Institute of Solid State Physics

Lukas Hörmann

Contact: ☎ ✉

   Switchable superlubricity
   Understanding Molecular Monolayer Formation with Machine Learning
   Machine Learning Provides New Insights Into Organic-Inorganic Interfaces
   Huge Computing Time Project Granted

   Computational Material Design with DFT and Machine Learning

Researching Organic/Inorganic Interfaces Machine Learning
My research interests include
  • Surfaces Structure Search
  • Polymorphism and Metastable Structures
  • Phase Diagrams and Phase Transitions
  • Adsorption Processes of Organic Molecules
  • Defects in Organic Monolayers
I use the following techniques for my research:
  • Machine Learning (mostly Gaussian Process Regression)
  • Density Functional Theory
  • Ab-initio Thermodynamics
Personal data

Recent talks

ML4MS, May 2019, Helsinki

Meeting of the German Physical Society, April 2019, Regensburg

--> last updated: 2. July 2020