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1.
Nat Commun ; 14(1): 1693, 2023 Mar 27.
Artigo em Inglês | MEDLINE | ID: mdl-36973266

RESUMO

The conducting boundary states of topological insulators appear at an interface where the characteristic invariant ℤ2 switches from 1 to 0. These states offer prospects for quantum electronics; however, a method is needed to spatially-control ℤ2 to pattern conducting channels. It is shown that modifying Sb2Te3 single-crystal surfaces with an ion beam switches the topological insulator into an amorphous state exhibiting negligible bulk and surface conductivity. This is attributed to a transition from ℤ2 = 1 → ℤ2 = 0 at a threshold disorder strength. This observation is supported by density functional theory and model Hamiltonian calculations. Here we show that this ion-beam treatment allows for inverse lithography to pattern arrays of topological surfaces, edges and corners which are the building blocks of topological electronics.

2.
Data Brief ; 40: 107674, 2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-34917713

RESUMO

This Data-in-brief article includes datasets of electron microscopy, polarised neutron reflectometry and magnetometry for ultra-small cobalt particles formed in titania thin films via ion beam synthesis. Raw data for polarised neutron reflectometry, magnetometry and the particle size distribution are included and made available on a public repository. Additional elemental maps from scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) are also presented. Data were obtained using the following types of equipment: the NREX and PLATYPUS polarised neutron reflectometers; a Quantum Design Physical Property Measurement System (14 T); a JEOL JSM-6490LV SEM, and a JEOL ARM-200F scanning transmission electron microscope (STEM). The data is provided as supporting evidence for the article in Applied Surface Science (A. Bake et al., Appl. Surf. Sci., vol. 570, p. 151068, 2021, DOI 10.1016/j.apsusc.2021.151068), where a full discussion is given. The additional supplementary reflectometry and modelling datasets are intended to assist future scientific software development of advanced fitting algorithms for magnetization gradients in thin films.

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