scholarly journals Effect of Ni(P) Layer Thickness on Interface Reaction and Reliability of Ultrathin ENEPIG Surface Finish

Materials ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 7874
Author(s):  
Panwang Chi ◽  
Yesu Li ◽  
Hongfa Pan ◽  
Yibo Wang ◽  
Nancheng Chen ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Surface Finish ◽  
High Frequency ◽  
Solder Joints ◽  
Interface Reaction ◽  
Temperature Cycle ◽  
Sac305 Solder ◽  
Surface Finishes ◽  
Reliability Of Solder Joints ◽  
Temperature Cycle Test

Electroless Ni(P)/electroless Pd/immersion Au (ENEPIG) is a common surface finish in electronic packaging, while the Ni(P) layer increases the impedance of solder joints and leads to signal quality degradation in high-frequency circuits. Reducing the thickness of the Ni(P) layer can balance the high impedance and weldability. In this paper, the interfacial reaction process between ultrathin ENEPIG substrates with different Ni layer thicknesses (0.112 and 0.185 μm) and Sn–3.0Ag–0.5Cu (SAC305) solder during reflow and aging was studied. The bonding ability and reliability of solder joints with different surface finishes were evaluated based on solder ball shear test, drop test and temperature cycle test (TCT), and the failure mechanism was analyzed from the perspective of intermetallic compound (IMC) interface growth. The results showed that the Ni–Sn–P layer generated by ultrathin ENEPIG can inhibit the growth of brittle IMC so that the solder joints maintain high shear strength. Ultrathin ENEPIG with a Ni layer thickness of 0.185 μm had no failure cracks under thermal cycling and drop impact, which can meet actual reliability standards. Therefore, ultrathin ENEPIG has broad prospects and important significance in the field of high-frequency chip substrate design and manufacturing.

Sequential interfacial reactions of SAC305 solder joints with thin ENEPIG surface finishes

2018 ◽  
Vol 50 (11) ◽  
pp. 1046-1050 ◽  
Author(s):  
Jeong-Won Yoon ◽  
Jong-Hoon Back ◽  
Seung-Boo Jung
Keyword(s):  
Solder Joints ◽  
Interfacial Reactions ◽  
Sac305 Solder ◽  
Surface Finishes

scholarly journals Influence of Flux and Related Factors on Intermetallic Layer Growth within SAC305 Solder Joints

Materials ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 7909
Author(s):  
Karel Dušek ◽  
Petr Veselý ◽  
David Bušek ◽  
Adam Petráč ◽  
Attila Géczy ◽  
...  
Keyword(s):  
Image Analysis ◽  
Layer Thickness ◽  
Surface Finish ◽  
Intermetallic Layer ◽  
Layer Growth ◽  
Solder Paste ◽  
Sac305 Solder ◽  
Related Factors ◽  
Reflow Soldering ◽  
Solder Mask

Flux contained in solder paste significantly affects the process of solder joint creation during reflow soldering, including the creation of an intermetallic layer (IML). This work investigates the dependence of intermetallic layer thickness on ROL0/ROL1 flux classification, glossy or matt solder mask, and OSP/HASL/ENIG soldering pad surface finish. Two original SAC305 solder pastes differing only in the used flux were chosen for the experiment. The influence of multiple reflows was also observed. The intermetallic layer thicknesses were obtained by the image analysis of micro-section images. The flux type proved to have a significant impact on the intermetallic layer thickness. The solder paste with ROL1 caused an increase in IML thickness by up to 40% in comparison to an identical paste with ROL0 flux. Furthermore, doubling the roughness of the solder mask has increased the resulting IML thickness by 37% at HASL surface finish and by an average of 22%.

Effect of Plasma Surface Finish on Wettability and Mechanical Properties of SAC305 Solder Joints

2016 ◽  
Vol 45 (12) ◽  
pp. 6184-6191 ◽  
Author(s):  
Kyoung-Ho Kim ◽  
Junichi Koike ◽  
Jeong-Won Yoon ◽  
Sehoon Yoo
Keyword(s):  
Mechanical Properties ◽  
Surface Finish ◽  
Solder Joints ◽  
Sac305 Solder ◽  
Plasma Surface

Characterizations of Ball Impact Responses of Tin-Silver-Copper Solder Joints Doped With Nickel or Germanium

2007 ◽  
Author(s):  
Yi-Shao Lai ◽  
Jenn-Ming Song ◽  
Hsiao-Chuan Chang ◽  
Ying-Ta Chiu
Keyword(s):  
High Speed ◽  
Solder Joints ◽  
Ball Impact ◽  
Test Methodology ◽  
Surface Finishes ◽  
Reliability Of Solder Joints ◽  
Tin Silver Copper ◽  
Board Level ◽  
Immersion Tin ◽  
Board Level Reliability

The ball impact test (BIT) was developed based on the demand of a package-level measure of the board-level reliability of solder joints in the sense that it leads to brittle intermetallic fracturing, similar to that from a board-level drop test. The BIT itself stands alone as a unique and novel test methodology in characterizing strengths of solder joints under a high-speed shearing load. In this work, we present BIT results conducted at an impact velocity of 500 mm/s on Sn-4Ag-0.5Cu, Sn-1Ag-0.5Cu, Sn-1Ag-0.5Cu-0.05Ni, Sn-1.2Ag-0.5Cu-0.05Ni, and Sn-1Ag-0.5Cu-0.05Ge package-level solder joints, bonded on substrate pads of immersion tin (IT) and direct solder on pad (DSOP) surface finishes. Differences of BIT results with respect to multi-reflow are also reported.

Machine learning framework for predicting reliability of solder joints

2019 ◽  
Vol 32 (2) ◽  
pp. 82-92 ◽  
Author(s):  
Sung Yi ◽  
Robert Jones
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Failure Modes ◽  
Solder Joints ◽  
Big Data Analytics ◽  
Content Type ◽  
Learning Framework ◽  
Surface Finishes ◽  
Reliability Of Solder Joints

Purpose This paper aims to present a machine learning framework for using big data analytics to predict the reliability of solder joints. The purpose of this study is to accurately predict the reliability of solder joints by using big data analytics. Design/methodology/approach A machine learning framework for using big data analytics is proposed to predict the reliability of solder joints accurately. Findings A machine learning framework for predicting the life of solder joints accurately has been developed in this study. To validate its accuracy and efficiency, it is applied to predict the long-term reliability of lead-free Sn96.5Ag3.0Cu0.5 (SAC305) for three commonly used surface finishes such OSP, ENIG and IAg. The obtained results show that the predicted failure based on the machine learning method is much more accurate than the Weibull method. In addition, solder ball/bump joint failure modes are identified based on various solder joint failures reported in the literature. Originality/value The ability to predict thermal fatigue life accurately is extremely valuable to the industry because it saves time and cost for product development and optimization.

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