collaborators
Showing cond-mat.mtrl-sciShow all

4 papers · 1 filter

cond-mat.mtrl-sci2025

Order-disorder duality of high entropy alloys extends non-linear optics

Valentin A. Milichko, Ekaterina Gunina, Nikita Kulachenkov +21

Order versus disorder in the structure of materials plays a key role in the theoretical prediction of their properties. However, this structural description appears to be ineffecti…

cond-mat.mtrl-sci2024

Predicting the Curie temperature in substitutionally disordered alloys using a first-principles based model

Marian Arale Brännvall, Rickard Armiento, Björn Alling

When exploring new magnetic materials, the effect of alloying plays a crucial role for numerous properties. By altering the alloy composition, it is possible to tailor, e.g., the C…

cond-mat.mtrl-sci2024

Evaluating and improving the predictive accuracy of mixing enthalpies and volumes in disordered alloys from universal pre-trained machine learning potentials

Luis Casillas-Trujillo, Abhijith S. Parackal, Rickard Armiento +1

The advent of machine learning in materials science opens the way for exciting and ambitious simulations of large systems and long time scales with the accuracy of ab-initio calcul…

cond-mat.mtrl-sci2024

Predicting the Curie temperature of magnetic materials with automated calculations across chemistries and structures

Marian Arale Brännvall, Gabriel Persson, Luis Casillas-Trujillo +2

We develop a technique for predicting the Curie temperature of magnetic materials using density functional theory calculations suitable to include in high-throughput frameworks. We…