Screw Dislocations in Chiral Magnets

Azhar, Maria; Kravchuk, Volodymyr P.; Garst, Markus

doi:10.1103/physrevlett.128.157204

Cited by 13 publications

(8 citation statements)

References 61 publications

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“…NPs often have asymmetric faces, edges, and vertices, as well as both surface and bulk defects and dislocations present in the crystal structure. Chiral arrangements of chiral defects [249,250] or distortions [251][252][253][254] of the crystal lattice (e.g., screw dislocations) [255] can in fact induce chiroptical activity in NPs. The use of chiral ligands, either in situ or by post-synthetic treatment, increases the probability of generating chiral defects and distortions.…”

Section: Chiral Shape Of Individual Npsmentioning

confidence: 99%

Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

Kuznetsova,

Coogan,

Botov

et al. 2024

Advanced Materials

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Machine learning holds significant research potential in the field of nanotechnology, enabling nanomaterial structure and property predictions, facilitating the design of novel materials, and reducing the need for time‐consuming and labour‐intensive experiments and simulations. In contrast to their achiral counterparts, the application of machine learning for chiral nanomaterials and nanostructures is still in its infancy, with a limited number of publications to date. This is despite the great potential of machine learning to advance the development of new sustainable chiral materials with high values of optical activity, circularly polarised luminescence, and enantioselectivity, as well as for the analysis of structural chirality by electron microscopy. In this review, we provide an analysis of machine learning methods used in studying achiral nanomaterials, subsequently offering guidance on adapting and extending this work to chiral nanomaterials. We present an overview of chiral nanomaterials within the framework of synthesis‐structure‐property‐application relationships and provide insights on how to leverage machine learning for the study of these highly complex relationships. We also review and discuss some key recent publications on the application of machine learning for chiral nanomaterials. Finally, the review captures the key achievements, ongoing challenges, and the prospective outlook for this very important research field.This article is protected by copyright. All rights reserved

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Section: Chiral Shape Of Individual Npsmentioning

confidence: 99%

Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

Kuznetsova,

Coogan,

Botov

et al. 2024

Advanced Materials

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“…In Ref. 25 , such vortex-cone configurations were discussed in the context of screw dislocations in chiral magnets. Here, such a configuration appears due to an interplay between short-range interactions (Heisenberg exchange and DMI) and a long-range demagnetizing field.…”

Section: Initial State For Hopfion Rings In Micromagnetic Simulationsmentioning

confidence: 99%

“…Figure 1a shows an initial state with three skyrmion strings, demonstrating a weak braiding effect and conical modulations along the sample thickness. In a confined geometry, due to the effect of the demagnetizing field such modulations exhibit an additional twist that resembles a vortex-like structure 25 in any transverse section. Swapping of the direction of the external magnetic field leads to a flip of the magnetization along the perimeter of the disk, as shown in Fig.…”

mentioning

confidence: 99%

Hopfion rings in a cubic chiral magnet

Kiselev

Zheng

Rybakov

et al. 2023

Preprint

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Magnetic skyrmions and hopfions are topological solitons1, well-localized field configurations that have gained significant attention over the past decade due to their unique particle-like properties, making them promising objects for spintronic applications. Skyrmions2,3 are two-dimensional solitons resembling vortex-like string structures that can penetrate an entire sample. Hopfions4-9 are three-dimensional solitons confined within a magnetic sample volume and can be considered as closed twisted skyrmion strings that take the shape of a ring in the simplest case. Despite extensive research on magnetic skyrmions, the direct observation of magnetic hopfions has remained challenging. Here, we present the first direct observations of coupled states of hopfions and skyrmion strings in FeGe plates using transmission electron microscopy. Furthermore, we provide a protocol for nucleating hopfion rings around skyrmion strings in confined samples, which we verify using Lorentz imaging and electron holography. Our results are highly reproducible, in full agreement with micromagnetic simulations, and offer new insight into the diversity of topological solitons in three-dimensional chiral magnets and their potential for practical applications.

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“…They have been shown to work as emergent inductors [18][19][20], lead to non-reciprocal charge and spin transport [21][22][23][24], or may actively pump spin and charge as Archimedean screws [25][26][27]. Moreover, they can serve as a non-trivial background for other topological excitations such as skyrmions [28][29][30] or dislocations [31][32][33][34]. Only recently, it has been shown that the orientation vector q of this lamellar phase can be combed and steered by external magnetic fields [35,36] and even electric currents [37,38].…”

Section: Introductionmentioning

confidence: 99%

Helitronics as a potential building block for classical and unconventional computing

Bechler

Masell

2023

Neuromorph. Comput. Eng.

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Non-trivial magnetic structures have been proposed to be a promising route to unconventional computing. The interplay between magnetic stiffness and Dzyaloshinskii-Moriya interaction (DMI) can stabilize a helical order of the magnetisation which is often discarded as trivial. However, recent studies have shown that the orientation of these helical magnetisation structures can be manipulated by strong enough magnetic fields [1] and spin currents [2] which revealed their unexpectedly complex dynamics. Using micromagnetic simulations, we investigate novel magnetic memory devices such as magnetoresistive random-access memory (MRAM) cells and memristors which use the orientation of the helical phase as an order parameter, dubbed helitronics. We propose a way to read-out said devices using the anisotropic magneto resistance (AMR) and point out their use for unconventional computing purposes.

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Screw Dislocations in Chiral Magnets

Cited by 13 publications

References 61 publications

Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

Hopfion rings in a cubic chiral magnet

Helitronics as a potential building block for classical and unconventional computing

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