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紫外高光谱成像作为一种过程分析工具,用于直接键合铜上氧化层和铜态的特性分析。

UV Hyperspectral Imaging as Process Analytical Tool for the Characterization of Oxide Layers and Copper States on Direct Bonded Copper.

机构信息

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.

Institute of Physical and Theoretical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany.

出版信息

Sensors (Basel). 2021 Nov 4;21(21):7332. doi: 10.3390/s21217332.

Abstract

Hyperspectral imaging and reflectance spectroscopy in the range from 200-380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.

摘要

采用 200-380nm 范围内的光谱成像和反射光谱技术,以非破坏性方式快速检测和表征直接键合铜上铜的氧化态及其各层厚度。单点紫外反射光谱作为一种成熟的方法,被用于比较光谱成像结果的质量。对于铜表面的横向分辨测量,使用了基于推扫式成像仪的紫外光谱成像系统。研究了六种不同类型的直接键合铜,每种类型的氧化层厚度都不同,并使用 X 射线光电子能谱进行了深度剖析。总共测量了 28 个样本,以开发多元模型来表征和预测氧化层厚度。主成分分析模型 (PCA) 能够在第一和第二主成分上将样本类型进行总体区分,对于紫外光谱和光谱成像,解释方差分别为 100.0%和 96%。偏最小二乘回归 (PLS-R) 模型表现出可靠的性能,相关系数为 0.94 和 0.94,RMSEC 分别为 1.64nm 和 1.76nm。所开发的在线原型系统结合多元数据分析模型,为该技术在实际大规模工艺中的进一步发展展示了巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1723/8588143/664d9c81eedd/sensors-21-07332-g001.jpg

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