Author

# Marek Sierka

Other affiliations: Autonomous University of Barcelona, Schiller International University, Humboldt University of Berlin ...read more

Bio: Marek Sierka is an academic researcher from University of Jena. The author has contributed to research in topics: Density functional theory & Infrared spectroscopy. The author has an hindex of 47, co-authored 147 publications receiving 7803 citations. Previous affiliations of Marek Sierka include Autonomous University of Barcelona & Schiller International University.

##### Papers published on a yearly basis

##### Papers

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TL;DR: In this article, a new computational approach is presented that allows for an accurate and efficient treatment of the electronic Coulomb term in density functional methods, which partitions the Coulomb interactions into the near and far-field parts.

Abstract: A new computational approach is presented that allows for an accurate and efficient treatment of the electronic Coulomb term in density functional methods. This multipole accelerated resolution of identity for J (MARI-J) method partitions the Coulomb interactions into the near- and far-field parts. The calculation of the far-field part is performed by a straightforward application of the multipole expansions and the near-field part is evaluated employing expansion of molecular electron densities in atom-centered auxiliary basis sets (RI-J approximation). Compared to full RI-J calculations, up to 6.5-fold CPU time savings are reported for systems with about 1000 atoms without any significant loss of accuracy. Other multipole-based methods are compared with regard to reduction of the CPU times versus the conventional treatment of the Coulomb term. The MARI-J approach compares favorably and offers speedups approaching two orders of magnitude for molecules with about 400 atoms and more than 5000 basis functio...

759 citations

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587 citations

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TL;DR: The adsorption and reaction energies are compared with the results from Møller‐Plesset second‐order perturbation theory with basis set extrapolation and errors due to missing self‐interaction correction are not affected.

Abstract: Ewald summation is used to apply semiempirical long-range dispersion corrections (Grimme, J Comput Chem 2006, 27, 1787; 2004, 25, 1463) to periodic systems in density functional theory. Using the parameters determined before for molecules and the Perdew-Burke-Ernzerhof functional, structure parameters and binding energies for solid methane, graphite, and vanadium pentoxide are determined in close agreement with observed values. For methane, a lattice constant a of 580 pm and a sublimation energy of 11 kJ mol−1 are calculated. For the layered solids graphite and vanadia, the interlayer distances are 320 pm and 450 pm, respectively, whereas the graphite interlayer energy is −5.5 kJ mol−1 per carbon atom and layer. Only when adding the semiempirical dispersion corrections, realistic values are obtained for the energies of adsorption of C4 alkenes in microporous silica (−66 to −73 kJ mol−1) and the adsorption and chemisorption (alkoxide formation) of isobutene on acidic sites in the micropores of zeolite ferrierite (−78 to −94 kJ mol−1). As expected, errors due to missing self-interaction correction as in the energy for the proton transfer from the acidic site to the alkene forming a carbenium ion are not affected by the dispersion term. The adsorption and reaction energies are compared with the results from Moller-Plesset second-order perturbation theory with basis set extrapolation. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008

234 citations

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TL;DR: In this article, a combined quantum mechanics (QM) and interatomic potential function (Pot) approach is described for ab initio modeling of the structure and reactivity of zeolite catalysts with both protons and transition metal cations as active species.

Abstract: The errors made when large chemical systems are replaced by small models are discussed: interrupted charge transfer, missing structure constraints, neglected long‐range interactions. A combined quantum mechanics (QM)–interatomic potential function (Pot) approach is described. Characteristic features of the QM‐Pot approach include: (1) periodic boundary conditions, (2) consistent definition of forces in the presence of link atoms that terminate the QM cluster, (3) interatomic potential functions parametrized on ab initio data and accounting for polarization effects, (4) use of reaction force fields (EVB potentials) in combination with QM methods for efficient localization of transition structures in large systems, (5) implementation as a loose coupling of existing QM and Pot engines. Comparison is made with some other hybrid QM/MM methods. Applications of the combined QM‐Pot method for ab initio modeling of the structure and reactivity of zeolite catalysts are reviewed with both protons and transition metal cations as active species. Potential functions of the ion‐pair shell‐model type available for such studies are compiled. The reliability of the method is checked by comparison with periodic ab initio studies and by examining the convergence of the results with increasing size of the QM cluster. The problems tackled are: different types of Cu+ sites in the CuZSM‐5 catalyst and their properties, acidity differences between active sites in different zeolite framework structures (energies of deprotonation, NH3 adsorption energies), and proton mobility in acidic zeolites. The combined QM‐Pot approach made possible a full ab initio prediction of reaction rates for an elementary process on the surface of solid catalysts and of how these rates differ between different catalysts with the same active site. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 1470–1493, 2000

205 citations

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TL;DR: In this article, an ion-pair shell model potential with functional parameters derived from the results of quantum mechanical density functional theory (DFT) calculations on small molecular models is used to predict the structure and properties of different silica and zeolite catalysts.

Abstract: An ion-pair shell-model potential with functional parameters derived from the results of quantum mechanical density functional theory (DFT) calculations on small molecular models is presented. It is used to predict the structure and properties of different silica and zeolite catalysts. Characteristic differences between the Hartree–Fock and DFT structures of quartz, silica sodalite and silicalite are revealed. A combined quantum mechanics–ion-pair shell-model potential scheme is presented and applied to embedded cluster calculations on catalytically active sites in periodic framework structures.

201 citations

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TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

24,496 citations

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TL;DR: The first steps towards using computational methods to design new catalysts are reviewed and how, in the future, such methods may be used to engineer the electronic structure of the active surface by changing its composition and structure are discussed.

Abstract: Over the past decade the theoretical description of surface reactions has undergone a radical development. Advances in density functional theory mean it is now possible to describe catalytic reactions at surfaces with the detail and accuracy required for computational results to compare favourably with experiments. Theoretical methods can be used to describe surface chemical reactions in detail and to understand variations in catalytic activity from one catalyst to another. Here, we review the first steps towards using computational methods to design new catalysts. Examples include screening for catalysts with increased activity and catalysts with improved selectivity. We discuss how, in the future, such methods may be used to engineer the electronic structure of the active surface by changing its composition and structure.

2,528 citations

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TL;DR: To model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region and an MM treatment for the surroundings, enabling the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

Abstract: Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

1,926 citations

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TL;DR: The General Utility Lattice Program (GULP) as discussed by the authors has been extended to include the ability to simulate polymers and surfaces, as well as adding many other new features, and the current status of the program is fully documented.

Abstract: The General Utility Lattice Program (GULP) has been extended to include the ability to simulate polymers and surfaces, as well as adding many other new features, and the current status of the program is fully documented. Both the background theory is described, as well as providing a concise review of some of the previous applications in order to demonstrate the range of its use. Examples are presented of work performed using the new compatibilities of the software, including the calculation of Born effective charges, mechanical properties as a function of applied pressure, calculation of frequency-dependent dielectric data, surface reconstructions of calcite and the performance of a linear-scaling algorithm for bond-order potentials.

1,793 citations

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TL;DR: In this paper, a review of the experimental methods for the production of free nanoclusters is presented, along with theoretical and simulation issues, always discussed in close connection with the experimental results.

Abstract: The structural properties of free nanoclusters are reviewed. Special attention is paid to the interplay of energetic, thermodynamic, and kinetic factors in the explanation of cluster structures that are actually observed in experiments. The review starts with a brief summary of the experimental methods for the production of free nanoclusters and then considers theoretical and simulation issues, always discussed in close connection with the experimental results. The energetic properties are treated first, along with methods for modeling elementary constituent interactions and for global optimization on the cluster potential-energy surface. After that, a section on cluster thermodynamics follows. The discussion includes the analysis of solid-solid structural transitions and of melting, with its size dependence. The last section is devoted to the growth kinetics of free nanoclusters and treats the growth of isolated clusters and their coalescence. Several specific systems are analyzed.

1,490 citations