Quantifying flux residues after soldering on technical copper using ultraviolet visible (UV-Vis) spectroscopy and multivariate analysis

被引:2
作者
Englert, Tim [1 ,2 ,3 ]
Stiedl, Jan [2 ,3 ,4 ]
Green, Simon [3 ]
Jacob, Timo [1 ]
Chasse, Thomas [4 ,5 ]
Rebner, Karsten [2 ]
机构
[1] Ulm Univ, Inst Electrochem, Albert Einstein Allee 47, D-89081 Ulm, Germany
[2] Reutlingen Univ, Proc Anal & Technol, Alteburgstr 150, D-72762 Reutlingen, Germany
[3] Robert Bosch GmbH, Automot Elect, Postfach 1342, D-72703 Reutlingen, Germany
[4] Univ Tubingen, Inst Phys & Theoret Chem, Morgenstelle 18, D-72076 Tubingen, Germany
[5] Ctr Light Matter Interact Sensors & Analyt LISA, Avf Morgenstelle 15, D-72076 Tubingen, Germany
关键词
XPS; MVA; PLS; Monitoring; Cleaning process; Cleanliness; HUMIDITY-RELATED FAILURES; REFLECTANCE SPECTROSCOPY; CONTACT-ANGLE; ACIDS; RELIABILITY; CLEANLINESS; CHEMISTRY; CATALYSTS; CORROSION; SURFACES;
D O I
10.1016/j.microrel.2021.114367
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Employing diffuse reflection ultraviolet visible (UV-Vis) spectroscopy we developed an approach that is capable to quantitatively determine flux residues on a technical copper surface. The technical copper surface was sol-dered with a no-clean flux system of organic acids. By a post-solder cleaning step with different cleaning pa-rameters, various levels of residues were produced. The surface was quantitatively and qualitatively characterized using X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES), Fourier trans -form infrared spectroscopy (FTIR) and diffuse reflection UV-Vis spectroscopy. With the use of a multivariate analysis (MVA) we examined the UV-Vis data to create a correlation to the carbon content on the surface. The UV-Vis data could be discriminated for all groups by their level of organic residues. Combined with XPS the data were evaluated by a partial least squares (PLS) regression to establish a model. Based on this predictive model, the carbon content was calculated with an absolute error of 2.7 at.%. Due to the high correlation of predictive model, the easy-to-use measurement and the evaluation by multivariate analysis the developed method seems suitable for an online monitoring system. With this system, flux residues can be detected in a manufacturing cleaning process of technical surfaces after soldering.
引用
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页数:9
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