氨化法制备大量单晶Ga N纳米线及其特性研究
MICROFABRICATION TECHNOLOGY（2008）
Abstract
利用磁控溅射技术先在硅村底上制备Ga2O3/Co薄膜,然后在管式炉中通入流动的氨气在950℃对薄膜进行氨化,反应后成功制备出大量GaN纳米线.采用X射线衍射(xRD)、傅里叶红外吸收光谱(FTIR)、扫描电子显微镜(SEM)和高分辨透射电子显微镜(HRTEM)对样品进行分析.结果表明,采用此方法得到了六方纤锌矿结构的GaN单晶纳米线,纳米线的直径在50 nm～150 nm范围内,长度为几十微米.
MoreTranslated text
求助PDF
上传PDF
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
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
Summary is being generated by the instructions you defined