Publications

Publications of the Institute

A complete list of publications you can find here

ICP Publications

  1. 2023

    1. Weeber, R., Grad, J.-N., Beyer, D., Blanco, P. M., Kreissl, P., Reinauer, A., Tischler, I., Košovan, P., & Holm, C. (2023). ESPResSo, a Versatile Open-Source Software Package for Simulating Soft Matter Systems. In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier. https://doi.org/10.1016/B978-0-12-821978-2.00103-3
    2. Kreissl, P., Holm, C., & Weeber, R. (2023). Interplay between steric and hydrodynamic interactions for ellipsoidal magnetic nanoparticles in a polymer suspension. Soft Matter, 19(6), Article 6. https://doi.org/10.1039/D2SM01428A
    3. Gravelle, S., Beyer, D., Brito, M., Schlaich, A., & Holm, C. (2023). Assessing the Validity of NMR Relaxation Rates Obtained from Coarse-Grained Simulations of PEG–Water Mixtures. The Journal of Physical Chemistry B, 127(25), Article 25. https://doi.org/10.1021/acs.jpcb.3c01646
    4. Beyer, D., & Holm, C. (2023). A generalized grand-reaction method for modeling the exchange of weak (polyprotic) acids between a solution and a weak polyelectrolyte phase. The Journal of Chemical Physics, 159(1), Article 1. https://doi.org/10.1063/5.0155973
    5. Košovan, P., Landsgesell, J., Nová, L., Uhlík, F., Beyer, D., Blanco, P. M., Staňo, R., & Holm, C. (2023). Reply to the ‘Comment on “Simulations of ionization equilibria in weak polyelectrolyte solutions and gels”’ by J. Landsgesell, L. Nová, O. Rud, F. Uhlík, D. Sean, P. Hebbeker, C. Holm and P. Košovan, Soft Matter, 2019, 15, 1155–1185. Soft Matter, 19(19), Article 19. https://doi.org/10.1039/D3SM00155E
    6. Sufi, S., Martinez-Ortiz, C., Doorn, P., Farrell, J., Barker, M., Katz, D. S., Jackson, A., Struck, A., Sandeman, A., Stewart, A., Terrel, A. R., Companjen, B., Haupt, C., Strasser, C., Goble, C., Chavez, C. V. F. G., Venters, C., Dietrich, D., Colón-Marrero, E., … Rampin, V. (2023). Report on the Workshop on Sustainable Software                    Sustainability 2021 (WoSSS21). Zenodo. https://doi.org/10.5281/zenodo.7951155

  2. 2022

    1. Wang, W., Gardi, G., Malgaretti, P., Kishore, V., Koens, L., Son, D., Gilbert, H., Wu, Z., Harwani, P., Lauga, E., Holm, C., & Sitti, M. (2022). Order and information in the patterns of spinning magnetic micro-disks at the air-water interface. Science Advances, 8(2), Article 2. https://doi.org/10.1126/sciadv.abk0685
    2. Rafieiolhosseini, N., Killa, M., Neumann, T., Tötsch, N., Grad, J.-N., Höing, A., Dirksmeyer, T., Niemeyer, J., Ottmann, C., Knauer, S. K., Giese, M., Voskuhl, J., & Hoffmann, D. (2022). Computational model predicts protein binding sites of a luminescent ligand equipped with guanidiniocarbonyl-pyrrole groups. Beilstein Journal of Organic Chemistry, 18, 1322--1331. https://doi.org/10.3762/bjoc.18.137
    3. Tischler, I., Weik, F., Kaufmann, R., Kuron, M., Weeber, R., & Holm, C. (2022). A thermalized electrokinetics model including stochastic reactions suitable for multiscale simulations of reaction–advection–diffusion systems. Journal of Computational Science, 63, 101770. https://doi.org/10.1016/j.jocs.2022.101770
    4. Lamprecht, A.-L., Martinez-Ortiz, C., Barker, M., Bartholomew, S. L., Barton, J., Hong, N. C., Cohen, J., Druskat, S., Forest, J., Grad, J.-N., Katz, D. S., Richardson, R., Rosca, R., Schulte, D., Struck, A., & Weinzierl, M. (2022). What Do We (Not) Know About Research Software Engineering? Journal of Open Research Software, 10. https://doi.org/10.5334/jors.384
    5. Beyer, D., Kosovan, P., & Holm, C. (2022). Simulations Explain the Swelling Behavior of Hydrogels with Alternating Neutral and Weakly Acidic Blocks. Macromolecules, 55(23), Article 23. https://doi.org/10.1021/acs.macromol.2c01916
    6. Beyer, D., Landsgesell, J., Hebbeker, P., Rud, O., Lunkad, R., Kosovan, P., & Holm, C. (2022). Correction to “Grand-Reaction Method for Simulations of Ionization Equilibria Coupled to Ion Partitioning.” Macromolecules, 55(3), Article 3. https://doi.org/10.1021/acs.macromol.1c02672
    7. Landsgesell, J., Beyer, D., Hebbeker, P., Kosovan, P., & Holm, C. (2022). The pH-Dependent Swelling of Weak Polyelectrolyte Hydrogels Modeled at Different Levels of Resolution. Macromolecules, 55(8), Article 8. https://doi.org/10.1021/acs.macromol.1c02489

  3. 2021

    1. Carral, Á. D., Ostertag, M., & Fyta, M. (2021). Deep learning for nanopore ionic current blockades. The Journal of Chemical Physics, 154(4), Article 4. https://doi.org/10.1063/5.0037938
    2. Itto, Y. (2021). Fluctuating Diffusivity of RNA-Protein Particles: Analogy with Thermodynamics. Entropy, 23(3), Article 3. https://doi.org/10.3390/e23030333
    3. Itto, Y., & Beck, C. (2021). Superstatistical modelling of protein diffusion dynamics in bacteria. Journal of The Royal Society Interface, 18(176), Article 176. https://doi.org/10.1098/rsif.2020.0927
    4. Finkbeiner, J., Tovey, S., & Holm, C. (2021). Efficient Data Selection Methods for the Development of Machine Learned Potentials. ArXiv, abs/2108.01582.
    5. Finkbeiner, J., Tovey, S., & Holm, C. (2021). Efficient Data Selection Methods for the Development of Machine Learned Potentials.
    6. Riede, J. M., Holm, C., Schmitt, S., & Haeufle, D. F. B. (2021). The control effort to steer self-propelled microswimmers depends on their morphology: comparing symmetric spherical versus asymmetric              L              -shaped particles. Royal Society Open Science, 8(9), Article 9. https://doi.org/10.1098/rsos.201839
    7. Tagliabue, A., Landsgesell, J., Mella, M., & Holm, C. (2021). Can oppositely charged polyelectrolyte stars form a gel? A simulational study. Soft Matter. https://doi.org/10.1039/D0SM01617A
    8. Wagner, A., Eggenweiler, E., Weinhardt, F., Trivedi, Z., Krach, D., Lohrmann, C., Jain, K., Karadimitriou, N., Bringedal, C., Voland, P., Holm, C., Class, H., Steeb, H., & Rybak, I. (2021). Permeability Estimation of Regular Porous Structures: A Benchmark for Comparison of Methods. Transport in Porous Media. https://doi.org/10.1007/s11242-021-01586-2
    9. Szuttor, K., Weik, F., Grad, J.-N., & Holm, C. (2021). Modeling the current modulation of bundled DNA structures in nanopores. The Journal of Chemical Physics, 154(5), Article 5. https://doi.org/10.1063/5.0038530
    10. Lee, M., Lohrmann, C., Szuttor, K., Auradou, H., & Holm, C. (2021). The influence of motility on bacterial accumulation in a microporous channel. Soft Matter, 17(4), Article 4. https://doi.org/10.1039/D0SM01595D
    11. Itto, Y., & Beck, C. (2021). Weak correlation between fluctuations in protein diffusion inside bacteria. Journal of Physics: Conference Series, 2090(1), Article 1. https://doi.org/10.1088/1742-6596/2090/1/012168
    12. Zeman, J., Kondrat, S., & Holm, C. (2021). Ionic screening in bulk and under confinement. The Journal of Chemical Physics, 155(20), Article 20. https://doi.org/10.1063/5.0069340
    13. Kreissl, P., Holm, C., & Weeber, R. (2021). Frequency-dependent magnetic susceptibility of magnetic nanoparticles in a polymer solution: a simulation study. Soft Matter, 17(1), Article 1. https://doi.org/10.1039/D0SM01554G
    14. Lee, M., Lohrmann, C., Szuttor, K., Auradou, H., & Holm, C. (2021). The influence of motility on bacterial accumulation in a microporous channel. Soft Matter. https://doi.org/10.1039/D0SM01595D
    15. Bauer, M., Eibl, S., Godenschwager, C., Kohl, N., Kuron, M., Rettinger, C., Schornbaum, F., Schwarzmeier, C., Thönnes, D., Köstler, H., & Rüde, U. (2021). waLBerla: A block-structured high-performance framework for multiphysics simulations. Computers & Mathematics with Applications, 81, 478--501. https://doi.org/10.1016/j.camwa.2020.01.007
    16. Atanasova, P., Dou, M., Kousik, S. R., Bill, J., & Fyta, M. (2021). Adsorption of azide-functionalized thiol linkers on zinc oxide surfaces. RSC Adv., 11(10), Article 10. https://doi.org/10.1039/D0RA05127F
    17. Feuerstein, L., Biermann, C. G., Xiao, Z., Holm, C., & Simmchen, J. (2021). Highly Efficient Active Colloids Driven by Galvanic Exchange Reactions. Journal of the American Chemical Society, 143(41), Article 41. https://doi.org/10.1021/jacs.1c06400
    18. Kuron, M., Stewart, C., de Graaf, J., & Holm, C. (2021). An extensible lattice Boltzmann method for viscoelastic flows: complex and moving boundaries in Oldroyd-B fluids. https://doi.org/10.1140/epje/s10189-020-00005-6
    19. Tagliabue, A., Landsgesell, J., Mella, M., & Holm, C. (2021). Can oppositely charged polyelectrolyte stars form a gel? A simulational study. Soft Matter, 17(6), Article 6. https://doi.org/10.1039/D0SM01617A
    20. Bauer, M., Eibl, S., Godenschwager, C., Kohl, N., Kuron, M., Rettinger, C., Schornbaum, F., Schwarzmeier, C., Thönnes, D., Köstler, H., & Rüde, U. (2021). waLBerla: A block-structured high-performance framework for multiphysics simulations. Computers &amp$\mathsemicolon$ Mathematics with Applications, 81, 478--501. https://doi.org/10.1016/j.camwa.2020.01.007
    21. Szuttor, K., Kreissl, P., & Holm, C. (2021). A numerical investigation of analyte size effects in nanopore sensing systems. The Journal of Chemical Physics, 155(13), Article 13. https://doi.org/10.1063/5.0065085
    22. Kuron, M., Stewart, C., de Graaf, J., & Holm, C. (2021). An extensible lattice Boltzmann method for viscoelastic flows: complex and moving boundaries in Oldroyd-B fluids. The European Physical Journal E, 44(1), Article 1. https://doi.org/10.1140/epje/s10189-020-00005-6
    23. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2021). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.2
    24. Bindgen, S., Weik, F., Weeber, R., Koos, E., & de Buyl, P. (2021). Lees–Edwards boundary conditions for translation invariant shear flow: Implementation and transport properties. Physics of Fluids, 33(8), Article 8. https://doi.org/10.1063/5.0055396
    25. Riede, J. M., Holm, C., Schmitt, S., & Haeufle, D. F. B. (2021). The control effort to steer self-propelled microswimmers depends on their morphology: comparing symmetric spherical versus asymmetric              $łess$i$\greater$L$łess$/i$\greater$              -shaped particles. Royal Society Open Science, 8(9), Article 9. https://doi.org/10.1098/rsos.201839
    26. Wagner, A., Eggenweiler, E., Weinhardt, F., Trivedi, Z., Krach, D., Lohrmann, C., Jain, K., Karadimitriou, N., Bringedal, C., Voland, P., Holm, C., Class, H., Steeb, H., & Rybak, I. (2021). Permeability Estimation of Regular Porous Structures: A Benchmark for Comparison of Methods. Transport in Porous Media, 138(1), Article 1. https://doi.org/10.1007/s11242-021-01586-2
    27. Stano, R., Kosovan, P., Tagliabue, A., & Holm, C. (2021). Electrostatically Cross-Linked Reversible Gels—Effects of pH and Ionic Strength. Macromolecules, 54(10), Article 10. https://doi.org/10.1021/acs.macromol.1c00470
    28. Rud, O. V., Landsgesell, J., Holm, C., & Kosovan, P. (2021). Modeling of weak polyelectrolyte hydrogels under compression – Implications for water desalination. Desalination, 506, 114995. https://doi.org/10.1016/j.desal.2021.114995

  4. 2020

    1. Sarap, C. S., Putra, M. H., & Fyta, M. (2020). Domain-size effect on the electronic properties of two-dimensional $MoS_2/WS_2$. Phys. Rev. B, 101(7), Article 7. https://doi.org/10.1103/PhysRevB.101.075129
    2. Hilfer, R., & Kleiner, T. (2020). Maximal Domains for Fractional Derivatives and Integrals. Mathematics, 8(7), Article 7. https://doi.org/10.3390/math8071107
    3. Breitsprecher, K., Janssen, M., Srimuk, P., Mehdi, B. L., Presser, V., Holm, C., & Kondrat, S. (2020). How to speed up ion transport in nanopores. Nature Communications, 11(1), Article 1. https://doi.org/10.1038/s41467-020-19903-6
    4. Landsgesell, J., Hebbeker, P., Rud, O., Lunkad, R., Kosovan, P., & Holm, C. (2020). Grand-Reaction Method for Simulations of Ionization Equilibria Coupled to Ion Partitioning. Macromolecules, 53(8), Article 8. https://doi.org/10.1021/acs.macromol.0c00260
    5. Zeman, J., Kondrat, S., & Holm, C. (2020). Bulk ionic screening lengths from extremely large-scale molecular dynamics simulations. Chem. Commun., 56(100), Article 100. https://doi.org/10.1039/D0CC05023G
    6. Kobayashi, T., Kraus, H., Hansen, N., & Fyta, M. (2020). Confined Ru-catalysts in a Two-phase Heptane/Ionic Liquid Solution: Modeling Aspects. ChemCatChem, 13(2), Article 2. https://doi.org/10.1002/cctc.202001596
    7. Dou, M., & Fyta, M. (2020). Lithium adsorption on 2D transition metal dichalcogenides: towards a descriptor for machine learned materials design. J. Mater. Chem. A, 8(44), Article 44. https://doi.org/10.1039/D0TA04834H
    8. Sánchez, P. A., Vögele, M., Smiatek, J., Qiao, B., Sega, M., & Holm, C. (2020). PDADMAC/PSS Oligoelectrolyte Multilayers: Internal Structure and Hydration Properties at Early Growth Stages from Atomistic Simulations. Molecules, 25(8), Article 8. https://doi.org/10.3390/molecules25081848
    9. Sivaraman, G., Krishnamoorthy, A. N., Baur, M., Holm, C., Stan, M., Csányi, G., Benmore, C., & Vázquez-Mayagoitia, Á. (2020). Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide. Npj Computational Materials, 6(1), Article 1. https://doi.org/10.1038/s41524-020-00367-7
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