ES22-Wen

Author: Wen, Wen, Department of Chemistry, Carnegie Mellon University, Pittsburgh

Title: Genarris 4.0: Random Structure Generator for Organic/inorganic Interfaces

Abstract: Here we present Genarris 4.0, a random structure generator for organic/inorganic interfaces for seeding downstream interface structure prediction algorithms or machine learning models. Genarris 4.0 is written in python and interface with FHI-aims for interface energy evaluation and geometry relaxation. A volume estimation based on the number of molecules in film (Z) provides a maximum area estimation of interfaces. Epitaxy matrix is leveraged to generate film lattices commensurate with substrate lattice within max area limit. By identifying all compatible layer groups, diverse film lattices are sampled and then cleaved to slab structures by Ogre. A geometric surface matching algorithm is utilized to find the optimal displacement for each generated interface. A workflow with clustering and down selection is implemented to form a final pool of diverse and low-energy structures. We present the application of Genarris 4.0 to three representative organic/inorganic systmes: TCNE/Au(111), PTCDA/Ag(111), and naphthalene/Cu(111). For all three cases, the generated interface structures show great agreement with experimental findings.

Other authors:
Saeed Moayedpour, Department of Chemistry, Carnegie Mellon University, Pittsburgh.
Rithwik Tom, Department of Physics, Carnegie Mellon University, Pittsburgh.
manuel Bier, Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh.
Derek Dardzinski, Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh.
Noa Marom, Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh.