# Database of novel magnetic materials for high-performance permanent magnet development

## TL;DR

The paper introduces the Novamag database, a comprehensive resource for designing high-performance, Rare-Earth free permanent magnets, combining computational predictions and experimental data to accelerate magnetic material development.

## Contribution

It presents a novel open database integrating computational high-throughput screening and experimental data for magnetic materials, aiding the design of Rare-Earth free permanent magnets.

## Key findings

- Identification of novel magnetic phases with high anisotropy
- Compilation of theoretical and experimental magnetic properties
- Insights into performance limits of Rare-Earth free magnets

## Abstract

This paper describes the open Novamag database that has been developed for the design of novel Rare-Earth free/lean permanent magnets. The database software technologies, its friendly graphical user interface, advanced search tools and available data are explained in detail. Following the philosophy and standards of Materials Genome Initiative, it contains significant results of novel magnetic phases with high magnetocrystalline anisotropy obtained by three computational high-throughput screening approaches based on a crystal structure prediction method using an Adaptive Genetic Algorithm, tetragonally distortion of cubic phases and tuning known phases by doping. Additionally, it also includes theoretical and experimental data about fundamental magnetic material properties such as magnetic moments, magnetocrystalline anisotropy energy, exchange parameters, Curie temperature, domain wall width, exchange stiffness, coercivity and maximum energy product, that can be used in the study and design of new promising high-performance Rare-Earth free/lean permanent magnets. The results therein contained might provide some insights into the ongoing debate about the theoretical performance limits beyond Rare-Earth based magnets. Finally, some general strategies are discussed to design possible experimental routes for exploring most promising theoretical novel materials found in the database.