1.2 Features of USPEX

• Prediction of the stable and metastable structures knowing only the chemical composition. Simultaneous searches for stable compositions and structures are also possible.

• Incorporation of partial structural information is possible:

  • constraining search to fixed experimental cell parameters, or fixed cell shape, or fixed cell volume (Subsection 4.6);

  • starting structure search from known or hypothetical structures (Subsection 8.5);

  • assembling crystal structures from predefined molecules, including flexible molecules (Subsection 5.3).

• Efficient constraint techniques, which eliminate unphysical and redundant regions of the search space. Cell reduction technique (Oganov & Glass, 2008).

• Niching using fingerprint functions (Oganov & Valle, 2009; Lyakhov, Oganov, Valle, 2010). Subsection 4.9 for details.

• Initialization using fully random approach, or using space groups and cell splitting techniques (Lyakhov, Oganov, Valle, 2010). Use of powerful topological structure generator (Bushlanov, Blatov, Oganov, 2018).

• On-the-flight analysis of results — determination of space groups (and output in CIF-format) (Subsection 4.11), calculation of the hardness, order parameters, etc.

• Prediction of the structure of nanoparticles and surface reconstructions. See Section 5.4 for details.

• Restart functionality, enabling calculations to be continued from any point along the evolutionary trajectory (Subsection 4.7).

• Powerful visualization and analysis techniques implemented in the STM4 code (by M. Valle), fully interfaced with USPEX (Subsection 8.1).

• USPEX is interfaced with VASP, SIESTA, GULP, LAMMPS, DMACRYS, CP2K, Abinit, CRYSTAL, Quantum Espresso, FHI-aims, ATK, CASTEP, Tinker, MOPAC codes. See full list of supported codes in Subsection 2.5.

• Submission of jobs from local workstation to remote clusters and supercomputers is possible. See Section 8.8 for details.

• Options for structure prediction using the USPEX algorithm (default), random sampling, corrected particle swarm optimization (Subsection 5.8), evolutionary metadynamics (Subsection 5.7), minima hopping-like algorithm. Capabilities to predict phase transition mechanisms using evolutionary metadynamics, variable-cell NEB method (Subsection 6.2), and TPS method (Subsection 6.3). USPEX also has a quick geometric mapping algorithm to predict likely mechanism of a phase transition. (Subsection 6.1)

• Options to optimize physical properties other than energy — e.g., hardness (Mazhnik & Oganov, 2019), density (Zhu et al., 2011), band gap and dielectric constant (Zeng et al., 2014), and many other properties.

• Starting from version 9.4.1, USPEX has a Python-based runner of the code (USPEX Python module), providing a number of useful command line options.