📝 SummarXiv

Abstract

Magnetic materials often exhibit complex energy landscapes with multiple local minima, each corresponding to a self-consistent electronic structure solution. Finding the global minimum is challenging, and heuristic methods are not always guaranteed to succeed. Here, we apply a recently developed automated workflow to systematically explore the energy landscape of 194 magnetic monolayers obtained from the Materials Cloud 2D crystals database and determine their ground-state magnetic order. Our approach enables effective control and sampling of orbital occupation matrices, allowing rapid identification of local minima. We find a diverse set of self-consistent collinear metastable states, further enriched by Hubbard-corrected energy functionals, when the $U$ parameters have been computed from first principles using linear-response theory. We categorise the monolayers by their magnetic ordering and highlight promising candidates. Our results include 109 ferromagnetic, 83 antiferromagnetic, and 2 altermagnetic monolayers, along with 12 novel ferromagnetic half-metals with potential for spintronics technologies.