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一种优化氧化锌薄膜化学蚀刻工艺的统计方法。

A statistical method to optimize the chemical etching process of zinc oxide thin films.

作者信息

Lynes David D, Chandrahalim Hengky, Brown Justin M, Singh Karanvir, Bodily Kyle T, Leedy Kevin D

机构信息

Department of Electrical and Computer Engineering, Air Force Institute of Technology, Wright-Patterson Air Force Base, OH 45433, USA.

Sensors Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH 45433, USA.

出版信息

R Soc Open Sci. 2022 Aug 3;9(8):211560. doi: 10.1098/rsos.211560. eCollection 2022 Aug.

DOI:10.1098/rsos.211560
PMID:35950193
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9346367/
Abstract

Zinc oxide (ZnO) is an attractive material for microscale and nanoscale devices. Its desirable semiconductor, piezoelectric and optical properties make it useful in applications ranging from microphones to missile warning systems to biometric sensors. This work introduces a demonstration of blending statistics and chemical etching of thin films to identify the dominant factors and interaction between factors, and develop statistically enhanced models on etch rate and selectivity of c-axis-oriented nanocrystalline ZnO thin films. Over other mineral acids, ammonium chloride (NHCl) solutions have commonly been used to wet etch microscale ZnO devices because of their controllable etch rate and near-linear behaviour. Etchant concentration and temperature were found to have a significant effect on etch rate. Moreover, this is the first demonstration that has identified multi-factor interactions between temperature and concentration, and between temperature and agitation. A linear model was developed relating etch rate and its variance against these significant factors and multi-factor interactions. An average selectivity of 73 : 1 was measured with none of the experimental factors having a significant effect on the selectivity. This statistical study captures the significant variance observed by other researchers. Furthermore, it enables statistically enhanced microfabrication processes for other materials.

摘要

氧化锌(ZnO)是一种适用于微米级和纳米级器件的材料。其理想的半导体、压电和光学特性使其在从麦克风到导弹预警系统再到生物识别传感器等各种应用中都很有用。这项工作展示了如何将薄膜的统计分析和化学蚀刻相结合,以识别主导因素及其之间的相互作用,并建立关于c轴取向的纳米晶ZnO薄膜蚀刻速率和选择性的统计增强模型。与其他无机酸相比,氯化铵(NH₄Cl)溶液因其可控的蚀刻速率和近似线性的行为,常用于湿法蚀刻微米级ZnO器件。研究发现蚀刻剂浓度和温度对蚀刻速率有显著影响。此外,这是首次证实已识别出温度与浓度之间以及温度与搅拌之间的多因素相互作用。建立了一个线性模型,将蚀刻速率及其方差与这些显著因素和多因素相互作用联系起来。测得平均选择性为73:1,且没有任何实验因素对选择性有显著影响。这项统计研究捕捉到了其他研究人员观察到的显著差异。此外,它还能为其他材料实现统计增强的微加工工艺。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06e6/9346367/5746aebf4332/rsos211560f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06e6/9346367/5eb8932d34a1/rsos211560f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06e6/9346367/5746aebf4332/rsos211560f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06e6/9346367/5eb8932d34a1/rsos211560f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06e6/9346367/5746aebf4332/rsos211560f04.jpg

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