Tunable Magnetism in Atomically Thin Itinerant Antiferromagnet with Room-Temperature Ferromagnetic Order.

Addressing the need for modulated spin configurations is crucial, as they serve as the foundational building blocks for next-generation spintronics, particularly in atomically thin structures and at room temperature. In this work, we realize intrinsic ferromagnetism in monolayer flakes and tunable ferro-/antiferromagnetism in (FeCo)GeTe antiferromagnets. Remarkably, the ferromagnetic ordering (≥1 L) and antiferromagnetic ordering (≥4 L) remain discernible up to room temperature.

Anomalous electrons in a metallic kagome ferromagnet.

Ordinary metals contain electron liquids within well-defined 'Fermi' surfaces at which the electrons behave as if they were non-interacting. In the absence of transitions to entirely new phases such as insulators or superconductors, interactions between electrons induce scattering that is quadratic in the deviation of the binding energy from the Fermi level. A long-standing puzzle is that certain materials do not fit this 'Fermi liquid' description.

Observation of a singular Weyl point surrounded by charged nodal walls in PtGa.

Constrained by the Nielsen-Ninomiya no-go theorem, in all so-far experimentally determined Weyl semimetals (WSMs) the Weyl points (WPs) always appear in pairs in the momentum space with no exception. As a consequence, Fermi arcs occur on surfaces which connect the projections of the WPs with opposite chiral charges. However, this situation can be circumvented in the case of unpaired WP, without relevant surface Fermi arc connecting its surface projection, appearing singularly, while its Berry curvature field is absorbed by nontrivial charged nodal walls.

Super resolution convolutional neural network for feature extraction in spectroscopic data.

Two dimensional (2D) peak finding is a common practice in data analysis for physics experiments, which is typically achieved by computing the local derivatives. However, this method is inherently unstable when the local landscape is complicated or the signal-to-noise ratio of the data is low. In this work, we propose a new method in which the peak tracking task is formalized as an inverse problem, which thus can be solved with a convolutional neural network (CNN).

Electronic structures and unusually robust bandgap in an ultrahigh-mobility layered oxide semiconductor, BiOSe.

Semiconductors are essential materials that affect our everyday life in the modern world. Two-dimensional semiconductors with high mobility and moderate bandgap are particularly attractive today because of their potential application in fast, low-power, and ultrasmall/thin electronic devices. We investigate the electronic structures of a new layered air-stable oxide semiconductor, BiOSe, with ultrahigh mobility (~2.