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COMMON PART

Project Number23-22-00328

Project titleMagnetic frustrations of 3D artificial spin ice

Project LeadShevchenko Yuriy

AffiliationInstitute for Applied Mathematics, Far Eastern Branch, Russian Academy of Sciences,

Research area 02 - PHYSICS AND SPACE SCIENCES, 02-207 - Magnetic properties and materials

KeywordsArtificial nanosystems, metamaterials, spin ice, magnetic frustrations, Monte Carlo methods, magnetism, statistical thermodynamics, high-performance computing

PROJECT CONTENT

Annotation
Artificial spin ice is a metamaterial consisting of islands of magnetic material stacked in such a way that the resulting structure exhibits collective magnetic properties associated with the competition of the magnetic fields of individual islands. The island is a single-domain nanoscale magnet that can interact with other islets through dipole-dipole interaction. The lattice geometry imposes configuration constraints, due to which not all pairwise interactions can be simultaneously satisfied. This phenomenon is called frustrations and systems are frustrated. The ability to fine-tune the lattice geometry allows one to improve the properties of metamaterials, such as magnetic susceptibility, anisotropy, energy barriers between similar energy configurations, etc. Most research over the past 15 years has focused on planar magnetic structures, which have many disadvantages. The most important is insufficiently dense packing. The use of bulk artificial spin ice makes it possible to achieve more consistent and stable exotic magnetic states and, therefore, denser packing of electronic devices that use spin ice effects. But it causes several difficulties both in numerical simulations and in experiments. Techniques for the production and preparation of nanoscale magnetic metamaterials are actively developing, and researchers are offering increasingly sophisticated ways to create precise samples of magnetic structures, including three-dimensional (bulk) spin ices. The possibilities of material design are limited only by the imagination of the researchers. Such tuning, as well as predicting the properties of experimental materials, is possible with using numerical experiments and computer physical modeling. But for three-dimensional systems, even the minimum system size required to simulate the desired effect is much larger than the same in two-dimensional case. There is a large variety of configurations of artificial spin ice objects, differing in both material composition and shape, and each of them has its own unique properties. Without computer modeling or experiment, it is impossible to predict these properties in advance. Hence, there is a complex and large-scale task of classifying them and determining their thermodynamic characteristics. The project proposes the search and theoretical study of the magnetic properties of three-dimensional frustrated lattice structures with the potential possibility of creating a real prototype and further application in electronic devices. The task is planned to be solved by computer modeling methods, which requires fine-tuning of existing computational methods for working with three-dimensional macrospin structures and long-range dipole-dipole interaction. The task requires creation and optimization of computational algorithms to work with spin ice objects.

Expected results
The project will propose structures of new bulk spin ice metamaterials and examine in detail their thermodynamic properties. These are three-dimensional lattices consisting of magnetic particles with the size of several tens nanometers that shows the frustration effect in the point dipole model. Improvements in nanofabrication techniques are helping to prototype materials with high accuracy, and allowing observation of new, previously unknown phenomena. With the development of technologies and experimental techniques, it became possible to realize almost any geometry and realize direct control of collective magnetic dynamics, which opened the way to a meaningful synthetic design of new exotic states, not inherent to natural materials. The obtained results can become the basis for further in-situ experiments. Possible applications of the resulting metamaterials include microelectronic devices for computing, storing and encrypting data, with the prospect of using the materials in the emerging field of unconventional computing, including non-boolean or neuromorphic computing.

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