Chrome Extension
WeChat Mini Program
Use on ChatGLM

Structural, Magnetic and Electric Properties of Sr0.95Y0.05Fe12-xZrxO19 (x = 0–2) M−type Hexaferrites

Journal of Magnetism and Magnetic Materials(2022)

Phenikaa Univ | Vietnam Natl Univ | Hanoi Univ Sci & Technol | Chungnam Natl Univ | Ulsan Natl Inst Sci & Technol | Hankuk Univ Foreign Stud | Duy Tan Univ | Univ Nang

Cited 12|Views21
Abstract
The ceramic technique has been utilized to fabricate Sr0.95Y0.05Fe12-xZrxO19 (x = 0-2) samples. Structural and Raman-scattering analyses have revealed that the samples with x = 0 and 0.5 possess the M-type hexagonal-ferrite phase, while the others have the additional Zr-related phase. All samples exhibit the hard-magnetic behavior and the magnetic parameters tend to decrease with increasing Zr-doping content. The study on the electric polarization has indicated that the sample with x = 0 shows the coexistence of paraelectric and weak ferroelectric behaviors, while the other samples (x = 0.5-2) show conductive behaviour with nearly circular loops. The changes in the magnetic and electrical properties mainly related to the co-presence of Fe2+ and Fe3+ ions, as evidenced from analyzing X ray absorption data.
More
Translated text
Key words
M-type hexaferrites,Crystallographic structure,Magnetic and electric properties
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
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest