Stripe Antiferromagnetic Ground-State Configuration of FeSe Revealed by Density Functional Theory

TL;DR

This study uses an advanced density functional theory functional to predict that FeSe's magnetic ground state is a stripe antiferromagnetic configuration with interlayer spin coupling, challenging previous predictions and emphasizing the importance of accurate functionals.

Contribution

The paper demonstrates that the r2SCAN functional accurately predicts the stripe-AFM ground state of FeSe, revealing interlayer spin coupling not captured by traditional GGA functionals.

Findings

r2SCAN predicts stripe-AFM ground state for FeSe.

Interlayer spin coupling of approximately 1.7 meV/atom.

Highlights importance of accurate exchange-correlation functionals.

Abstract

The magnetic ground-state configuration of iron selenide FeSe has been a topic of debate, with experimental evidence suggesting the stripe spin fluctuations as predominant at low temperatures, while density functional theory (DFT) calculations using exchange-correlation (XC) functional of the Generalized Gradient Approximation (GGA) have historically predicted the antiferromagnetic (AFM) dimer configuration. In this study, we utilize the $\text{r}^{2}\text{SCAN}$ functional, a variant of the Strongly Constrained and Appropriately Normed (SCAN) meta-GGA, to investigate the magnetic configurations of FeSe. It is found that $\text{r}^{2}\text{SCAN}$ predicts a stripe-AFM ground-state configuration with an anti-parallel spin alignment between layers. The energy difference between the parallel and anti-parallel inter-planar spin alignments is approximately 1.7 meV/atom, predicting a significant but previously unreported interlayer spin coupling not yet observed by experiments. The present study underscores the importance of accurate XC functionals, such as $\text{r}^{2}\text{SCAN}$, in predicting the magnetic ground-state configuration of complex materials like FeSe, highlighting its potential to predict magnetic interactions more reliably than traditional GGA functionals by adhering to exact constraints.