# Structure-based approach¶

Our current work is focused on **structure-based** atomistic approach, where the information about the atomistic arrangement is known *a priori* (see data conventions).

Non-structure-based scenario

Our data convention has support for materials data where no structural information is available, however this topic is beyond the content of the current documentation.

## Example Representation¶

For examples of JSON representation of materials and structure-based descriptors see materials data section.

## Features, Fingerprints, Targets¶

On many occasions terms "Features", "Fingerprints", "Targets" are used for materials informatics purposes. For example, when constructing a machine learning model a dataset containing information about multiple materials is used in order to find regular patterns and inter-dependencies. Such dataset is usually split into properties that represent the known data, or *features*, and the properties to be predicted, or *targets*.
First we clarify this terminology as follows:

**Feature**: any property of a material, eg. density or electronic band gap.-
**Fingerprint**: property of a material used as an input for a (statistical modeling) Workflow, equivalent of**Descriptive**property by definitionBy default, we only store the minimal amount of information required to identify a material enough to reveal a set of its

**Fingerprints**. Such minimal set of properties is called**Identity Fingerprints**, and the rest -**Derived Fingerprints**. -
**Target**: property of a material used as an input for a (statistical modeling) Workflow, equivalent of a**Characteristic**property by definition.

Thus a *property-descriptive-characteristic* triad is equivalent to *feature-fingerprint-target*.

# Example properties¶

Exact set of Materials properties that have to be supplied to and can be extracted as a result of a Workflow vary based on the type of Workflow and models/methods included therein.

## Results¶

Below we provide example properties extracted by the using Density Functional Theory (DFT) as simulation results:

Property | Overview |
---|---|

Total Energy | The ground state energy (free energy) of the system |

Fermi Energy | The highest energy level occupied by electrons in a system |

Fermi Surface | Surface of constant energy (Fermi) in reciprocal space |

Atomic forces | Force exerted on each atom by its surrounding |

Stress tensor | 3x3 matrix expressing stresses in x, y and z dimensions |

Pressure | Scalar average pressure |

Charge density | Spatial function of charge distribution |

Band Structure | Electronic Band Structure |

Band Gap | Electronic Band Gap (direct / indirect) |

Density of States | Electronic Density of States (including partial contributions) |

Zero Point Energy | Energy of the lowest vibrational level wrt to vacuum |

Final Structure | Visualization of the final computed crystal structure |

Total Energy Contributions | Ewald, Exchange correlation and Hartree contributions to the total energy |

Magnetic Moments | The magnetic moment of ferromagnetic materials when the "Magnetism" modifier is activated |

Total Force | Sum of the atomic forces |

## Monitors¶

These are the data points that can be monitored during the course of a DFT calculation:

Output information | Overview |
---|---|

Standard Output | Standard output of an execution unit in UNIX sense |

Ionic Convergence | Convergence information on ionic moves in relaxation or molecular dynamics calculations |

Electronic Convergence | Convergence information on self-consistent electronic calculation steps |