Multiferroic Properties and Structural Features of M -Type Al-substituted Barium Hexaferrites

A. V. Trukhanov,S. V. Trukhanov,V. G. Kostishin,L. V. Panina,M. M. Salem,I. S. Kazakevich,V. A. Turchenko,V. V. Kochervinskii, D. A. Krivchenya

Physics of the Solid State（2017）

National University of Science and Technology MISiS | Frank Neutron Physics Laboratory | Moscow Branch of Karpov Institute of Physical Chemistry

Cited 117|Views8

Abstract

Precise studies of the crystal and magnetic structures of M-type substituted barium hexaferrites BaFe12–x Al x O19 (0.1 ≤ x ≤ 1.2) have been performed by powder neutron diffraction in the temperature range 300–730 K. The electric polarization and the magnetization, and also the magnetoelectric effect of the compositions under study have been studied in electric (to 110 kV/m) and magnetic (to 14 T) fields at room temperature. The spontaneous polarization and significant correlation between the dielectric and magnetic subsystems have been observed at room temperature. The magnetoelectric effect value is, on average, about 5%, and it increases slightly with the aluminum cation concentration. The precise structural studies made it possible to reveal the cause and the mechanism of formation of the spontaneous polarization in M-type substituted barium hexaferrites BaFe12–x Al x O19 (x ≤ 1.2) with a collinear ferromagnetic structure.

Translated text

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper