Virtual experiments in computational magnetism with mag2exp

IF 11.9 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Samuel J. R. Holt, Martin Lang, James C. Loudon, Thomas J. Hicken, Dieter Suess, David Cortés-Ortuño, Swapneel A. Pathak, Marijan Beg, Kauser Zulfiqar, Hans Fangohr
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引用次数: 0

Abstract

We have designed and implemented the Python package mag2exp, which enables researchers to perform a range of virtual experiments given a spatially resolved vector field for the magnetization, a typical result from computational methods to simulate magnetism such as micromagnetics. This software allows experimental measurements such as magnetometry, microscopy, and reciprocal space based techniques to be simulated in order to obtain observables that are comparable to those of the corresponding experimental measurement. Such virtual experiments tend to be more economic to carry out than actual experiments. There are many uses for virtual experiments, including (i) choosing the best experimental techniques and assessing their feasibility prior to experimentation, (ii) fine tuning experimental setup, (iii) guiding the experiment by conducting concurrent simulations of the measurement, and (iv) interpreting the experimental data at a later point though both qualitative and quantitative methods.

Abstract Image

mag2exp在计算磁学中的虚拟实验
我们已经设计并实现了Python包mag2exp,它使研究人员能够执行一系列虚拟实验,给定一个空间分辨的矢量场的磁化,一个典型的结果,从计算方法来模拟磁性,如微磁性。该软件允许模拟实验测量,如磁强计、显微镜和基于空间的互反技术,以获得与相应实验测量相媲美的可观测值。这样的虚拟实验往往比实际实验更经济。虚拟实验有许多用途,包括(i)选择最佳实验技术并在实验前评估其可行性,(ii)微调实验设置,(iii)通过并行模拟测量来指导实验,以及(iv)在稍后通过定性和定量方法解释实验数据。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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