Kabiraj, A and Kumar, M and Mahapatra, S (2020) High-throughput discovery of high Curie point two-dimensional ferromagnetic materials. In: npj Computational Materials, 6 (1).
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Abstract
Databases for two-dimensional materials host numerous ferromagnetic materials without the vital information of Curie temperature since its calculation involves a manually intensive complex process. In this work, we develop a fully automated, hardware-accelerated, dynamic-translation based computer code, which performs first principles-based computations followed by Heisenberg model-based Monte Carlo simulations to estimate the Curie temperature from the crystal structure. We employ this code to conduct a high-throughput scan of 786 materials from a database to discover 26 materials with a Curie point beyond 400 K. For rapid data mining, we further use these results to develop an end-to-end machine learning model with generalized chemical features through an exhaustive search of the model space as well as the hyperparameters. We discover a few more high Curie point materials from different sources using this data-driven model. Such material informatics, which agrees well with recent experiments, is expected to foster practical applications of two-dimensional magnetism. © 2020, The Author(s).
Item Type: | Journal Article |
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Publication: | npj Computational Materials |
Publisher: | NATURE PUBLISHING GROUP |
Additional Information: | The copyright of this article belongs to NATURE PUBLISHING GROUP |
Keywords: | Calculations; Codes (symbols); Computer hardware; Computerized tomography; Crystal structure; Curie temperature; Data mining; Ferromagnetism; Intelligent systems; Monte Carlo methods, Chemical features; Complex Processes; Data-driven model; Dynamic translation; Hardware-accelerated; Machine learning models; Material Informatics; Two-dimensional materials, Ferromagnetic materials |
Department/Centre: | Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology) |
Date Deposited: | 10 Aug 2020 07:07 |
Last Modified: | 10 Aug 2020 07:07 |
URI: | http://eprints.iisc.ac.in/id/eprint/65210 |
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