SimLab NanoMicro

The simulation of nanostructured materials requires high performance computers and modern calculation methods, for example density functional theory and molecular dynamics.
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Complementing experiment and theory, computer simulation gains greater importance in materials research and life sciences. Simulations help to understand observed phenomena and even predict properties and scenarios in complex systems. Especially challenging is the quest for new materials and phenomena for which an experimental exploration without the knowledge from simulations would be prohibitive.

The calculation of properties of nanostructured materials is very demanding and requires deployment of high performance computer architectures and scalable programming models. Especially, these computer architectures pose challenges for code developers like improving parallelism, data locality and load balancing. Furthermore, novel materials have very complex morphologies that require a treatment on different size and time scales. On the shortest time/length (femtoseconds, nanometer) scale the structures are modeled with atomic resolution and the properties are calculated quantum mechanically using density functional theory (DFT). On larger size and time scale the systems are treated classically employing classical molecular dynamics (MD) methods. For larger size (micrometer up to centimeter) and timescales (> 1 millisecond) coarse-grain methods as well as continuum methods (finite element analysis, phase-field method) have to be employed.


The SimLab NanoMicro conducts joint research and development with the nanoscience and materials science communities focusing on better exploitation of capabilities of modern supercomputer facilities. Major tasks of the SimLab consist in development, maintenance and efficient deployment of simulation codes on high performance architectures, developing and deploying novel efficient highly scalable algorithms and providing integrated application solutions for the community.


Supported simulation codes: Turbomole, VASP, NWChem, Siesta, CP2K, NAMD, LAMMPS, Gromacs

Developed software

Research topics

  • Multiscale nanomaterials modeling and simulation: materials for organic electronics, carbon-based materials, materials for fuel cells and batteries
  • Adoption of novel approaches for integration and scaleup of the supported and developed simulation codes

Completed projects

”Multiscale modeling of materials building blocks for energy conversion and storage" - a joint project with the group of Wolfgang WenzelInstitute of Nanotechnology (INT) - funded by the Baden-Württemberg Stiftung in the framework of an HPC program.

HPC-5 ”High-throughput protein structure prediction on hybrid and distributed high performance architectures“ - a joint project with the group of Wolfgang WenzelInstitute of Nanotechnology (INT) - funded by the Baden-Württemberg Stiftung.

MMM∂HPC "Multiscale materials modelling on high performance computer architectures" - a FP7 project funded by the European Commission, grant agreement number RI-261594.

”Multiscale modeling and simulation of nanostructured materials for energy storage and conversion“ a joint project with the group of Gerd Schön and the Center for Functional Nanostructures (CFN) in Karlsruhe.

Former members of the SimLab

Dr. Saientan Bag
Dr. Alexej Bagrets
Dr. Martin Brieg
Dr. Julian Helfferich
Dr. Konstantin Klenin
Dr. Robert Maul
Dr. Velimir Meded
Dr. Angela Poschlad
Dr. Bogdan Yavorskyy
Dr. Asfaw Geremew Yohannes

Selected publications

  • S. Bag, P. Friederich, I. Kondov, W. Wenzel, Concentration dependent energy levels shifts in donor-acceptor mixtures due to intermolecular electrostatic interaction, Scientific Reports 9, 12424 (2019).
  • M. Berghoff, I. Kondov, J. Hötzer, Massively Parallel Stencil Code Solver with Autonomous Adaptive Block Distribution, IEEE Transactions on Parallel and Distributed Systems 29, 2282-2296 (2018).
  • P. Faubert, I. Kondov, D. Qazzazie, O. Yurchenko, C. Müller, A non-noble Cr–Ni-based catalyst for the oxygen reduction reaction in alkaline polymer electrolyte fuel cells MRS Communications 8, 160-167 (2018).
  • I. Kondov, P. Faubert, C. Müller, Activity and electrochemical stability of a chromium modified nickel catalyst for oxygen reduction reaction, Electrochimica Acta 236, 260-272 (2017).
  • P. Friederich, T. Strunk, W. Wenzel, I. Kondov, Multiscale Simulation of Organic Electronics Via Smart Scheduling of Quantum Mechanics Computations, Procedia Computer Science 80, 1244-1254 (2016).
  • P. Friederich, V. Meded, A. Poschlad, T. Neumann, V. Rodin, V. Stehr, F. Symalla, D. Danilov, G. Lüdemann, R. F. Fink, I. Kondov, F. von Wrochem, W. Wenzel, Molecular Origin of the Charge Carrier Mobility in Small Molecule Organic Semiconductors, Advanced Functional Materials 26, 5757-5763 (2016).
  • M. Walz, A. Bagrets, F. Evers, I. Kondov, Ab Initio Transport Calculations for Functionalized Graphene Flakes on a Supercomputer, In: W. E. Nagel, D. H. Kröner, M. M. Resch, (Eds.), High Performance Computing in Science and Engineering'15, Springer, 2015.
  • J. Li, I. Kondov, H. Wang, M. Thoss, Quantum dynamical simulation of photoinduced electron transfer processes in dye-semiconductor systems: theory and application to coumarin 343 at TiO2, Journal of Physics: Condensed Matter 27, 134202 (2015).
  • J. Setzler, C. Seith, M. Brieg, and W. Wenzel, SLIM: An improved generalized Born implicit membrane model, Journal of Computational Chemistry 35, 2027-2039 2014. (abstract)
  • P. Gerstel, S. Klumpp, F. Hennrich, A. Poschlad, V. Meded, E. Blasco, W. Wenzel, M. M. Kappes and C. Barner-Kowollik, Highly Selective Dispersion of Single-Walled Carbon Nanotubes via Polymer Wrapping: A Combinatorial Study via Modular Conjugation, ACS Macro Letters 3, 10-15, 2014. (abstract)
  • S. Bozic, J. Kruger, C. Sinner, B. Lutz, A. Schug and I. Kondov, Integration of eSBMTools into the MoSGrid Portal Using the gUSE Technology, In: 6th International Workshop on Science Gateways (IWSG), 2014, 2014, 85-90, 2014. (abstract)
  • B. Lutz, C. Sinner, S. Bozic, I. Kondov and A. Schug, Native structure-based modeling and simulation of biomolecular systems per mouse click, BMC Bioinformatics 15, 292, 2014. (abstract)
  • N. Berton, F. Lemasson, A. Poschlad, V. Meded, F. Tristram, W. Wenzel, F. Hennrich, M. M. Kappes, M. Mayor, Selective Dispersion of Large-Diameter Semiconducting Single-Walled Carbon Nanotubes with Pyridine-Containing Copolymers, Small 10, 360-367, 2014. (abstract)
  • M. Brieg and W. Wenzel, Powerborn: A Barnes-Hut tree implementation for accurate and efficient Born radii computation, Journal of Chemical Theory and Computation 9(3), 1489-1498, 2013. (abstract)
  • K. V. Klenin and W. Wenzel, Calculation of the "absolute" free energy of a beta-hairpin in an all-atom force field, The Journal of Chemical Physics 139, 054102, 2013. (abstract)
  • A. Bender, A. Poschlad, S. Bozic, and I. Kondov, A Service-oriented Framework for Integration of Domain-specific Data Models in Scientific Workflows, Procedia Computer Science 18, 1087 - 1096, 2013. (abstract)
  • I. Kondov, Protein structure prediction using distributed parallel particle swarm optimization, Natural Computing 12, 29-41, 2013. (abstract)
  • A. Poschlad, V. Meded, R. Maul, and W. Wenzel, Different interface orientations of pentacene and PTCDA induce different degrees of disorder, Nanoscale Research Letters 7, 248, 2012. (abstract)
  • T. Strunk, M. Wolf, M. Brieg, K. Klenin, A. Biewer, F. Tristram, M. Ernst, P.-J. Kleine, N. Heilmann, I. Kondov, and W. Wenzel, SIMONA 1.0: An Efficient and Versatile Framework for Stochastic Simulations of Molecular and Nanoscale Systems, Journal of Computational Chemistry 33, 2602–2613, 2012. (abstract)
  • O. Schneider, R. H. Fogh, U. Sternberg, K. Klenin, and I. Kondov, Structure Simulation with Calculated NMR Parameters - Integrating COSMOS into the CCPN Framework, In "HealthGrid Applications and Technologies Meet Science Gateways for Life Sciences", S. Gesing et al. (Eds.), Studies in Health Technology and Informatics, Vol. 175, pp. 162-172, IOS Press, 2012. (abstract)
  • S. Bozic and I. Kondov, Dataflow Management: A Grand Challenge in Multiscale Materials Modelling, eChallenges e-2012 Conference Proceedings, 2012. (abstract)
  • S. Bozic, I. Kondov, V. Meded, and W. Wenzel, UNICORE based Workflows for the Simulation of Organic Light-Emitting Diodes, In UNICORE Summit 2012 Proceedings, May 30-31, 2012, Dresden, Germany, IAS Series, Vol. 15, pp. 15-25, Jülich (2012), 2012. (abstract)
  • K. Klenin and W. Wenzel, Transition network based on equilibrium sampling: A new method for extracting kinetic information from Monte Carlo simulations of protein folding, J. Chem. Phys. 135, 235105, 2011. (abstract)
  • K. Klenin, F. Tristram, T. Strunk, and W. Wenzel, Derivatives of molecular surface area and volume: Simple and exact analytical formulas, J. Comp. Chem. 32, 2647-2653, 2011. (abstract)
  • I. Kondov, R. Maul, S. Bozic, V. Meded, and W. Wenzel, UNICORE-Based Integrated Application Services for Multiscale Materials Modeling, In UNICORE Summit 2011 Proceedings, IAS Series, Vol. 9, pp. 1-10, FZJ ZB Verlag, 2011. (abstract)
  • K. Klenin, B. Strodel, D. J. Wales, and W. Wenzel, Modelling proteins: Conformational sampling and reconstruction of folding kinetics, Biochimica et Biophysica Acta - Proteins and Proteomics, 1814, 977-1000, 2011. (abstract)
  • M. Polok, D. V. Fedorov, A. Bagrets, P. Zahn, and I. Mertig, Evaluation of conduction eigenchannels of an adatom probed by an STM tip, Phys. Rev. B 83, 245426, 2011. (abstract)
  • I. Kondov, A. Verma, and W. Wenzel, Performance assessment of different constraining potentials in computational structure prediction for disulfide-bridged proteins, Comput. Biol. Chem. 35, 230, 2011. (abstract)
  • S. Bera and F. Evers and I. Kondov, Highly efficient numerical implementation of the Chalker-Coddington network model and applications, In: Computational Methods in Science and Engineering: Proceedings of the Workshop SimLabs@KIT, pp. 47-57, Karlsruhe, KIT Scientific Publishing, 2011. (abstract)
  • I. Kondov, R. Maul, K. Klenin, M. Brieg, A. Poschlad, A. Bagrets, V. Meded, and S. Bozic, Multiscale materials and biomolecular simulations at Simulation Lab NanoMikro, In: Computational Methods in Science and Engineering: Proceedings of the Workshop SimLabs@KIT, pp. 5-16, Karlsruhe, KIT Scientific Publishing, 2011. (abstract)
  • I. Kondov and R. Berlich, Protein Structure Prediction using Particle Swarm Optimization and a Distributed Parallel Approach, Proc. "Biologically inspired algorithms for distributed systems", ICAC '11 8th International Conference on Autonomic Computing Karlsruhe, Germany, pp. 35-42, ACM, 2011. (abstract)
  • J. Li, I. Kondov, H. Wang, and M. Thoss, Theoretical Study of Photoinduced Electron-Transfer Processes in the Dye-Semiconductor System Alizarin-TiO2, J. Phys. Chem. C 114, 18481, 2010. (abstract)
  • I. Bâldea, H. Köppel, R. Maul and W. Wenzel, Applying the extended molecule approach to correlated electron transport: important insight from model calculations, J. Chem. Phys. 133, 014108, 2010. (abstract)
  • F.-Q. Xie, R. Maul, Ch. Obermair, W. Wenzel, G. Schön, and Th. Schimmel, Multilevel Atomic-Scale Transistors Based on Metallic Quantum Point Contacts, Adv. Mater. 22, 2033, 2010. (abstract)
  • K. V. Klenin and W. Wenzel, A method for the calculation of rate constants from stochastic transition paths, J. Chem. Phys. 132, 104104, 2010. (abstract)
  • I. Kondov, A. Verma and W. Wenzel, Folding path and funnel scenarios for two small disulfide-bridged proteins, Biochemistry 48, 8195, 2009. (abstract)