Interface Morphology Prediction with Robust and Efficient Structure Search (IMPRESS)

June 7, 2017 to June 9, 2017
Location : CECAM-FI, Aalto University, Helsinki, Finland


  • Milica Todorovic (Centre of Excellence in Computational Nanophysics (COMP), Aalto University, Finland)
  • Oliver T. Hofmann (Institute of Solid State Physics, Graz University of Technology, Austria)
  • Patrick Rinke (Aalto University, Helsinki, Finland)





Aalto University Educational Network


The properties of molecular materials in the condensed phase depend strongly on their intra-molecular structure and morphology [1]. This holds especially true for organic overlayers and organic films grown on inorganic surfaces, which is a complex processes determined by multiple physical and chemical phenomena, such as multipole-multipole interactions, van-der-Waals interactions, covalent-bond formation and charge-transfer. Despite the long history of surface science, the field of structure determination at inorganic/organic interfaces is still in its infancy. Today, most computational studies can be grouped in two different categories: electronic structure calculations that focus on the chemistry and quantum mechanical detail of adsorbates, and methods that harness the vast phase space of configurations and can tackle molecular ensembles and morphology.

Considering phase-space exploration first, molecular dynamics (MD) based methods like simulated annealing [2] or minima hopping [3], as well as kinetic Monte Carlo (kMC) methods are very well established. Due to the large size of surface unit cells and long timescales required for an adequate sampling, classical force-field techniques are frequently employed for MD, which caps the accuracy of the search. kMC calculations need to be performed for each set of deposition conditions. Accessing higher energy structures and other system properties is prohibitively laborious. For inorganic systems, many alternative methods ranging from cluster expansions over graph search methods to metadynamics and genetic algorithms have been developed to facilitate efficient phase space exploration, and yet they all depend on accurate total energies for input structures.

Electronic-structure calculations provide such accurate total energies together with a quantum mechanical description of inorganic/organic interfaces. Density-functional theory (DFT) with dispersion-corrected density functionals has emerged as the tool of choice for interface studies. The recent crystal structure prediction round-robin tests for organic bulk materials have not only shown that DFT is accurate enough to provide the correct ordering of different polymorphs, but also that structure prediction is now possible on sensible timescales [4]. Despite technical advances on high-performance computers, the computational cost of DFT methods is still too prohibitive for phase space exploration. Instead, candidate interface geometries for DFT calculations are frequently either inspired by experiment or by chemical intuition, and hence intrinsically biased.

What is required to move forward is a fusion of efficient phase space exploration and chemical accuracy of the model. Each approach to date has its advantages and disadvantages and the challenge lies in combining techniques in a synergistic way.

Read more, register and submit your contribution at the IMPRESS website:



[1] Jansen, M., Angewandte Chemie Int. Ed., 41, 3747 (2002)
[2] S. Kirkpatrick et al., Science, 220, 671 (1983)
[3] S. Goedecker et al., Phys. Rev. Lett., 95, 055501 (2005)
[4] D. Bardwell et al., Acta Crystallographica Section B Structural Science, 67, 535 (2011)