteady turbulent flow field, heat transfer, particle motion, and chemistry at the same time. There is also a strong interaction between simulated phenomena which are limiting the application of a suitable computational method. Especially for pollutant formation are asked accurate model of turbulent flow field which can be obtained by using complex turbulence models such as LES or hybrid RANS-LES turbulence model. This project follows the goal of emission reduction which was set in the EU Horizon 2020 program CleanSky 2. It is planned to reduce CO2 emissions by 75% and NOx by 90% by 2050. There is a group in Czech Aerospace Research Centre which is focused on the development of low emission combustion technologies. Member’s of this group worked e.g. on the design of novel combustion chamber for small jet engines or study of burners for industrial applications. Currently, this group is working on 2 projects connected with combustion in gas turbines which is supported by the Technology Agency of Czech Republic (grant no. TH04010357) and the Ministry of industry and trade (Support for long term conceptual development of research organization grant no. 11/2018).
Primary Investigator: Victor Montagud Camps
Project: Turbulence in the expanding solar wind: from inertial to kinetic scales
Allocation: 870000 core hours
Abstract: The Solar Wind is the largest layer of the Sun’s Heliosphere, extending from 10 solar radii above the Sun’s surface up to the edge of the solar system. The study of solar wind properties finds its application in a scientific domain known as space weather: similarly to weather forecasting, its purpose is to predict the properties of the Sun’s atmosphere at Earth’s orbit, so adequate decisions can be made in case of unfrequent but violent events such as Coronal Mass Ejections. Like Earth’s atmosphere, solar wind is also a turbulent fluid. The main difference with respect to atmospheric turbulence is that solar wind is a gas composed by charged particles (a plasma) that interact with the Sun’s magnetic field. To the difference in nature, we have to add the difficulty to obtain data from the solar wind, as only satellites can do that. In this context, numerical simulations are a way to study solar wind turbulence without the constraints of a space mission. We propose to reproduce the so-called ”transition region” between the low and high frequency domains of solar wind turbulence. In order to do so, we will, for the first time, model the plasma as a single fluid in 3D space, including some high frequency effects and the large scale expansion of the wind. With this numerical approach we pretend to study the role played by expansion on the transition to high frequency scales and its influence on the turbulence developed there.
Primary Investigator: Jamil Missaoui
Project: Molecule contamination effects on nanofriction in Layered Materials (MoleLaM)
Allocation: 2103000 core hours
Abstract: The energy dissipation due to friction in mechanical systems is estimated to reach a considerable rate of 20%. As such, most surfaces sliding on top of another experience friction-induced wear; this automatically calls for high performance lubricants. When classic liquid lubricants cannot be used, the solution is found in the form of solid lubrication in applications such as aerospace or nuclear industries. The discovery of the low-friction behavior of graphene marked the beginning of a new chapter of research of novel solid lubricants, where attention is drawn on layered compounds. Transition metal dichalcogenides (TMDs), family of lamellar materials, are currently the most promising alternative to graphene in this field. Their peculiarities open several routes to achieve unprecedented properties of wide applicability, such as in photovoltaic devices, lithium ion batteries, hydrogen evolution catalysis, transistors, photodetectors, DNA detection, memory devices and tribological applications. The focus of the present project is to control layer sliding and separation in TMDs in the presence of small molecules, in order to obtain guidelines on how to produce layered TMDs films with controlled thickness. To this aim, density functional calculations will be used together with advanced methods of electronic and phonon analysis, in order to predict and suggest new structure/composition configurations of novel MX2 TMD prototypes, with controlled frictional behavior.
Primary Investigator: Martin Beseda
Project: Computations of [N2/He]+ potential energy surfaces
Allocation: 525000 core hours
Abstract: This project is a straight continuation of OPEN-14-25, where ab initio computations of [N2/He]+ proved to be significantly more computationally expensive, that thought previously. Their purpose and the broader research context of this project stays the same, so I provide a shortened version of the previously posted abstract, which introduces the topic in sum. Modeling of cold rare-gas plasmas is currently one of the popular topics in the field of quantum chemistry because of their possible applications in many fields, with plasma medicine being the most interesting to our team. To understand the healing properties of cold rare-gas plasmas, detailed knowledge of processes on the microscopic level is of crucial importance. Initially, interactions between rare-gas ions and air molecules will be calculated with the main focus on the simplest rare-gas (He) and the most abundant air molecule (N2). However, both the ab initio computations of potential energy surfaces and the semiclassical nonadiabatic molecular dynamics are very computationally demanding and, in some cases, even the modern computation methods show themselves unstable. The one way to overcome these obstacles is the utilization of machine learning methods, especially artificial neural networks (ANNs). Thus, there are three pillars of this project: a) ab initio computations, b) nonadiabatic molecular dynamics, and c) development and testing of our ANN library.
Primary Investigator: Pavlo POLISHCHUK
Project: Investigation of molecular mechanism of actions of anticancer and antineurodegenerative compounds
Allocation: 262000 core hours
Abstract: The main goal of the project is to explore the conformational changes and mechanistic details of ligand binding towards proteins relevant to anticancer and neurodegenerative studies. The first target of interest is MARK4 kinase – a prominent target for anticancer and antineurodegenerative drugs, directly involved in microtubule regulation in cells. Several promising ligands were already synthesized at IMTM, and now the goal is to explore the underlying mechanisms of their action and perform rational molecular design. The second target is bystin, which is a part of pre-40S ribosomal subunit involved in cell growths process. Bystin is a promising target for anticancer research. However, there are no reported ligands yet and therefore a mechanism and a binding site are unknown. Recently several bystin ligands have been discovered at IMTM. Now we have to determine the binding site of those compounds which is a complex and laborious task including protein mutagenesis and other techniques. Application of computational tools may substantially decrease time and complexity by determining most probable binding sites which would be reasonable to validate experimentally.
Primary Investigator: Tomas Karasek
Project: Real-time mapping of cellular traction forces
Allocation: 306000 core hours
Abstract: Biochemical and biophysical signals are known to influence the abilities of cells to sense and generate mechanical forces. Similarly, cells in their in vivo microenvironment actively sense mechanical forces and convert them into biochemical responses . Indeed, mechanical factors are present during embryogenesis and development , and are involved in many pathological conditions, such as atherosclerosis , osteoporosis , myopathies , and cancer . On a cellular level, there is clear evidence of mechanical cues affecting cellular adhesion, proliferation , morphogenesis , migration , and stem cell differentiation . These mechanical signals present themselves in the form of shear stress, hydrostatic pressure, ECM topography or stiffness, or intercellular tugging. The objective of this project is the simulation of mechanical properties of nanopillars in order to optimize the technology process of nanopillar fabrication for later cellular force measurement. This is the critical point for patterning the nanopillar array in the context of the center-to-center and diameter of pillars as it should be optimized for cells. Thus, the pattern must be compatible with cell attachment and spreading, sensitive enough for measurement of traction force with high spatial resolution and it must avoid pillars collision and stiction.
Primary Investigator: Martin Žonda
Project: Magnetization dynamics due to nonequilibrium quantum transport
Allocation: 481000 core hours
Abstract: Magnetization dynamics is a central issue when discussing the future of the random access memories and information processing. An essential requirement for minimization of size and energy consumption of the memory devices repeatedly open a question of manipulation of spin of single atom, molecule, or a atomic clusters. One of the most efficient way of spin control is coupling the localized atomic spins to a flow of itinerant electrons. Due to transport of angular momentum between the localized noncollinear magnetic moments their dynamics might be substantially influenced due to the spin transfer torque. From theoretical point of view description of spin dynamics on atomistic level is a complex problem. Direct quantum mechanical treatment of this problem does not come into account when the number of localized spins increases. Therefore, we shall use hybrid model, in which dynamics of localized atomistic spins will be described using classical equation of motion, while transport of itinerant electrons shall be treated in frame of quantum mechanics. Namely, a well established spin-dependent Falicov-Kimball model shall be utilized to model complex behaviour of classical and quantum degrees of freedom coupled via the exchange interaction. This simplification will allow us to apply nonequilibrium Green-function technique combined with Landau-Lifshitz-Gilbert equation. In this project we shall focus on both stability of long-range ordering in the presence of spin transport as well as current-induced dynamics of domain wall formed by atomistic spins.
Primary Investigator: Martin Cermak
Project: Analyses of concrete structures by ANSYS and PERMON
Allocation: 171000 core hours
Abstract: Along with development of computer technologies, computer simulations have been used to predict various phenomena. One of the phenomena that are being pursued by scientists around the world is the problem of foundation in contact with subsoil. Despite the fact that the computational models are constantly developed, the optimal procedure to provide sufficiently accurate results has not been arrived at yet. For better understanding of the issue, the special testing equipment was constructed at the Faculty of Civil Engineering at VŠB – Technical University of Ostrava, and experiment tests of loading slabs are performed there. Together with the experiments, numerical models are developed but the capacity of the standard workstation is insufficient for the research at the moment so the aim of this project is to explore the possibilities of a supercomputer and its application to the solved problems. During this project, several numerical models will be made and solved by ANSYS Multiphysics and the PERMON toolbox. The obtained results will be compared to the experimental values. This will allow the research to continue.
Primary Investigator: Marek Ingr
Project: Environmental effects on hyaluronan molecules and their intermolecular interactions.
Allocation: 743000 core hours
Abstract: Hyaluronic acid (HA, hyaluronan) is a natural polysaccharide contained by the extracellular matrix of connective tissues, synovial fluid, vitreous fluid of eyes, umbilical cords and in chicken combs. For decades it is intensively studied for the manifold of biological functions, but also for its possible technological use in the field of cosmetics, drug-delivery or tissue engineering. Free HA macromolecules form random coils in aqueous solution and may also form supramolecular structures in special conditions. Following our previous work, HA oligomers and their couples will be simulated in different environments in order to study the influence of ions on HA structure and the formation and stability of the supermolecular structures of two HA chains. Interactions of HA with its protein receptors (hyaladherins), especially the TSG-6 Link domain, will be also studied within this project. The goal is to explain the experimentally observed strong pH dependence of the HA binding to this domain and to evaluate whether chemically modified oligosaccharides may serve as ligands of this domain, too. Recently, several binding modes were found for a neutral HA analog. Within this project a complex thermodynamic description of the binding modes of HA and its neutral analog should be obtained including the influence of pH and ionic strength. The artificial oligosaccharide ligands with favourable thermodynamics properties may have a strong potential in pharmaceutical applications.
Primary Investigator: Mojmir Sob
Project: Structure and properties of novel nanocomposites formed by intermetallic compounds
Allocation: 7223000 core hours
Abstract: This computational research aims to investigate structure and properties of promising novel nanocomposites formed by intermetallic compounds, such as various transition-metal disilicides and selected nitrides, which may bring technological foundations for a variety of engineering innovations. Central topic of our work will be a detailed investigation of interfaces in these intermetallic nanocomposites which are decisive for their technologically important properties. Here we will consider both the “clean” interfaces as well as the effect of segregated impurities and vacancies, which has been studied very little or not at all. The prime objectives of this proposal are to deliver a deeper understanding of structural and mechanical properties of intermetallic nanocomposites (such as strength, elastic moduli and stability), provide a solid theoretical basis for interpretation of corresponding experimental data, contribute to designing of new advanced materials and, in this way, foster a system of innovation comprising basic and engineering research.
Primary Investigator: Pavel Jungwirth
Project: Impact of insulin oligomeric state on its T to R conformational transformation
Allocation: 5072000 core hours
Abstract: Improving treatments for diabetes and better understanding its causes is a major challenge for public health. According to the WHO, diabetes affected in 2017 more than 425 million people worldwide, resulting in 4.0 million deaths. The disease is caused by disorders in the metabolism of insulin, a hormone that lowers glucose levels in human blood. The insulin molecule can adopt different shapes (called T and R), that exhibit different physical properties. During its storage in the pancreas, insulin forms hexamers, which can thus exist in different forms (R6, T3R3, T6) depending on the presence of different ions and neurotransmitters. In order to improve existing insulin formulations, it is thus very important to understand how the formation of oligomers (dimer, hexamer) and the presence of neurotransmitters influence the conformation (or “shape”) of insulin. Studying the insulin T-R conformational transformation is a computational challenge because of the complexity of the transformation. It thus requires the use of state-of-the-art simulation techniques. Our goal is to characterize the insulin T-R conformational transformation in different oligomeric states, and the binding of neurotransmitters to these different oligomers. This work will allow us to gain for the first time molecular insight into this key transformation, and will thus guide experimentalists towards designing better insulin formulations.
Primary Investigator: Rajko Cosic
Project: Utilization of artificial neural networks in path integral Monte Carlo simulations
Allocation: 134000 core hours
Abstract: In path integral Monte Carlo (PIMC) simulations, the most demanding part is the evaluation of the potential energy. This limitation allows us to perform calculations only for small clusters and forces us to use less accurate potential energy surface (PES) representations if larger clusters are considered. One of the possible approaches which may enable us to overcome this bottleneck is to represent the PES using the artificial neural networks (ANNs). The main aim of the present project is to connect the PIMC simulations with the modules for the PES representation using the ANNs. The implementation is to be tested on charged helium clusters photoabsorption spectra of which are of high interest and, for small cluster sizes, have been investigated before within the scope of previous projects. The project will cover only the pilot phase of much larger scientific intention which aims to investigate the photoabsorption spectra of charged helium and neutral mercury clusters size of which is too large for the PIMC simulations using the diatomics in molecules (DIM) PES representation.
Primary Investigator: Tomas Martinovic
Project: Statistical and machine learning algorithms for time series analysis
Allocation: 175000 core hours
Abstract: One of the areas most touched by increased computing capacity obtained in last few years is data analysis. Analysis of data obtained from the study of real-world phenomena like protein structures or reliability of electricity grid requires a computing capacity that was previously unavailable. These phenomena are usually described by a large quantity of data. A significant part of this data are time series, which represent dynamical properties of these phenomena. To further complicate the matter, these time series can also be loaded with uncertainties, which are usually caused by errors or inaccuracies in measurements and can also be variable in time. Usually, these challenges concerning uncertainty can be solved by applications of various statistical methods, but, given the large quantity of data and their complex structure, statistical approach can sometimes be very complicated or outright unfeasible. Therefore, these statistical methods must be enriched or replaced by approaches coming from the field of machine learning. These approaches can possibly process more complicated and larger data sets at a price of less exact mathematical description. Aim of this project is to find, implement and optimize algorithms and methods coming from both these fields to perform various tasks connected with data analysis of time series like their prediction, comparison and clustering. To enhance their performance, they will be implemented to take advantage of HPC infrastructure.
Primary Investigator: Jana Pavlikova Precechtelova
Project: Validation of combined MD/DFT computational approaches for the calculation of 15N chemical shifts in intrinsically disordered proteins.
Allocation: 423000 core hours
Abstract: The project designs and validates the computational methodology for the calculation of 15N nuclear magnetic resonance (NMR) chemical shifts (CSs) in intrinsically disordered proteins (IDPs). The proteins play an important role in the regulation of molecular mechanisms that lead to neurodegenerative diseases. The understanding of their structure and interactions with other biomolecules is thus immensely important for humans. High flexibility of IDPs hamper their structural characterization by experimental techniques such as NMR spectroscopy. However, the use of computational methods alleviates the problem substantially. To reflect the flexibility of IDPs, the proposed project builds on molecular dynamics simulations that provide coordinates of molecular clusters for further quantum mechanics calculations. The project seeks to identify a computational set-up that minimizes the extent of systematic errors. The effects of conformational sampling, ensemble averaging and basis set size are inspected and a computational protocol for reliable 15N chemical shift calculations is proposed as a result. The accuracy of the protocol is then validated for the human tyrosine hydroxylase 1 (hTH1) that serves as an example of an IDP. The project contributes to the development of approaches for computer-aided structural characterization of intrinsically disordered proteins.
Primary Investigator: Donato Magarielli
Project: Aeronautics Large-scale Pilot on LEXIS
Allocation: 2867000 core hours at first period
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 aero-engines, 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 CPU-intensive and time-consuming routines. The objective is to demonstrate the speed-up opportunities given by state-of-the-art Computing Systems and to develop and deploy an efficient management of numerical results.
Primary Investigator: Miroslav Rubes
Project: On the accuracy of zeolite structure prediction from first principle calculations
Allocation: 2317000 core hours
Abstract: The zeolite framework flexibility is becoming a very important issue due to its impact on mass transport in these materials. It has been recently realized that even a small change in theoretical description of the framework can determine, whether a particular adsorbate pass through zeolitic material or not. Thus, theoretical modeling needs to be accompanied with corresponding experimental measurements to conclusively address the issue. This is obviously not very convenient in cases, where large sets of different frameworks are considered and theoretical pre-screening could save a significant amount of time. In this work, we propose to closely inspect the accuracy of different approaches ranging from various force-fields to very accurate ab initio calculations and compare their performance against well-defined set of experimentally available structures.
Primary Investigator: Paolo Nicolini
Project: Molecular Dynamics simulations for investigating tribological properties of Vanadium Pentoxide (MD4V2O5)
Allocation: 2361000 core hours
Abstract: Effective lubrication and wear protection at high temperature and in cyclic environments are hot topics in mechanical engineering. Traditional solid lubricant coatings degrade at elevated temperatures due to their low oxidation resistance. To overcome this shortcoming, self-lubricant coatings have been developed by combining the intrinsic properties of some binary or ternary films with specific elements that diffuse to the surface and formed a low friction tribolayer. Vanadium is a very popular choice since it forms an oxide at the coating surface, which reduces friction, and it melts at relatively low temperatures providing liquid lubrication. Little is know about the lubrication mechanism of vanadium pentoxide. This lack of knowledge on the experimental conditions leading to the best performance of the lubricant (e.g., film thickness, working temperature and pressure, etc) prevents the possibility of efficiently designing such coatings. The core objective of the present project is the simulation-based design of a novel nanocomposite structure with controlled diffusion of lubricious metals. By means of molecular dynamics simulations I plan to elucidate: i) the most favorable structures formed by exposing metallic vanadium to humid air in tribological conditions, ii) the fundamental lubrication mechanism of vanadium pentoxide, and iii) the influence of the working conditions on the tribological performance of the material.
Primary Investigator: Thibault Derrien
Project: MORILLE (First-principle modeling of materials excitation and optical response upon intense laser irradiation)
Allocation: 1780000 core hours at first period
Abstract: The excitation of solids triggered by high intensity laser irradiation induce nontrivial electronic and optical responses that can be described using quantum approaches. Time-dependent density functional theory (TDDFT) is an accurate method to study these phenomena, in particular in the field of laser processing for which the existing parametrizations are sufficient to address a number of materials excitation. Within this project, the HiLASE RP4 theory group (IoP, IP-ASCR) will use HPC to simulate a number of experimental situations relevant to laser materials interaction using the quantum simulation package Octopus. Novelty of the present proposal is found in bringing the existing theoretical “large-scale” descriptions (available at HiLASE Centre) of one- and bi-color laser-irradiated materials to a predictive stage. The existing TDDFT database will be extended to a selection of materials (metals, semiconductors and dielectrics) for a number of irradiation conditions. In particular, the transient changes of optical properties upon irradiation will be studied from first-principles. This proposal also comes to support the newly funded H2020 Marie Curie RISE project “ATLANTIC” in which HiLASE Centre is one of the main actors. A training on the TDDFT simulation package Octopus and large data management will be provided to the incoming researchers hosted by the HiLASE Centre within the frame of the “ATLANTIC” project, using the IT4I resources. See http://www.quantumlap.eu/.
Primary Investigator: Petr Kulhanek
Project: Importance of Intercalation in DNA Mismatch Recognition
Allocation: 860000 core hours
Abstract: Watson-Crick base pairs are essential for keeping the integrity of DNA and fidelity of genetic information inheritance. However, there are many other base pairs (mismatches) that are similar in structure and strength of the interaction, but life has developed very effective pathways for their recognition and removal. One of them is the Mismatch Repair (MMR) pathway, which recognizes mismatches by the MutS protein. Corrupted DNA is sharply bent in the complex with MutS and the base step containing a mismatch is intercalated by conserved aromatic amino acid residue from MutS. In this project, we will determine the impact of the intercalation on the mismatch recognition employing advanced computer simulations and specially designed geometrical parameters allowing a precious evaluation of bending and navigation of intercalator into the DNA with a mismatched base pair. Obtained data will be helpful for better understanding of sequence-dependent mutability or designing chemical substances suitable for anti-cancer therapy targeting damaged DNA.
Primary Investigator: Marie Behounkova
Project: Thermomechanical processes in icy moons
Allocation: 350000 core hours at first period
Abstract: The last twenty years have seen significant progress in our understanding of the icy moons of Jupiter and Saturn. The observations of Jovian system by Galileo spacecraft and Saturnian system by Cassini spacecrafts suggest that some of the moons contain subsurface oceans. Special attention has been paid to Europa and Enceladus since both moons are expected to have an internal ocean in direct contact with the silicate interior and the conditions at the ocean floor may be similar to those on the Earth at the time when life appeared. On larger moons, such as Ganymede and Titan, the analogy with the Earth is less straightforward due to an expected layer of high-pressure ice below the ocean reducing the contact of the liquid water with silicates. The observed features and activity as well as their evolution and stability are shaped by processes that occur in the interior of icy moons such as tidal deformation, thermal convection, melt generation and material transport. Numerical modeling of these processes has been proven an invaluable tool for interpretation of the observation and for assessing their long-term evolution and stability of the environment possibly supporting life. Here, we will concentrate on models of icy moons’ deformations from diurnal to geological timescales and their interaction.
Primary Investigator: Martin Beseda
Project: Ab initio computations of potential energy surfaces in a dinitrogen cation
Allocation: 66000 core hours
Abstract: Modeling of cold rare-gas plasmas is currently one of the popular topics in the field of quantum chemistry because of their possible applications in many other fields, e.g. surface treatment, food industry or plasma medicine, with the last being the most interesting to our team. It was shown previously that rare-gas plasmas are well-working in such applications, which resulted in a broad research in this field. To understand the healing properties of cold rare-gas plasmas, a detailed knowledge of processes on the microscopic level is of crucial importance. Initially, interactions between rare-gas ions and air molecules will be calculated with the main focus on the simplest rare-gas (He) and the most abundant air molecule (N2), i.e. the collision complex [N2/He]+. The important prerequisite for that research is a description of potential energy surfaces of dinitrogen cation N2+. Those can be computed using „classical“ ab intio approach, utilizing Configuration Interaction (CI) method. The main challenges of the project are a) finding the right active space, b) the right basis set and c) CI parameters, as ab initio methods tend to have numerically unstable behavior very often. This project is a continuation of the project Modeling of plasma interactions using machine learning methods (OPEN-14-25).
Primary Investigator: Václav BAZGIER
Project: Virtual screening of human and plant hormones
Allocation: 437000 core hours
Abstract: Virtual screening is a computational method that allows to discover potentially new chemical compounds based on structures of biological macromolecules1. This project is focused on design of new chemical compounds and their derivatives in relation to hormones and other biologically active compounds. These hormones plays crucial role in human, animal and plant life and are responsible for a number of biological interest processes. The design of new compounds will be provided by the molecular docking technique.2 This technique allows to run virtual screening of proposed molecules over multiple targets to select potential compounds for further in-vitro or in-vivo testing and thus to help in the design of new hormone-based drugs or fertilizers.
Primary Investigator: Pavel Hobza
Project: In silico drug design
Allocation: 8016000 core hours
Abstract: Modern drug design makes use of the understanding of diseases in molecular basis. Drugs exert their action by binding to their biological targets, thus modulating or inhibiting their functions. Reliable prediction of noncovalent interactions is critically dependent on the use of computationally demanding quantum mechanics (QM). In our laboratory, we have developed1-4 and successfully applied5-16 the corrected semiempirical QM (SQM) methods for accurate description of protein-ligand interactions. It makes it possible to reliably describe not only classical noncovalent interactions but also non-classical ones like halogen, chalcogen, pnictogen and dihydrogen bond occurring in complexes of protein with novel types of unusual inhibitors.17-18 The methods also successfully describe covalent bonding which allow us to investigate any type of protein inhibitor. We are using this knowledge and experience on developing our own Computer-aided drug design framework. This framework can help to reduce the amount of experimental work and expenses by prioritizing compounds for synthesis and biological screening with a higher success. Moreover, it provides insight into the drug action at the molecular level. We have ascertained that such an approach outperforms classically used scoring functions in both ligand ranking16 and identifying the ligand native pose in cognate docking.15,19,20 To further improve and validate our methodology, we are carrying out large-scale virtual screening studies using extended databases of therapeutically relevant targets with active molecules and decoys. Currently, we are evaluating how this methodology improve “enrichment” in screening studies.
Primary Investigator: Miroslav Voznak
Project: Modal split detection from mobile networks
Allocation: 700000 core hours
Abstract: Popular abstract: Enhanced awareness about the behaviour of transport network participants could improve the quality and the extent of the services provided by a public authorities and a private sector. Consequently, more passengers could use public transport. This will positively affect the increase in the efficiency of means allocated for public passenger transport, reduced congestions within road network, increased comfort of travelling, less stress for transport network participants, less polluted environment and last but not least increased attractiveness of the disadvantaged regions. We use our expertise in mobile networks signaling data processing to extract O-D matrixes (relation information about trip’s origin and destination), traffic intensity, movement speed, trip length, traffic density in certain areas, etc. Aims and objectives The application is directly related to solving an approved TAČR https://starfos.tacr.cz/en/project/TE01020155, transport systems development centre (project). Our task as a project member is to utilize the expertise and knowledge in the sphere of mobile networks and deliver a data layer of origin – destination matrix (O-D layer) of population mobility in the Czech Republic for selected major relations corresponding to highways and tier 1 road network and back bone railway network. O-D streams volumes on relations in the layer will be labeled with transport mode (bus, train, car). Part of the layer is its validation against former project results, i.e. build in traffic counters data and floating cars data. To achieve the result, we need to 1. setup transport infrastructure map equipped with origin destination of nodes based on parameters (best time, shortest arrival time etc) and combine this layer with traditional land use layers such as constructions objects (line constructions, construction of public facility, etc.) and overlay the map with best service availability maps of mobile networks to create reference data multilayer, 2. search the match mobile phones signaling data with the given route in given time.
Primary Investigator: Mauricio Maldonado Dominguez
Project: Radical Catalysis by Biomimetic Polynuclear Transition-Metal Active Sites
Allocation: 602000 core hours
Abstract: Our first goal is to develop a methodology to accurately reproduce the available experimental redox potentials and acidity constants of binuclear Fe2S2 clusters reported for bioinspired complexes related to the Rieske and mitoNEET proteins. The latter is of special interest since only recent studies have begun to unravel its actual significance to human health and the treatment of diseases and is currently becoming a target for the alleviation of cancer and diabetes. We will then study the thermodynamic contributions (both the classical Bell-Evans Polanyi and a nonclassical component we recently proposed) to their reactivity, specifically the dependence of the rate constants with the free energy of reaction and asynchronicity factors for H-atom transfer between these complexes and model substrates. We will apply standard DFT combined with multireference quantum-chemical methods to achieve these goals. The calibrated protocol will serve as a cornerstone for the posterior investigation of Fe2S2 and Fe4S4 containing proteins, with a great potential to be translated into functional and stable bioinspired catalysts for the efficient production and derivatization of molecular targets.
Primary Investigator: Barbora Planková
Project: Molecular and mesoscopic simulations of aqueous solutions in inhomogeneous environments
Allocation: 1159000 core hours
Abstract: Aqueous solutions are omnipresent in nature, industrial processes and daily life. Understanding their behavior in inhomogeneous environments (nanopores, self-assembled systems) is important in many key applications such as medicine or enviromental protection. In this project, we focus on three water systems: graphene-aqueous electrolyte interfaces, surfactant adsorption on soft surfaces and solubilisation of small molecules into polymeric structures. We use molecular and mesoscopic simulations to provide the molecular-level insights into these water systems and to also fill gaps in our understanding of their physical and chemical behaviour of these systems.
Primary Investigator: Piya Changmai
Project: Archaeogenetic Study of Human Populations in Mainland Southeast Asia
Allocation: 350000 core hours
Abstract: Genome-wide genetic studies of ancient human populations changed our view on prehistory of Indo-European speakers and other groups in West Eurasia, shaping archaeogenetics as one of the fastest-growing scientific fields of recent years. Mainland Southeast Asia is a region with high ethnolinguistic diversity, but so far there are not many studies on populations in this region. The spread of Indian cultural influence in Mainland Southeast Asia (MSEA) in early 1st millennium CE and the spread of Tai-Kadai languages at some point before the 13th c. CE were events that had profound influence on the history of the region. It remains controversial if spread of people or ideas and languages was responsible for these events, and their dating also remains obscure. We have newly generated genotype data from 10 present-day populations from Thailand which their languages belong to 4 different families of languages and the populations have different historical background. We combined our data with published data from present-day and ancient populations. Using various methods (PCA, f-statistics, qpAdm, and ADMIXTUREGRAPH), we will trace Indian ancestry and genetic structure of populations in MSEA to investigate interactions between populations and the spread of Indian influence and Tai-Kadai languages in the region. We also have follow-up plan to sequence samples from ancient bones in the region. Selection of ancient samples and direction of the future study will be dependent on the results of our current research.
Primary Investigator: Jakub Zelezny
Project: High-throughput transport in unconventional magnetic systems
Allocation: 2612000 core hours
Abstract: Among magnetically ordered materials, ferromagnets are the best known and the most explored, however, many other types of magnetic order exist. Their usefulness has been often underestimated in the past, but they have been attracting attention recently, mostly in connection with spintronics: the field which studies how the spin of the electron (in addition to its charge) can be utilized in novel micro- and opto-electronic devices. Unconventional magnetic orders such as antiferromagnets or non-collinear magnetic orders can bring various advantages or new functionalities for such devices. For example, antiferromagnets have naturally fast magnetic dynamics which could be utilized for very fast computer memories. To utilize the unconventional magnetic materials, it is necessary to identify methods allowing for electrical means of detecting and manipulating their magnetic order. In ferromagnets, many such methods exist, however, their understanding in more complex magnetic systems is at its infancy. Within this project we will utilize first principle quantum physics calculations to explore the physics of transport in unconventional magnetic systems and to identify materials and methods of interest for future experiments or applications. To explore a large number of materials we will automatize the calculation process so that properties of a large number of materials can be calculated.
Primary Investigator: Andrzej Kadzielawa
Project: Superconductivity in hydrogen-rich compounds
Allocation: 1124000 core hours
Abstract: Recent development in the high-pressure physics provides us with a new class of the superconducting materials, namely with the hydrogen-rich materials, such as silane (transition temperature Tc = 17 K at pressure p = 96 GPa), hydrogen sulphide (Tc = 203 K @ 150 GPa) or hydrogen lanthanide (Tc = 274-286 K @ 210 GPa). We are planning to extended our original Exact Diagonalization Ab-Initio (EDABI) method, to describe superconductivity in hydrogen-rich compounds. Starting from the extended Hubbard model, we examine an electron-correlation-driven conductivity connected with the creation of high-symmetry hydrogen molecular and atomic planes, as well as a series of both structural and electronic-in-nature quantum phase transitions. For the realistic cases, we plan to obtain effective electron-phonon Hamiltonian for which we can estimate both the zero-point motion of the lattice ions, as well as of the electron-lattice coupling. This, by using the McMillan formula allows estimation of the superconducting transition temperature versus the effective pressure (external and/or chemical) acting on the plane. Whole project will be a natural extension of existing library of Quantum Metallization Tools (bitbucket.org/azja/qmt).
Primary Investigator: Jiri Klimes
Project: Accuracy and precision for extended systems II
Allocation: 1875000 core hours
Abstract: Materials bound by non-covalent interactions are important both in nature and industries. From methane clathrates at the bottom of the sea, over pharmaceuticals in pills, to derivatives of layered systems such as graphite. Many of them have also some peculiar properties. For example, even at the same conditions, many pharmaceuticals can exist in different crystal structures, called polymorphs. One of these polymorphs is the most stable, but the others are usually very close in energy. One of the long term goals of our project is to develop a theoretical modelling scheme that would allow a reliable description of the stability of the different polymorphs or different phases of materials in general. The problem is that to get the tiny energy differences between different phases, we need to use quantum mechanics. Solving the equations of quantum mechanics is only possible for simple systems and for extended systems we need to use approximations. To reach our goal we want to combine one of the most accurate schemes currently available for the treatment of extended systems with a method used to calculate reference quality binding energies of molecules. Moreover, we want to develop methods that will ensure that our results are very precise and thus reproducible. This will enable us to obtain highly reliable binding energies of extended systems.
Primary Investigator: Jan Martinovic
Project: Weather and Climate Pilot (H2020 LEXIS Project)
Allocation: 394000 core hours
Abstract: The increasing quantities of data generated by modern industrial and business processes pose enormous challenges for organizations seeking to glean knowledge and understanding from the data. Combinations of HPC, Cloud and Big Data technologies are key to meeting the increasingly diverse needs of large and small organizations alike. Critically, access to powerful compute platforms for SMEs – which has been difficult due to both technical and financial reasons – may now be possible. The H2020 LEXIS (Large-scale EXecution for Industry & Society) project, under the IT4Innovations coordination, will build an advanced engineering platform at the confluence of HPC, Cloud and Big Data which will leverage large-scale geographically-distributed resources from existing HPC infrastructure, employ Big Data analytics solutions and augment them with Cloud services. Driven by the requirements of the pilots, the LEXIS platform will build on best of breed data management solutions (EUDAT) and advanced, distributed orchestration solutions (TOSCA), augmenting them with new, efficient hardware capabilities in the form of Data Nodes and federation, usage monitoring and accounting/billing supports to realize an innovative solution. The consortium will develop a demonstrator with a significant Open Source dimension including validation, test and documentation. It will be validated in the pilots – in the industrial and scientific sectors (Aeronautics, Earthquake and Tsunami, Weather and Climate) where significant improvements in KPIs including job execution time and solution accuracy are anticipated. This proposal is specifically focused on computing resources about the Weather and Climate pilot. This pilot is aiming at facilitating a complex stack of weather-related computational models to improve the prediction of water-food-energy nexus phenomena and their associated socio-economic impacts.
Primary Investigator: Tomas Karasek
Project: Cloudification of Production Engineering for Predictive Digital Manufacturing
Allocation: 350000 core hours
Abstract: In October 2017, the Horizon 2020 Innovation Action “CloudiFacturing” (www.cloudifacturing.eu) was launched and 33 project partners from all over Europe came together at Fraunhofer IGD – the coordinator of the Innovation Action – in Darmstadt, Germany. The mission of CloudiFacturing is to optimize production processes and producibility using Cloud/HPC-based modelling and simulation, leveraging online factory data and advanced data analytics, thus contributing to the competitiveness and resource efficiency of manufacturing SMEs, ultimately fostering the vision of Factories 4.0 and the circular economy. This project will support seven application experiments from 2nd wave of the experiments conducted by CloudiFacturing project: Flowforming process calibration via cloud optimization (FLOWCALOP), Smart thermoplastic injection (SHION) and Optimization of the production process of metal structures using OSICE (OSICS).
Primary Investigator: Tugba Dogan
Project: Analyzing Urban Heat Island Effect in Prague in Changing Climate Using Regional Climate Model
Allocation: 32400 core hours
Abstract: Land use change and greenhouse gas emission have been known as the main causes of climate change, which inherently interlinked with Urban Heat Island Effect (UHI). This project aims to help bridge the gap in understanding the relationship between trends in global/regional temperature change and UHI effect with using state of art regional climate model to dynamically downscale global climate models. The Weather Research Forecasting model (WRF) will be set up with climate-oriented land cover classification, Local Climate Zones (LCZ), for past (1990-2000) and future (2040-2050) experiments. The master plan of Prague provided by Planning Institution of Prague will be used to create LCZ. Climate projections will be produced by using Global Climate Models (GCM) forced by two different Representative Concentration Pathway (RCP) emission scenarios to compare the effect of the different emissions. The results will be a database for urban planners and decision-makers to achieve climate sensitive urban planning.
Primary Investigator: Tomas Martinovic
Allocation: 44000 core hours
Abstract: Tsunamis have, in recent years, made the news as a disaster with huge numbers of victims, including in areas that have felt nothing of the earthquake generating the tsunami, where beachgoers could only contemplate the damage and loss of lives of a huge wave. To handle that, the LEXIS project (H2020 – EU) work on integrating tsunami simulations into the emergency process. But a tsunami simulation with TsunAWI takes hours to run where people may have only minutes before the wave strikes. So the open call is to study how TsunAWI can be tuned with it’s input data to know how much time a simulation will take, running it with many different adjustements on the data and measuring how long it takes to run a simulation and how precise the result is. At the end, we will know, in a situation where we have a given set of resources and a target time to run, which input data and parameters we need to give to TsunAWI to get the best tsunami wave estimate, and, in the end, properly warn people at risk. The challenge is to provide warning information on a large scale. Since especially the extent of inundation events depends strongly on the tsunami source, pre-calculated products can only contain coarse estimates. On-the-fly calculations during an event with better knowledge of the source are costly but good preparations can help to reduce the computational burden for example by adjusting the mesh to the least necessary resolution and optimizing the friction parameters. The model employs triangular meshes, therefore there is large flexibility for resolving necessary features adequately. Furthermore a probabilistic investigation with a large number of scenarios with a realistic range of magnitudes for a given region can give insights into the possible spread of inundation depth to be expected in beforehand (compare also Glimsdal et al. 2019, Grezio et al, 2017).
Primary Investigator: Pavel Plevka
Project: IT resources to characterize virus structures and replication
Allocation: 2113000 core hours at first period
Abstract: Many viruses are important human and animal pathogens with significant societal and economic impact. In contrast, bacterial viruses – bacteriophages have the potential to be developed into therapeutic tools to treat bacterial infections instead of antibiotics. We use cryo-electron microscopy and tomography to study virus structure and replication. Our efforts are directed towards using structural information to facilitate development of treatments for human and animal diseases. Our research is focused on five projects: (1) Human picornaviruses that are the causative agents of diseases ranging from common cold to more serious illnesses such as foot, hand, and mouth disease or encephalitis. (2) Viruses that contribute to collapses of honeybee colonies. (3) Bacteriophages that infect pathogenic bacteria Staphylococcus aureus and Pseudomonas aeruginosa and, therefore, have potential to be utilized for treatment of bacterial infections. (4) Tick borne encephalitis virus, which is widespread in the Czech Republic and Central Europe and causes potentially lethal disease of nervous system. (5) Leishmania RNA virus 1 that contributes to the severity of human disease leishmaniasis.
Primary Investigator: Dominik Legut
Project: Role of defects on heat transfer in novel nuclear fuels
Allocation: 4810000 core hours at first period
Abstract: The subject of the current project is to determine the effect of defects on the heat transfer of the nuclear fuel materials considered for IVth generation reactors, specifically, actinide compounds, such as uranium, thorium, and neptunium carbides. Comprehensive studies of the electronic, magnetic, elastic, dynamical, and thermodynamical properties of various phases in the (U/Np/Th/Pa)-C systems are to be carried out based on large scale quantum-mechanical calculations. The primary goal is to gain insight into the nature of the thermal expansion and thermal conductivity phenomena, which belong to the most significant quantities for the design of fuels for the IVth generation nuclear reactors. The thermal expansivity and the heat transport of these materials show anomalies which are hardly understood. In addition it is not clear at which temperature the heat is transferred by phonons or by electrons. Due to the self-irradiation accumulating with time the compounds are neither stochiometric nor defect free. Therefore, in this project a high importance is devoted to establishing the role of fission products, such as vacancies, oxygen impurities, and off-stochiometry in the thermal expansivity and conductivity of these materials. The proposed project extends standard ab initio investigations to the modeling properties of potential nuclear fuel materials at real conditions utilizing large HPC resources.
Primary Investigator: Jiri Hanzelka
Project: Betweenness centrality algorithm for global view of traffic network
Allocation: 122000 core hours
Abstract: A lot of the systems that at first glance appear to be very complex can be simplified. A popular approach is to substitute such system with an abstract structure that keeps the maximum amount of knowledge about it but is simple enough to further work with it. One widespread method is to replace objects with dots and relations between objects with lines. Created structure is in mathematics known as a graph and accompanying study of the graph’s properties is called a graph theory. Described methodology is used in many areas where we want to study objects and their relations, like sociology, biology, traffic monitoring, information sciences and many others. Our research is aimed at the structure and the inner workings of the graph. We want to extract additional information from the structure so we can better understand the complexities of the described problem. Since the studied graphs are enormous, it is necessary to use high-performance computing to get results in adequate time. Because of this, we also have to develop our own algorithms that are tailored for the high-performance computing infrastructure.
Primary Investigator: Jaroslav Hron
Project: Patient specific geometry flow simulations III
Allocation: 240000 core hours at first period
Abstract: The goal of carotid endarterectomy is prevention of ischemic stroke, one of the most common causes of morbidity or mortality in developed countries. The current indication criteria are primarily based on the grade of stenosis caused by the atherosclerotic plaque. The development and the character or the plaque are probably influenced by the hemodynamics in the carotid arteries. The goal of our project is to describe the relationship between the hemodynamic parameters and the character of the plaque. The mathematical calculations will be verified with laboratory modelling. There are two main sub goals – 1. To correlate hemodynamic parameters in the carotid artery using CFD modelling with the histological characteristics of the plaque. 2. To validate our CFD analyses using laboratory models.
Primary Investigator: Lukas Sukenik
Project: Mechanism of genome release of non-enveloped viruses
Allocation: 4081000 core hours
Abstract: Many picornaviruses are human pathogens that cause diseases varying from common cold to life-threatening encephalitis. Currently, there is no picornavirus antiviral drug approved for humans. At the beginning of infection, these non-enveloped viruses need to transport their genetic material from the protective protein shell to host cytoplasm. However, the molecular mechanisms of this process remains elusive. We propose to investigate molecular details of genome release by means of coarse-grained molecular dynamics simulations. We will employ two different levels of coarse- graining and investigate how the capsid properties affect the genome release. The obtained data will be compared to experiments. The knowledge obtained will be useful for understanding viral infection process and could be utilized to the development of new antiviral therapeutics.
Primary Investigator: Daniela Szturcova
Project: Traffic Simulation
Allocation: 94000 core hours at first period
Abstract: A combination of cloud and high performance computing resources to use traffic simulation is able to optimize traffic flow in a macro scale. A distributed system for serving vehicle routing requests was developed in the ADAS laboratory. Its testing over a country area with tens or hundreds of thousands of vehicles will help us to compare various routing algorithms and strategies as well as to verify their performance in real life. The main aim of the project is to extend the functionality of a traffic simulator CaSim, which is one of the components of a server-side navigation system developed in ADAS lab at IT4Innovations. The simulator was used for validation and testing of the server-side navigation system, which was a part of the H2020 project ANTAREX use case. One of the goals of this effort is to determine concrete cost figures for various types of operations and amounts of vehicles in order to make the service attractive to potential commercial exploitation.
Primary Investigator: Pezhman Zarabadi-Poor
Project: High-Throughput Screening of Metal-Organic Frameworks for CO2 Separation from Post-Combustion Gas Mixture under Humid Condition
Allocation: 3308000 core hours
Abstract: This proposal is devised to provide reliable solutions to avert the climate change issues. This emerging issue results from anthropogenic CO2 emission. In this regard, metal-organic frameworks (MOFs) are considered as attractive solid adsorbents that can efficiently be utilized for carbon capture from one of main sources of CO2 emission, i.e. post-combustion gas. There are practically enormous number of MOFs that we need to search among for finding suitable adsorbent for the separation process of interest. On the other hand, post-combustion gas mixture comes with considerable amount of humidity which results complication in separation of CO2. In the current project, extensive computational investigations are proposed to benefit from high-throughput screening for identification of best performing MOFs that can separate CO2 from post-combustion gas mixture. It is expected that the outcome of this project will provide social, economic, and environmental benefits by providing reliable solutions to avert the climate change resulting from CO2 emission.
Primary Investigator: Frantisek Karlicky
Project: Two Dimensional Crystals and van der Waals Heterostructures
Allocation: 1202000 core hours at first period
Abstract: Current needs of applied research on two-dimensional (2D) materials for flexible and ultrathin functional devices require computational predictions and computer aided design. We will systematically study physical properties of 2D materials and their heterostructures like electronic and optical properties including excitonic effects. For the presence of delicate interplay of multiple effects in 2D materials, accurate predictions of their properties require accurate and costly many-body methods instead of usual density functional theory, that makes these computations demanding for single-layers, almost unfeasible for large incommensurate van der Waals heterostructures and intermediate demanding approximate methods will be therefore devises and assessed as tool for reliable computer aided design of new 2D materials with tailored properties for a new-generation of solar cells and functional devices.
Primary Investigator: Tomas Karasek
Project: Scalable distributed MultiLevel MonteCarlo workfow design
Allocation: 350000 core hours at first period
Abstract: The ExaQUte project aims at constructing a framework to enable Uncertainty Quantification and Optimization Under Uncertainties in complex engineering problems using computational simulations on Exascale systems. The stochastic problem of quantifying uncertainties will be tackled by a Multilevel Monte Carlo approach that allows using a high number of stochastic variables. Gradient-based optimization techniques will be extended to consider uncertainties by developing methods to compute stochastic sensitivities. The application chosen as a demonstrator focuses on wind engineering, which includes the quantification of uncertainties in the response of civil engineering structures to the wind action, and the shape optimization taking into account uncertainties related to wind loading, structural shape and material behavior.
Primary Investigator: Ondrej Chrenko
Project: Migration of giant planets in stellar-irradiated disks
Allocation: 669000 core hours
Abstract: Giant planets (i.e. planets similar to Jupiter or Saturn) are massive planetary bodies with extended gaseous envelopes that were formed in protoplanetary disks. There is both observational and theoretical evidence that giant planets gravitationally interact with their natal disk in a way that they are forced to migrate deeper into the disk, towards the central protostar. Since the solar-system giant planets and a great number of giant exoplanets are observed at separations exceeding 1 astronomical unit (au), one may argue that they must have formed at ~20 au in order not to migrate below 1 au. However, the timescale for giant planet formation at 20 au is too long to be feasible and this poses a conundrum. Either the formation mechanism is understood poorly or the migration must have been slower or even directed outward. In this project, I envisage the latter possibility. More specifically, I investigate the scenario proposed by : As the giant planet carves a gap in the surrounding disk, the outer edge of this gap may receive radiation from the central protostar. The edge heats up and its structure changes so that its gravitational influence allows for outward migration of the planet. Since this scenario was previously studied only in a simplified 2D hydrodynamic model, I propose to verify it using 3D hydrodynamic simulations with radiation transfer.
Primary Investigator: Jan Novotny
Project: Paramagnetic NMR of dynamic drug-carriers systems by Respect program
Allocation: 2087000 core hours
Abstract: Current strategies of cancer treatment utilizing coordination compounds of transition metals are limited by non-specific action of these drugs and side effects. The binding of metallodrugs to functionalized carriers is considered as a promising way to diminish this deficiency. To perform a rational design of supramolecular drug-carrier systems, NMR spectroscopy together with quantum-chemical calculations pose a unique tool for structure-dynamic determination. However, paramagnetic nature of Ru(III) metallodrugs disables to apply conventional methods of NMR and therefore predictions provided by accurate relativistic calculations can help to gain correct interpretations of experimental observations. In this project we will use computational resources provided by IT4I infrastructure to use recently developed fully relativistic methodology1 for calculations of magnetic response properties in paramagnetic host-guest systems. Based on conclusions from calibration and testing calculations, optimized protocols will be used to acquire production data on series of experimentally characterized complexes. Complementarity of this proposal with research interests of the group of applicants will substantially facilitates further development of paramagnetic NMR spectroscopy applied on real supramolecular assemblies.
Primary Investigator: Martin Culka
Project: Factors Defining Protein Fold Seen through Quantum-Chemical Lens
Allocation: 1791000 core hours
Abstract: The principles behind protein folding, i.e. how the information in the amino acid sequence is transformed into the final 3D structure, are a long standing mystery in molecular biology. Although multiple folding and unfolding events of primary protein sequence have been observed in vitro, the physical principles behind the process remain elusive. We will employ quantum-chemical (DFT) calculations, which have been proven to represent chemical phenomena with reasonable accuracy, to describe strain and interaction energies along the protein fold. We plan to analyze three small well-studied proteins: all-α albumin-binding domain, all-β WW domain and α-β immunoglobuling-G binding protein. The resulting energetic map of the protein fold will be compared with amino acid conservation and known facts on folding mechanism of the respective proteins.
Primary Investigator: Pezhman Zarabadi-Poor
Project: High-Throughput Screening of Metal-Organic Frameworks for Xenon Recovery
Allocation: 525000 core hours
Abstract: Metal-Organic Frameworks (MOFs) are a class of advanced materials that have attracted lots of attentions during last decade due to their unique properties. MOFs are constructed from the combination of organic linkers and metal nodes which results in having almost infinite possible structures. MOFs found their place in several applications which are directly or indirectly related to the daily life concerns such as removal of anthropogenic carbon dioxide to decelerate global warming or hydrogen and methane storage to provide a safer way of building energy-efficient vehicles. One of the most recent studies proved that they also can be employed to provide xenon at lower prices through its recovery from exhaled anesthetic gas mixture. We plan to benefit from excellent supercomputing resources to screen thousands of MOFs for adsorption-based and diffusion-based separation of xenon from exhaled anesthetic gas which provides us a list of potential MOFs. Consequently, we provide molecular level knowledge on the top performing structures using cutting-edge simulation techniques to study our compounds of interest and design novel and better adsorbents. It will build a valuable database for consequent experimental researches and save tremendous amount of time and energy. Last but not the least, outcomes of this project would finally result in providing xenon as anesthetic gas to a wide range of patients at lower price as well as promoting sustainability.
Primary Investigator: Valeria Butera
Project: DFT Investigations of Functional Waveguide Materials for MIR Sensors
Allocation: 656000 core hours
Abstract: Mid-infrared (MIR) based, monolithically integrated optical sensors are a recent and rapidly emerging research field. Combining bi-functional quantum cascade lasers and detectors with optical interconnects allows to transform formerly lab-sized spectroscopic setups into compact optoelectronic devices. This proposal supports the development of the next sensor generation by focusing on the adsorption and related reactions of analyte molecules on the waveguide surface in the interaction zone. The experimental counterpart will realize plasmonic, dielectric and hybrid waveguide structures, which allow the realization of highly integrated MIR sensors. Cluster-based density functional theory (DFT) will be applied to determine the chemical bonding behavior including possible charge transfer and resulting shifts in the absorption spectra of analyte substances. Our studies will be also complemented by periodic boundary condition (PBC) calculations that will allow us to consider larger surfaces and bulk structures. Findings obtained from the surface chemistry model will enable directed optimization of the sensing surface e.g. through engineered roughness or by exploiting field enhancement due to plasmonic near-field antennas. All components will be combined into advanced, fully-integrated protoype sensors, which open new opportunities for further application-oriented research.
Primary Investigator: Radek Halfar
Project: Investigation of dynamic properties of cardiac tissue
Allocation: 7000 core hours
Abstract: The heart is a complex organ on its continuous work is depending life of every human. Mechanical work of the heart is controlled by electrical signals propagated in its tissue. Violations of this system can lead to life-threatening conditions. The goal of this project is to investigate heart electrophysiology from the dynamic point of view and give insight into the propagation of cardiac action potential. For this purpose, the heart electrophysiology, described by a set of differential equations, is being investigated in order to find regular, as well as, chaotic motions.
Primary Investigator: Ctirad Cervinka
Project: Cohesive Properties of Ionic Liquids from First-principles Calculations
Allocation: 1093000 core hours
Abstract: Ionic liquids (ILs) possess a vast potential for numerous technologies − gas capture, smart electrolytes, polymer or nanoparticles exfoliation). ILs also exhibit unique properties such as low volatility, large electrochemical window or a boundless structural variability. Broader exploitation of their beneficial characteristics is impeded by their cost, limited availability of the physico-chemical data or an insufficient understanding of ILs-related phenomena. Concomitantly, literature on ILs is growing unprecedentedly, although the quality of the published data is sometimes at least questionable. Known for a century and considered absolutely nonvolatile for decades, ILs were proved to possess a nonzero saturated vapor pressure only a decade ago. Still, ILs are orders of magnitude less volatile when compared to common molecular solvents. Low volatility of ILs, being one of their most valuable properties, is also the principle factor making reliable measurements of their vapor pressures and heat of vaporization extremely difficult. However, heat of vaporization can be also obtained from the heat of sublimation and heat of fusion. While the latter can be obtained via calorimetric experiments with a fair accuracy, the former is in principle accessible through ab initio computations. This work assesses the performance of ab initio predictions of sublimation of ionic liquids, aiming to replace the difficult and hardly reproducible vaporization experiments with calculations.
Primary Investigator: Maninder Kaur
Project: High quality electron beam generation via Laser wakefield acceleration for development of XFEL
Allocation: 700000 core hours
Abstract: Unique parameters of electron beams produced by Laser Wakefield Accelerators (LWFA) such as very short bunch length and high energy of a few Gev in extremely compact geometry make it very attractive for the new generation Free Electron Laser (FEL) development. Although the LWFA beam quality is still significantly lower than provided by conventional radio-frequency accelerators, with constant improvements they have a great potential to be considered as a new basis for FEL’s and even colliders. Our main focus in this project is to investigate the generation of the electron bunch with few MeV with improvement in parameters such as energy spread, divergence, emittance, charge, current etc. so as to consider it for realization of X-ray FEL in the frame of LUIS project being commisioned at ELI beamlines. This can be done by 1) optimizing the density target. For stable electron injection and acceleration to MeV’s energy, the laser should interact with lower density plasma over longer distances which motivates us to use gas-filled capillary discharge waveguide. 2) Electron injection schemes, various schemes such as self-injection, ionisation-induced injection and density graident injection can be employed for enhancing the quality of accelerated electron beam. The X-ray emission is assumed to be correlated to the accelerated electron beam charge. Therefore the production of a reliable beam charge would benefit future developments and applications of this table-top X-ray source.
Primary Investigator: Miroslav Jícha
Project: Surfactant delivery to infants and children respiratory tract to suppress Respiratory Distress Syndrome
Allocation: 87000 core hours
Abstract: The respiratory system is one of the most important barriers between the human body and the environment. Infants and children are more exposed to air pollution compared to adults relative to their size, due to higher ventilation per minute. Due to different development stages of nasal and oral cavities in the early ages there is a big difference between breathing in infants/children and adults. A major problem associated with the structural immaturity in the lungs is a disease called Respiratory Distress Syndrome caused by lung surfactant deficiency. The treatment relies on Surfactant Replacement Therapy, which is mostly linked with mechanical ventilation and intubating that provides breathing support to infants. However the mechanical ventilation is a costly treatment and invasive. Therefore new surfactant administration is seeking that however requires a good knowledge on the flow field and aerosol transport and deposition in the lungs. In vivo studies in infants and children are prohibited, in vitro studies very limited therefore in silico (computational modeling) is a promising way. For that we need extremely powerful computers to allow for high number of control volumes reaching an order of 100 million to approach Direct numerical simulation. This could be enabled using lattice Boltzmann technique instead of solving Navier-Stokes equations.