AFLOW School for Materials Discovery

Monday 06.09.2021 - Friday 10.09.2021

online, organized by TU Dresden and Helmholtz-Zentrum Dresden-Rossendorf
(Germany) in cooperation with the Center for Autonomous Materials Design at Duke University (USA)



Autonomous computational frameworks such as AFLOW are generating large databases that power materials discovery. The repository is the largest of its kind, containing more than 3.5 million entries each characterized by 150+ different properties.

Join us in September 2021 for our AFLOW School for Materials Discovery. Through hands-on exercises, the School will provide an in-depth overview of AFLOW’s features, giving participants the tools to employ the framework in their own research.


Topics covered include:

  • High-throughput data generation
  • Interaction with the AFLOW database
  • Structure prototypes and crystal symmetry
  • Thermal, vibrational, and elastic properties analysis
  • Thermodynamic stability analysis
  • Machine learning models for property prediction
  • Modeling of disordered materials

Lecturers and Teachers

David Hicks

Corey Oses

Marco Esters

Rico Friedrich

Andriy Smolyanyuk

Cormac Toher

Stefano Curtarolo


Rico Friedrich

Marco Esters

Alexander Croy

Florian Pump

Gianaurelio Cuniberti


Hardware Check and Test Session

 06.09. (Mon)07.09. (Mon)08.09. (Mon)09.09. (Mon)10.09. (Fri)
14:30Primer: Command Line ToolsSession 2: AFLOW + DFTSession 4: Structure Prototyping (AFLOW-PROTO)Session 7: Thermodynamics of polar materials (AFLOW-CCE)Session 10: Phonons I: Harmonic Approximation (AFLOW-APL)
15:30Keynote address: Stefano CurtaroloSession 8: Disorder (AFLOW-POCC)
16:30Introduction and SetupSession 11: Phonons II: Quasi-Harmonic Approximation (AFLOW-QHA)
17:00Session 3: Symmetry (AFLOW-SYM) part 1Session 5: AFLOW XtalFinder
19:00Session 1: The AFLOW Materials Database (, AFLUX)
19:30Session 3: Symmetry (AFLOW-SYM) Part 2Session 6: Thermodynamic stability (AFLOW-CHULL)Session 9: Thermomechanical Properties (AFLOW-AEL/AGL)Session 12: Machine Learning (AFLOW-ML)