Chrome Extension
WeChat Mini Program
Use on ChatGLM
VIPCreated with Sketch.

    • Microstructural and Electrical Resistivity of TiN Electrode Films Prepared by Direct Current (DC) Reactive Magnetron Sputtering

    Yu Zhang, Wen-Tao Shi,Lei Chen,Fu-Ru Zhong,Zhen-Xing Fang,Long-Fei Yuan

    SCIENCE OF ADVANCED MATERIALS（2023）

    Zunyi Normal Coll

    Cited 1|Views16
    Abstract
    In this study, the crystal structure as well as electron transport of TiN thin films were evaluated. We used DC reactive magnetron sputtering to deposit a thin layer of polycrystalline titanium nitride (TiN) on a Si (100) substrate starting from elemental Ti in a nitrogen atmosphere. The influence of nitrogen flow rate on the crystal structure, surface morphology, and electron transport of TiN were investigated systematically. It was found that the preferred orientation and conductivity of TiN thin films exhibit strong nitrogen flow rate dependence. The preferred orientation changed from (111) to (200) initially and then changed back to (111) as the nitrogen flow rate increases. However, an increase in the (200) phase leads to higher conductivity and lower surface roughness. At the optimized deposition conditions, ultra-thin (around 30 nm) TiN thin films with a low resistivity of 101.8 μ C·cm and a surface roughness of less than or equal to 0.51 nm were obtained. These superior performances, along with low running costs, suggest that TiN thin films have great potential for use as electrodes in microelectronic devices.
    More
    Translated text
    Key words
    TiN Films,Preferred Orientation,Reactive Sputtering,Resistivity,Microstructure
    求助PDF
    上传PDF
    View via Publisher
    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
    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
    【要点】：本研究通过直流反应磁控溅射技术制备TiN薄膜，并探究了氮气流量对薄膜晶体结构、表面形态及电子输运性能的影响，发现氮气流量对TiN薄膜的择优取向和导电性有显著影响。
    

    【方法】：采用直流反应磁控溅射技术，在Si (100) 衬底上从元素钛在氮气氛围中沉积多晶钛氮化物（TiN）薄膜。
    

    【实验】：通过改变氮气流量，研究了TiN薄膜的晶体结构、表面形貌和电子输运性能，发现氮气流量影响TiN薄膜的择优取向，从(111)变为(200)，再变回(111)。在优化条件下，获得了低电阻率（101.8 μΩ·cm）和表面粗糙度小于等于0.51 nm的约30 nm厚的TiN薄膜。实验使用的数据集为氮气流量变化下的TiN薄膜性能数据。