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Department of Materials Science

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Preprint Sep 2026

High-Temperature ferromagnetism from site-selective filling in (Fe,Ni)$_{6-\delta}$GeTe$_2$

The discovery of high-temperature ferromagnetism in the metallic van der Waals (vdW) system Fe$_N$GeTe$_2$ has brought two-dimensional (2D) magnets into technologically relevant temperature scales. Specifically at N = 5, dilution of magnetic moments by nickel substitution counterintuitively achieves a record high Curie temperature of 478~K. Unraveling the origin of this nickel-substitution-induced enhancement is complicated by the compound's structural complexity, coexistent itinerant and local magnetic contributions, and mesoscopic compositional domains. Through coordinated structural and electronic characterization, we identify that the high-T$_C$ magnetic phase arises from a strain-stabilized Fe$_6$GeTe$_2$ nano-precipitate. Combining first-principles calculations and spin- and angle-resolved photoemission spectroscopy (ARPES), we uncover a site-specific electronic landscape in which interior iron atoms primarily host localized moments while the outer iron atoms neighboring the tellurium layers produce spin-polarized itinerant carriers that cross the vdW gap. The large energy cost associated with homogeneous nickel substitution is found to favor the spontaneous precipitation of the crystallographically and electronically ``clean''high-T$_C$ phase. Finally, we compare metal-rich vdW magnets with binary magnetic alloys, and discuss the unifying roles of nano-precipitates in stabilizing otherwise unattainable bulk phases. Our work provides mechanistic insights into the record-high T$_C$ ferromagnetism in (Fe,Ni)$_{5+\delta}$GeTe$_2$, establishing a rigorous foundation for the atomic engineering of vdW magnetic metals informed by direct electronic signatures.

T. Werner, Jonathan T. Reichanadter, Xiang Chen et al. · 0 citations
#machine learning Preprint Apr 2026

AutoREC: A reinforcement learning platform for equivalent circuit model generation

The platform supports an end-to-end workflow encompassing EIS preprocessing with selectable impedance representations, agent setup and training, ECM generation for new measurements, and visualization-based evaluation and analysis of agent decision-making.

A. Jaberi, Yonatan Kurniawan, Robert Black et al. · 0 citations

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