A comparative study of thermal fatigue life of Eutectic Sn-Bi, Hybrid Sn-Bi/SAC and SAC solder alloy BGAs

Cai, Chongyang; Xu, Jiefeng; Wang, Huayan; Park, S.B.

doi:10.1016/j.microrel.2021.114065

Cited by 40 publications

(4 citation statements)

References 9 publications

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“…Methods. In order to verify the correctness and effectiveness of the proposed network model method, finally compare the proposed convolutional network method with the traditional convolution model [40] and 2D-CNN [33], 3D-CNN [34], Multiscale-3D-CNN [41], and Hybrid SN [42] methods. In order to ensure the fairness of the experiment, the hyperparameters in all comparison networks are set the same; for example, the input data is reduced to 20 dimensions, the spatial dimension is set to 11 × 11 × 20, the epoch period is 50, and the batch size is 256.…”

Section: Comparison Of Experimental Performance Under Differentmentioning

confidence: 99%

I3D: An Improved Three-Dimensional CNN Model on Hyperspectral Remote Sensing Image Classification

Qian

2021

Security and Communication Networks

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Hyperspectral image data are widely used in real life because it contains rich spectral and spatial information. Hyperspectral image classification is to distinguish different functions based on different features. The computer performs quantitative analysis through the captured image and classifies each pixel in the image. However, the traditional deep learning-based hyperspectral image classification technology, due to insufficient spatial-spectral feature extraction, too many network layers, and complex calculations, leads to large parameters and optimizes hyperspectral images. For this reason, I proposed the I3D-CNN model. The number of classification parameters is large, and the network is complex. This method uses hyperspectral image cubes to directly extract spectral-spatial coupling features, adds depth separable convolution to 3D convolution to reextract spatial features, and extracts the parameter amount and calculation time at the same time. In addition, the model removes the pooling layer to achieve fewer parameters, smaller model scale, and easier training effects. The performance of the I3D-CNN model on the test datasets is better than other deep learning-based methods after comparison. The results show that the model still exhibits strong classification performance, reduces a large number of learning parameters, and reduces complexity. The accuracy rate, average classification accuracy rate, and kappa coefficient are all stable above 95%.

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Section: Comparison Of Experimental Performance Under Differentmentioning

confidence: 99%

I3D: An Improved Three-Dimensional CNN Model on Hyperspectral Remote Sensing Image Classification

Qian

2021

Security and Communication Networks

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“…Several works have also predicted the shape (geometry) of a BGA ball after one or several reflows using the finite element method [ 10 , 11 , 12 , 13 , 14 , 15 ] or computational fluid dynamic simulation [ 16 ]. There have also been studies examining mixed assemblies; for example, an assembly consisting of an SAC305 BGA solder ball with a printed Sn-Bi solder alloy [ 17 ] or a Cu BGA ball covered with an SAC305 solder alloy [ 18 ]. The initial collapse was evaluated after soldering; however, it is worth noting that the level of collapse with mixed assemblies, which was found to be low [ 17 , 18 ], may occur due to causes other than those studied in this work.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Temperature-Induced Ball Grid Array Collapse Observation

Sorokina,

Dušek,

Bušek

2024

Materials

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This study presents a new approach to investigating the impact of repeated reflow on the failure of ball grid array (BGA) packages. The issue with the BGA package collapse is that the repeated reflow can lead to short circuits, particularly for BGAs with a very fine pitch between leads. A novel approach was developed to measure the collapse of BGA solder balls during the melting and solidification process, enabling in situ measurements. The study focused on two types of solders: Sn63Pb37 as a reference, and the commonly used SAC305, with measurements taken at various temperatures. The BGA samples were subjected to three different heating/cooling cycles in a thermomechanical analyzer (TMA) at temperatures of 250 °C, 280 °C, and 300 °C, with a subsequent cooling down to 100 °C. The results obtained from the TMA indicated differences in the collapse behavior of both BGA solder alloys at various temperatures. Short circuits between neighboring leads (later confirmed by an X-ray analysis) were also recognizable on the TMA. The novel approach was successfully developed and applied, yielding clear insights into the behavior of solder balls during repeated reflow.

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“…[13,14] Contact printing methods, including gravure printing and screen printing, need a mask that still limits their printing resolution. [15][16][17] Therefore, non-contact printing technologies with relatively higher resolution are widely used for electronic devices. [18] But the resolution of non-contact printing technologies is usually limited by the nozzle, whose size is at the same scale of the printing resolution.…”

Section: Introductionmentioning

confidence: 99%

Electrohydrodynamic Printing of High‐Resolution Self‐Reduced Soldered Silver Nanowire Pattern for Wearable Flexible Strain Sensors

Feng

Zhang

et al. 2023

Adv Materials Technologies

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As an indispensable aspect of flexible and printed electronics, flexible strain sensors composed of silver nanowires (AgNWs) have attracted significant attention recently. However, low resolution and large wire‐wire contact resistance still impede the stability and sensitivity of AgNW‐based flexible strain sensors. Herein, self‐reduced soldered AgNW pattern is fabricated by combining the high‐resolution electrohydrodynamic (EHD) printing and joining of AgNWs. The resolution achieved by EHD printing is up to ≈20 µm. The contact resistance between AgNWs is greatly reduced by depositing Ag atoms at the AgNW junctions while EHD printing Ag ion ink on as‐prepared AgNW pattern. After self‐reduced soldering process, the sheet resistance decreases from 14.8 to 2.13 Ω sq−1. This process can be conducted under room temperature and ambient conditions and requires no external assistance from heat, light, or mechanical pressing. Furthermore, the deposited Ag atoms at the junctions remarkably improve the sensitivity (gauge factor 14.5–37.9) and stability (over 5000 stretching cycles with 25% strain). This superior sensitivity and stability occur because nano‐junctions induced by the self‐reduced soldering process significantly reduce the initial resistance and enable a robust network structure. This EHD‐based technique for nanojoining of AgNWs demonstrates its potential for flexible and wearable electronics.

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A comparative study of thermal fatigue life of Eutectic Sn-Bi, Hybrid Sn-Bi/SAC and SAC solder alloy BGAs

Cited by 40 publications

References 9 publications

I3D: An Improved Three-Dimensional CNN Model on Hyperspectral Remote Sensing Image Classification

I3D: An Improved Three-Dimensional CNN Model on Hyperspectral Remote Sensing Image Classification

A Novel Approach for Temperature-Induced Ball Grid Array Collapse Observation

Electrohydrodynamic Printing of High‐Resolution Self‐Reduced Soldered Silver Nanowire Pattern for Wearable Flexible Strain Sensors

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