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首页> 外文期刊>Journal of Vacuum Science & Technology. B, Microelectronics and Nanometer Structures >Real-time material quality prediction, fault detection, and contamination control in AlGaN/GaN high electron mobility transistor metalorganic chemical vapor deposition process using in situ chemical sensing
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Real-time material quality prediction, fault detection, and contamination control in AlGaN/GaN high electron mobility transistor metalorganic chemical vapor deposition process using in situ chemical sensing

机译:使用原位化学感应的AlGaN / GaN高电子迁移率晶体管金属有机化学气相沉积工艺中的实时材料质量预测,故障检测和污染控制

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摘要

Gallium nitride and its alloys promise to be key materials for future heterojunction semiconductor devices aimed at high frequency, high power electronic applications. However, manufacturing for such high performance products is challenged by reproducibility and material quality constraints that are notably higher than those required for optoelectronic applications. To meet this challenge, in situ mass spectrometry was implemented in AlGaN/GaN/AlN metalorganic chemical vapor deposition processes as a real-time process and wafer state metrology tool. In particular, the various pregrowth gas phase impurity levels within the reactor, measured by mass spectrometry in real time, were correlated to photoluminescence band-edge and deep-level properties measured postprocess. Band-edge intensities increased and deep-level intensities decreased with lower oxygen-containing impurity levels in the pregrowth environment. These real-time indications of oxygen impurity incorporation were used for fault detection and to optimize preprocess reactor conditioning involving degassing of the wafer susceptor and furnace liner elements. Because this in situ sensing provides a control on contaminants to assure high material quality and a fault detection capability as well, it is now implemented routinely for both purposes. These real-time contamination control and fault detection strategies complement an overall advanced process control program for GaN-based semiconductor manufacturing, offering a systematic methodology to improve the product quality of GaN-based electronic devices.
机译:氮化镓及其合金有望成为未来针对高频,高功率电子应用的异质结半导体器件的关键材料。然而,对于此类高性能产品的制造受到可再现性和材料质量限制的挑战,该限制明显高于光电应用所需的那些。为了应对这一挑战,在AlGaN / GaN / AlN金属有机化学气相沉积工艺中实施了原位质谱,作为实时工艺和晶圆状态计量工具。特别地,通过质谱实时测量的反应器内各种预生长气相杂质水平与光致发光带边缘和在加工后测量的深水平性质相关。在预生长环境中,随着含氧杂质水平的降低,带边强度增加,深层强度降低。这些氧杂质掺入的实时指示用于故障检测和优化涉及晶片基座和炉衬元件脱气的预处理反应器条件。由于这种原位传感技术可以控制污染物,从而确保高质量的材料质量和故障检测能力,因此现在可以同时实现这两个目的。这些实时污染控制和故障检测策略补充了基于GaN的半导体制造的整体高级过程控制程序,从而提供了一种系统的方法来提高GaN基电子设备的产品质量。

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