Spin-texture inversion in the giant Rashba semiconductor BiTeI

Semiconductors with strong spin-orbit interaction as the underlying mechanism for the generation of spin-polarized electrons are showing potential for applications in spintronic devices. Unveiling the full spin texture in momentum space for such materials and its relation to the microscopic structure of the electronic wave functions is experimentally challenging and yet essential for exploiting spin-orbit effects for spin manipulation. Here we employ a state-of-the-art photoelectron momentum microscope with a multichannel spin filter to directly image the spin texture of the layered polar semiconductor BiTeI within the full two-dimensional momentum plane. Our experimental results, supported by relativistic ab initio calculations, demonstrate that the valence and conduction band electrons in BiTeI have spin textures of opposite chirality and of pronounced orbital dependence beyond the standard Rashba model, the latter giving rise to strong optical selection-rule effects on the photoelectron spin polarization. These observations open avenues for spin-texture manipulation by atomic-layer and charge carrier control in polar semiconductors.This work was supported by DFG (through SFB 1170 'ToCoTronics') and through FOR1162 (P3). We acknowledge the support by the Basque Departamento de Educacion, UPV/EHU (Grant Number IT-756-13), Spanish Ministerio de Economia y Competitividad (MINECO Grant Number FIS2013-48286-C2-2-P), Tomsk State University Academic D.I. Mendeleev Fund Program in 2015 (Research Grant Number 8.1.05.2015), the Russian Foundation for Basic Research (Grant Numbers 15-02-01797 and 15-02-589 02717). Partial support by the Saint Petersburg State University (Grant Number 15.61.202.2015) is also acknowledged

Intermixing-Driven Surface and Bulk Ferromagnetism in the Quantum Anomalous Hall Candidate MnBi6Te10

The recent realizations of the quantum anomalous Hall effect (QAHE) in MnBi2Te4 and MnBi4Te7 benchmark the (MnBi2Te4)(Bi2Te3)n family as a promising hotbed for further QAHE improvements. The family owes its potential to its ferromagnetically (FM) ordered MnBi2Te4 septuple layers (SLs). However, the QAHE realization is complicated in MnBi2Te4 and MnBi4Te7 due to the substantial antiferromagnetic (AFM) coupling between the SLs. An FM state, advantageous for the QAHE, can be stabilized by interlacing the SLs with an increasing number n of Bi2Te3 quintuple layers (QLs). However, the mechanisms driving the FM state and the number of necessary QLs are not understood, and the surface magnetism remains obscure. Here, robust FM properties in MnBi6Te10 (n = 2) with Tc ≈ 12 K are demonstrated and their origin is established in the Mn/Bi intermixing phenomenon by a combined experimental and theoretical study. The measurements reveal a magnetically intact surface with a large magnetic moment, and with FM properties similar to the bulk. This investigation thus consolidates the MnBi6Te10 system as perspective for the QAHE at elevated temperatures

Author Correction: Non-local effect of impurity states on the exchange coupling mechanism in magnetic topological insulators

A Correction to this paper has been published: https://doi.org/10.1038/s41535-021-00314-

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio