Anyterial

Publications

This page lists key publications related to the databases and tools made available through Anyterial.

Databases

The ADAQ database

These publications contributed to the database and key methodology.

• ADAQ: Automatic workflows for magneto-optical properties of point defects in semiconductors, J. Davidsson, V. Ivády, R. Armiento, and I. A. Abrikosov, Computer Physics Communications, 108091 (2021).

Also see the ADAQ publications page.

The Altermagnets database

• High-Throughput Quantification of Altermagnetic Band Splitting, Ali Sufyan, Brahim Marfoua, J. Andreas Larsson, E. van Loon, and R. Armiento, Phys. Rev. Mater. 10, 044407 (2026).

Also see the Altermagnets database how-to-cite page.

The Hard-coating Alloys DataBase (HADB)

• HADB: A materials-property database for hard-coating alloys, H. Levämäki, F. Bock, D. G. Sangiovanni, L. J. S. Johnson, F. Tasnádi, R. Armiento, I. A. Abrikosov, Thin Solid Films 766, 139627 (2023).

Also see the HADB front page.

Anyterial Crystals

We are about to launch a crystal structure database based on the following publication:

• Screening 39 billion protostructures for materials discovery, A. S Parackal, F. Trybel, F. A. Faber, R. Armiento, arXiv:2601.21393 [cond-mat.mtrl-sci] (2026).

Tools

httk

Main publication

• Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design, R. Armiento in Schütt K., Chmiela S., von Lilienfeld O., Tkatchenko A., Tsuda K., Müller KR. (eds), Machine Learning Meets Quantum Physics, Lecture Notes in Physics, vol 968. Springer, Cham. (2020).

High-throughput computational publications from which the software originated

• Machine Learning Energies of 2 M Elpasolite (ABC2D6) Crystals, F. A. Faber, A. Lindmaa, O. A. von Lilienfeld, R. Armiento, Physical Review Letters 117, 135502 (2016).
• Crystal structure representations for machine learning models of formation energies, F. Faber, A. Lindmaa, O. A. von Lilienfeld, R. Armiento, International Journal of Quantum Chemistry 115, 1094 (2015).

ADAQ software platform

Automatic Defect Analysis and Qualification (ADAQ) is a software platform for automatic workflows for high-throughput calculations of point defects in semiconductors.

Main publication

• ADAQ: Automatic workflows for magneto-optical properties of point defects in semiconductors, J. Davidsson, V. Ivády, R. Armiento, and I. A. Abrikosov, Computer Physics Communications, 108091 (2021).

Tools

• ADAQ-SYM: Automated Symmetry Analysis of Defect Orbitals, W. Stenlund, J. Davidsson, V. Ivády, R. Armiento, and I. A. Abrikosov, arXiv:2307.04381 [cond-mat.mtrl-sci] (2023).