Molekulardynamik-Simulationen komplexer Systeme mit hochdimensionalen neuronalen Netzen

• Antragsteller: Professor Dr. Jörg Behler
• Fachliche Zuordnung: Theoretische Chemie: Elektronenstruktur, Dynamik, Simulation
• Förderung: Förderung von 2016 bis 2020
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 329898176

• Erstellungsjahr: 2019

Zusammenfassung der Projektergebnisse

Keine Zusammenfassung vorhanden

Projektbezogene Publikationen (Auswahl)

• First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems. Angewandte Chemie, International Edition, Vol. 56. 2017, Issue 42, pp. 12828-12840.
  J. Behler
  (Siehe online unter https://doi.org/10.1002/anie.201703114)
• Proton Transfer Mechanisms at the Water-ZnO Interface: The Role of Presolvation. Journal of Physical Chemistry Letters, Vol. 8. 2017, Issue 7, pp. 1476–1483.
  V. Quaranta, M. Hellström, J. Behler
  (Siehe online unter https://doi.org/10.1021/acs.jpclett.7b00358)
• Proton-Transfer-Driven Water Exchange Mechanism in the Na+ Solvation Shell. Journal of Physical Chemistry B, Vol. 121. 2017, Issue 16, pp. 4184–4190.
  M. Hellström, J. Behler
  (Siehe online unter https://doi.org/10.1021/acs.jpcb.7b01490)
• Maximally Resolved Anharmonic OH Vibrational Spectrum of the Water/ZnO(10-10) Interface from a High-Dimensional Neural Network Potential. Journal of Chemical Physics, Vol. 148. 2018, Issue 24, 241720.
  V. Quaranta, M. Hellström, J. Behler, J. Kullgren, P. Mitev, K. Hermansson
  (Siehe online unter https://doi.org/10.1063/1.5012980)
• Nuclear Quantum Effects in Sodium Hydroxide Solutions from Neural Network Molecular Dynamics Simulations. Journal of Physical Chemistry B, Vol. 122. 2018, Issue 44, pp. 10158–10171.
  M. Hellström, M. Ceriotti, J. Behler
  (Siehe online unter https://doi.org/10.1021/acs.jpcb.8b06433)
• Ab initio Thermodynamics of Liquid and Solid Water. PNAS, Vol. 116. 2019 no. 4, pp. 1110-1115.
  B. Cheng, E. A. Engel, J. Behler, C. Dellago, M. Ceriotti
  (Siehe online unter https://doi.org/10.1073/pnas.1815117116)
• From Molecular Fragments to the Bulk: Development of a Neural Network Potential for MOF-5. Journal of Chemical Theory and Computation, Vol. 15. 2019, Issue 6, pp. 3793-3809.
  M. Eckhoff, J. Behler
  (Siehe online unter https://doi.org/10.1021/acs.jctc.8b01288)
• One-Dimensional vs. Two-Dimensional Proton Transport Processes at Solid-Liquid Zinc-Oxide-Water Interfaces. Chemical Science, Vol. 10. 2019, pp. 1232-1243.
  M. Hellström, V. Quaranta, J. Behler
  (Siehe online unter https://doi.org/10.1039/c8sc03033b)
• Parallel Multi-Stream Training of High-Dimensional Neural Network Potentials. Journal of Chemical Theory and Computation, Vol. 15. 2019, Issue 5, pp. 3075–3092.
  A. Singraber, T. Morawietz, J. Behler, C. Dellago
  (Siehe online unter https://doi.org/10.1021/acs.jctc.8b01092)
• Structure and Dynamics of the Liquid-Water/Zinc-Oxide Interface from Machine Learning Potential Simulations. Journal of Physical Chemistry C, Vol. 123.2019, Issue 2, pp. 1293–1304.
  V. Quaranta, J. Behler, M. Hellström
  (Siehe online unter https://doi.org/10.1021/acs.jpcc.8b10781)