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| Format: | Preprint |
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2026
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| Online Access: | https://arxiv.org/abs/2602.21575 |
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| _version_ | 1866911468274843648 |
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| author | Chandra, Soham Sarkar, Soumyajit |
| author_facet | Chandra, Soham Sarkar, Soumyajit |
| contents | Patterned two-dimensional (2D) magnetic nanostructures constitute geometry-engineered spin systems in which exchange, anisotropy, dipolar coupling, and finite-size effects operate on comparable energy scales. Spatial modulation of continuous magnetic films produces confinement-driven critical behavior, compensation phenomena, metastable switching pathways, and topologically non-trivial textures such as vortices and skyrmions. Computational modeling plays a central role in resolving this complexity, enabling quantitative construction of thermodynamic phase diagrams and analysis of geometry-dependent stability regimes. This review synthesizes theoretical and numerical frameworks for patterned 2D magnetism, including classical spin models, stochastic spin dynamics, rare-event methods, and multiscale parameterization informed by first-principles calculations. Representative systems-nanodot and antidot arrays, artificial spin-ice lattices, exchange-modulated heterostructures, and patterned van der Waals magnets- illustrate how geometry functions as an effective thermodynamic control parameter. Emerging directions in nonequilibrium modeling, multiphysics coupling, and scalable data-centric workflows are discussed in the context of predictive phase mapping. Patterned 2D magnetism thus exemplifies the convergence of geometry-controlled materials engineering and computational statistical physics, with phase stability and controlled spin textures at the core of next-generation spintronic architectures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_21575 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Computational Frameworks for Patterned Two-Dimensional Magnetism Chandra, Soham Sarkar, Soumyajit Materials Science Mesoscale and Nanoscale Physics Statistical Mechanics Patterned two-dimensional (2D) magnetic nanostructures constitute geometry-engineered spin systems in which exchange, anisotropy, dipolar coupling, and finite-size effects operate on comparable energy scales. Spatial modulation of continuous magnetic films produces confinement-driven critical behavior, compensation phenomena, metastable switching pathways, and topologically non-trivial textures such as vortices and skyrmions. Computational modeling plays a central role in resolving this complexity, enabling quantitative construction of thermodynamic phase diagrams and analysis of geometry-dependent stability regimes. This review synthesizes theoretical and numerical frameworks for patterned 2D magnetism, including classical spin models, stochastic spin dynamics, rare-event methods, and multiscale parameterization informed by first-principles calculations. Representative systems-nanodot and antidot arrays, artificial spin-ice lattices, exchange-modulated heterostructures, and patterned van der Waals magnets- illustrate how geometry functions as an effective thermodynamic control parameter. Emerging directions in nonequilibrium modeling, multiphysics coupling, and scalable data-centric workflows are discussed in the context of predictive phase mapping. Patterned 2D magnetism thus exemplifies the convergence of geometry-controlled materials engineering and computational statistical physics, with phase stability and controlled spin textures at the core of next-generation spintronic architectures. |
| title | Computational Frameworks for Patterned Two-Dimensional Magnetism |
| topic | Materials Science Mesoscale and Nanoscale Physics Statistical Mechanics |
| url | https://arxiv.org/abs/2602.21575 |