Data for: Defect Landscape Engineering to Tune Skyrmion-Antiskyrmion Systems in FeGe

Description

A promising architecture for next-generation, low energy spintronic devices uses skyrmions— nanoscale whirlpools of magnetic moments— as information carriers. Notably, schemes for racetrack memory have been proposed in which skyrmions and antiskyrmions, their antiparticle, serve as the logical bits 1 and 0. However, major challenges exist to designing skyrmion-antiskyrmion based computing. The presence of both particles in one material is often mutually exclusive such that few systems have been identified in which they coexist, and in these systems their appearance is stochastic rather than deterministic. Here, we create a tunable skyrmion-antiskyrmion system in FeGe films through ion-irradiation and annealing, and detail the structural properties of the films under these various conditions. Specifically, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au4+ ions, showing evidence that the amorphized regions preferentially host antiskyrmions at densities controlled by the irradiation fluence. In this work, we focus on a subsequent, systematic electron diffraction study with in-situ annealing, demonstrating the ability to recrystallize controllable fractions of the material at temperatures ranging from approximately 150°C to 250°C, enabling further tunability of skyrmion/antiskyrmion populations. We describe the crystallization kinetics using the Johnson-Mehl-Avrami-Kolmogorov model, finding that growth of crystalline grains is consistent with diffusion-controlled one-to-two dimensional growth with a decreasing nucleation rate. The procedures developed here can be applied towards creation of skyrmion-antiskyrmion systems for energy efficient, high density data storage, spin wave emission produced by skyrmion-antiskyrmion pair annihilation, and more generally testbeds for research on skyrmion-antiskyrmion liquids and crystals. This dataset includes all the raw data and the Python script used for data analysis and figure generation for the paper. This includes .csv files containing the data used in figures, microscopy images (.tif files), python code used for the analysis, and an Origin file (.opju) containing all figures and data spreadsheets, which can be opened using Origin Viewer, a free application that permits viewing and copying of data contained in Origin project files.

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