Joint Reliability Research Articles

Study on microstructure and mechanical properties of femtosecond laser welding of non-optical contact quartz glass and Zr-4

Femtosecond laser welding was employed to join quartz glass and Zr-4 under non-optical contact conditions, investigating the influence of single-pulse energy (SPE) on interfacial diffusion and bonding strength. The study revealed the formation of a stable transition layer at the interface through Si and Zr diffusion, with Zr-4 extending toward the quartz glass. Effective bonding was achieved via the synergy of mechanical interlocking and chemical bonding at the interface, consistent with recent advances in glass-metal bonding. The maximum bonding strength reached 19.49 MPa, but further increases in SPE led to stress unevenness and premature fracture. These findings provide valuable insights into enhancing the reliability of dissimilar material joints and advancing their applications in the nuclear and high-precision industries.

Effects of the grain size and orientation of Cu on the formation and growth behavior of intermetallic compounds in Sn-Ag-Cu solder joints

The rapid development of semiconductor packaging technology has accelerated the applications of flip-chip bonding technology using fine-pitch micro bumps and Cu pillar bumps. These micro-bump systems are composed of metallic Cu and Sn. The properties of the Cu- and Sn-based bonding materials applied in these technologies have a significant effect on the mechanical properties and long-term reliability of micro-joints. This study focuses on the effects of the grain size and orientation of the Cu substrate on the formation and growth of intermetallic compounds (IMCs) at the Sn/Cu interface. The Cu substrate was annealed from 200 to 1000 °C to alter its grain size, which was measured via electron backscatter diffraction analysis. Sn-3.0Ag-0.5Cu (SAC) solder paste was printed onto the Cu substrate, and the Sn/Cu interfacial microstructure was observed by scanning electron microscopy and energy-dispersive X-ray spectroscopy after the reflow soldering process. A thin IMC formed on substrates with small grain sizes, whereas larger grain sizes resulted in the formation of thick and elongated IMCs. In addition, the IMC growth exhibited a specific directional preference in the (21̅1̅0) direction on substrates annealed at 1000 ℃. The effects of the Cu grain size and orientation on the interfacial reactions and growth of IMCs were compared and analyzed by observing IMCs formed at the SAC/Cu interface. Microstructural analysis revealed that controlling the Cu grain size and orientation significantly impacts the reliability of the solder joints. This study shows that the effect of grain size and orientation can be utilized to micro-solder joints, which can significantly enhance their mechanical strength and reliability.

The Intermediate Barrier Performance of Electroless Co-W-B / Ni-P Stacked Deposits Between Cu and Solder Joint

Nickel (Ni) is one of the most common surface finishing materials for solder joint and wire bonding because it can behave as the diffusion barrier for Copper (Cu) and bring excellent reliability. Electroless Ni plating has many advantages such as high productivity, good thickness uniformity, and the deposition ability for isolated patterns of printed circuit boards without supplying electrolytic power. Electroless Ni plating is widely used as the jointing material for Tin (Sn) or Sn alloy solder in printed circuit boards, lead frames, and so on. The amorphous deposits of electroless Nickel-Phosphorus (Ni-P) generate the intermetallic compounds (IMC) with solder after the reflow and the remaining Ni behaves as the barrier between Cu and solder. In this time, the P amount of Ni-P deposits generally have the impact to the growth of IMC. Electroless Ni-P with high P (high P Ni) such as 10-12 wt% has been selected to achieve both corrosion resistance and solder joint reliability. Because the growth of Sn-Ni IMC between high P Ni is faster than deposits with lower P, the target thickness of high P Ni has been set to approximately 10 µm to sustain the Ni-P layer as the barrier layer between Cu and solder during reflow. However, if the Ni-Sn IMC is repeatedly formed and dissolved by the diffusion after solder jointing, the Ni-P layer reduces and finally disappears. As a result, an additional barrier layer is desirable for higher reliability. In this study, we investigated adding electroless Cobalt-Tungsten-Boron (Co-W-B) as a new intermediate barrier between Cu and solder jointing. We evaluated the bonding strength and IMC analysis after mounting Sn-Cu-Ni-P type solder on Cu/Co-W-B/Ni-P by using different reflow profiles. Results showed that Co-W-B 0.1-0.2 µm/Ni-P 1-2 µm stacked deposits had excellent bonding strength even though the Ni-P thickness is thinner such as 1 µm. After mounting solder, a P-rich layer was generated on the Co-W-B layer in cross-sectional Transmission Electron Microscope (TEM) observation. Scanning Transmission Electron Microscope (STEM) –Energy Dispersive X-ray Spectroscopy (EDS, STEMEDS) analysis showed the P-rich layer and Co-W-B layer prevented diffusion between solder and Cu. Furthermore, even if after the thermal loading of high temperature, the bonding strength was excellent. Additionally, the cross-section analysis of STEM-EDS revealed that a thin layer composed of Ni, Co and P was formed between Co-W-B and the P-rich layer. This thin layer also might behave as the barrier for solder. In conclusion, Co-W-B / Ni-P stacked deposits exhibited excellent reliability as the additional intermediate barrier layer between Cu and solder.

Enhancing the reliability of CSP solder joints under thermal cycling conditions through particle swarm optimization of an improved BP neural network

The packaging of chip-scale (CSP) devices plays a pivotal role in enhancing the reliability of CSP under thermal cycling conditions, largely due to the intricate structure and the recurrent alterations in the actual operating environment. The objective of this study is to enhance the reliability of solder joints by optimising the structural parameters of CSP packaging in order to reduce the strain values at the solder joints. In order to enhance the design efficiency and accuracy of the computational model, the Anand model is adopted in order to define the solder joint parameters, and finite element simulations are conducted using Ansys software. This paper puts forward a novel intelligent algorithm that fuses response surface methodology with a neural network-particle swarm optimization algorithm, thereby enhancing the precision of the system. The method is capable of identifying the combination with the minimum strain value using limited data, thereby addressing the issue of insufficient generalisation ability in conventional methods. The implementation of this method into the model resulted in a minimum strain value of 4.071 × 10−3, representing a 37.6 % reduction compared to the original CSP structure. Furthermore, the optimized lifespan is approximately 3.24 times longer than that observed prior to optimization. The approach presented in this paper has the potential to significantly enhance design efficiency and increase the lifespan of components. It offers a novel perspective for optimising the structural parameters of CSP packaging.

A New Bivariate Survival Model: The Marshall-Olkin Bivariate Exponentiated Lomax Distribution with Modeling Bivariate Football Scoring Data

This paper focuses on applying the Marshall-Olkin approach to generate a new bivariate distribution. The distribution is called the bivariate exponentiated Lomax distribution, and its marginal distribution is the exponentiated Lomax distribution. Numerous attributes are examined, including the joint reliability and hazard functions, the bivariate probability density function, and its marginals. The joint probability density function and joint cumulative distribution function can be stated analytically. Different contour plots of the joint probability density function and joint reliability and hazard rate functions of the bivariate exponentiated Lomax distribution are given. The unknown parameters and reliability and hazard rate functions of the bivariate exponentiated Lomax distribution are estimated using the maximum likelihood method. Also, the Bayesian technique is applied to derive the Bayes estimators and reliability and hazard rate functions of the bivariate exponentiated Lomax distribution. In addition, maximum likelihood and Bayesian two-sample prediction are considered to predict a future observation from a future sample of the bivariate exponentiated Lomax distribution. A simulation study is presented to investigate the theoretical findings derived in this paper and to evaluate the performance of the maximum likelihood and Bayes estimates and predictors. Furthermore, the real data set used in this paper comprises the scoring times from 42 American Football League matches that took place over three consecutive independent weekends in 1986. The results of utilizing the real data set approve the practicality and flexibility of the bivariate exponentiated Lomax distribution in real-world situations, and the bivariate exponentiated Lomax distribution is suitable for modeling this bivariate data set.

Cu Pillar Electroplating Using a Synthetic Polyquaterntum Leveler and Its Coupling Effect on SAC305/Cu Solder Joint Voiding.

With the advancement of high-integration and high-density interconnection in chip manufacturing and packaging, Cu bumping technology in wafer- and panel- level packaging is developed to micrometer-sized structures and pitches to accommodate increased I/O numbers on high-end integrated circuits. Driven by this industrial demand, significant efforts have been dedicated to Cu electroplating techniques for improved pillar shape control and solder joint reliability, which substantially depend on additive formulations and electroplating parameters that regulate the growth morphology, crystal structure, and impurity incorporation in the process of electrodeposition. It is necessary to investigate the effect of an additive on Cu pillar electrodeposition, and to explore the Kirkendall voids formed during the reflowing process, which may result from the additive-induced impurity in the electrodeposited Cu pillars. In this work, a self-synthesized polyquaterntum (PQ) was made out with dual suppressor and leveler effects, and was combined with prototypical accelerator bis- (sodium sulfopropyl)-disulfide (SPS) for patterned Cu pillar electroplating. Then, Sn96.5/Ag3.0/Cu0.5 (SAC305) solder paste were screen printed on electroplated Cu pillars and undergo reflow soldering. Kirkendall voids formed at the joint interfaces were observed and quantified by SEM. Finally, XRD, and EBSD were employed to characterize the microstructure under varying conditions. The results indicate that PQ exhibits significant suppressive and levelled properties with the new structure of both leveler and suppressor. However, its effectiveness is dependent on liquid convection. PQ and SPS work synergistically, influencing the polarization effect in various convective environments. Consequently, uneven adsorption occurs on the surface of the Cu pillars, which results in more Kirkendall voids at the corners than at the center along the Cu pillar surface.

Reliability-based capacity safety factor for G20Mn5 cast steel joints

Cast steel joints have complex geometries and great load-carrying capacity, and hence their resistances are commonly determined through FE simulations. Considering the significant variability in the material mechanical properties (that in fracture strains, in particular) and the model uncertainty inevitably involved in the FE analysis, a large safety factor (γR) should be adopted for the FE simulation-based design of cast steel joints. However, the γR-values specified by the current design specifications, e.g. the Chinese standard CECS 235: 2008 in which γR = 3.0, are deemed to be overly conservative. This paper examined the structural reliability of G20Mn5 cast steel joints to provide a rational γR-value for the practical joint design. The above-mentioned uncertainty of the material and geometric properties as well as the model uncertainty related to FE simulations are evaluated, and Monte Carlo simulations were conducted on nine representative joints to obtain the statistical characteristics of cast steel joints’ ultimate resistance, allowing for both failure modes of material fracture and instability caused by large-scale yielding. FORM was adopted to calculate the reliability index β for the assumed γR-values and different loading scenarios, and the recommended values for γR under target reliability indices are proposed. For snow load-dominant and wind load-dominant load combinations, the recommended γR corresponding to β = 4.2 are 2.29 and 2.16, respectively, and the recommended γR corresponding to β = 3.7 are 2.01 and 1.90, respectively.

Reliability of BGA solder joints using nanoindentation

Reliability of BGA solder joints using nanoindentation

Interfacial microstructure evolution and mechanical characterization of brazed Al2O3 joints with Ni‒Ti interlayer: An experimental and theoretical approach

Reliable brazing joints of Al2O3 ceramics were obtained using an active Ni‒Ti interlayer under vacuum conditions. The interfacial microstructure and mechanical properties of the joints were studied. The structural, electronic, and elastic properties of the primary interfacial reaction phases were determined using first–principles calculations. After brazing at 1320 °C for 30 min, Ni2Ti4O layer and columnar AlNi2Ti formed at the interface adjacent to the Al2O3 substrate. With increasing brazing temperature between 1300 °C and 1380 °C, Ni2Ti4O layer thickened gradually, and the AlNi2Ti became increasingly longer. As brazing temperature reached 1400 °C, TiO was formed at the interface, and the Ni2Ti4O content decreased significantly; moreover, bulk AlNi2Ti and TiNi3 were distributed in the brazing seam. The highest shear strength of 129 MPa was achieved when brazed at 1350 °C for 30 min. According to the first–principles calculations, Ni2Ti4O is more readily formed than AlNi2Ti, whereas AlNi2Ti exhibits greater stability than Ni2Ti4O. Both AlNi2Ti and Ni2Ti4O possess metallic bonds, contributing to the adhesion of the filler metal to the Al2O3 substrates. The calculated modulus and Poisson’s ratio indicate that both AlNi2Ti and Ni2Ti4O exhibit ductile characteristics, which assist in relieving residual stress within the joint.

Inhibiting the formation of interfacial voids in Cu/In/Cu microbump via Zn doping into Cu substrate

To address warpage issues in 3D-IC, low temperature soldering technology such as Cu/In bonding has been developed in recent years. However, the formation of Kirkendall voids at the original Cu/In interface would lead to degradation of joint reliability. By adding Zn, the diffusional flux of Cu was inhibited, and the numbers of interfacial voids larger than 50 nm decreased substantially by 66 % at top interface and 58 % at bottom interface, respectively. In this study, Cu–15Zn/In/Cu system was investigated and could be regarded as a promising option for advanced electronic packaging in the future.

Effect of Preheating Parameters on Extrusion Welding of High-Density Polyethylene Materials.

High-density polyethylene (HDPE) has emerged as a promising alternative to fiber-reinforced plastic (FRP) for small vessel manufacturing due to its durability, chemical resistance, lightweight properties, and recyclability. However, while thermoplastic polymers like HDPE have been extensively used in gas and water pipelines, their application in large, complex marine structures remains underexplored, particularly in terms of joining methods. Existing techniques, such as ultrasonic welding, laser welding, and friction stir welding, are unsuitable for large-scale HDPE components, where extrusion welding is more viable. This study focuses on evaluating the impact of key process parameters, such as the preheating temperature, hot air movement speed, and nozzle distance, on the welding performance of HDPE. By analyzing the influence of these variables on heat distribution during the extrusion welding process, we aim to conduct basic research to derive optimal conditions for achieving strong and reliable joints. The results highlight the critical importance of a uniform temperature distribution in preventing defects such as excessive melting or thermal degradation, which could compromise weld integrity. This research provides valuable insights into improving HDPE joining techniques, contributing to its broader adoption in the marine and manufacturing industries.

Container migration for edge computing in industrial Internet with joint latency reduction and reliability enhancement

Edge computing has emerged as a prominent trend in the field of information technology, offering flexible and robust resources for the industrial Internet. How to migrate container accurately is crucial for edge computing in the industrial Internet, as it plays a vital role in enhancing service response speed and safeguarding uninterrupted continuity of production operations. In this paper, we explore the problem of container migration in edge computing within the industrial Internet, aiming to reduce latency and enhance reliability. We establish a two-objective optimization model to comprehensively capture the container migration problem and formulate it as a constrained optimization model. The formulated model provides a systematic framework that effectively balances the trade-off between reducing latency and enhancing reliability. To tackle the migration strategy derived from the optimization model, we propose a migration algorithm based on the improved binary whale optimization algorithm. Our migration algorithm incorporates the adaptive probability and adaptive position weight within the hunting and searching operations, effectively enhancing the search efficiency during the solving process. The experimental results demonstrate the effectiveness of the established model in reducing the objective value, while the proposed migration algorithm surpasses existing algorithms by achieving an average reduction of at least 15.59% in the objective value.

Electrochemical Migration Study on Sn-58Bi Lead-Free Solder Alloy Under Dust Contamination.

With the development of electronic packaging technology toward miniaturization, integration, and high reliability, the diameter and pitch of solder joints continue to shrink. Adjacent solder joints are highly susceptible to electrochemical migration (ECM) due to the synergistic effects of high-density electric fields, water vapor, and contaminants. Dust has become one of the non-negligible causal factors in ECM studies due to air pollution. In this study, 0.2 mM/L NaCl and Na2SO4 solutions were used to simulate soluble salt in dust, and the failure mechanism of an Sn-58Bi solder ECM in the soluble salt in dust was analyzed by a water-droplet experimental method. It was shown that the mean failure time of the ECM of an Sn-58Bi solder in an NaCl solution (53 s) was longer than that in an Na2SO4 solution (32 s) due to the difference in the anodic dissolution characteristics in the two soluble salt solutions. XPS analysis revealed that the dendrites produced by the ECM process were mainly composed of Sn, SnO, and SnO2, and there were precipitation products-Sn(OH)2 and Na2SO4-attached to the dendrites. The corrosion potential in the NaCl solution (-0.351 V) was higher than that in the Na2SO4 solution (-0.360 V), as shown by a polarization test, indicating that the Sn-58Bi solder had better corrosion resistance in the NaCl solution. Therefore, an Sn-58Bi solder has better resistance to electrochemical migration in an NaCl solution compared to an Na2SO4 solution.

Understanding the deformation creep and role of intermetallic compound-microstructure in Sn-Ag-Cu solders

Tin-based alloys are commonly used in lead-free solder joints in electronic interconnection applications, where creep can limit joint reliability. In this work, directionally solidified bulk solder alloys of different compositions (pure tin, SAC105 and SAC305) are mechanically tested under a constant load for each composition at room temperature to understand mechanical creep performance and quantify the role of different content of Ag3Sn and Cu6Sn5 intermetallic compounds (IMCs) in terms of secondary creep strain rate, microstructural evolution, and total amount of accumulated strain. In this work, microstructures are fabricated using directional solidification to promote a systematic variation in IMC sizes, shapes, and distributions within similar crystal orientations of the primary β-Sn matrix. Analysis of creep data indicates that secondary creep is dominated by obstacle-controlled dislocation motion. This is further confirmed by electron backscatter diffraction (EBSD) analysis, which reveals that the formation of subgrains and internal structure, correlating to the initial microstructure of the sample, i.e. changes in secondary dendrite arm spacing (λ2) and eutectic intermetallic spacing (λe). The experimental observations are supported further by crystal plasticity simulations that explicitly model the presence of IMCs within the Sn-based samples and show the dependence of the secondary creep rate upon the IMC content, and therefore be beneficial for the possible future composition design in solders.

Estimation of Lower Limb Joint Angles Using sEMG Signals and RGB-D Camera.

Estimating human joint angles is a crucial task in motion analysis, gesture recognition, and motion intention prediction. This paper presents a novel model-based approach for generating reliable and accurate human joint angle estimation using a dual-branch network. The proposed network leverages combined features derived from encoded sEMG signals and RGB-D image data. To ensure the accuracy and reliability of the estimation algorithm, the proposed network employs a convolutional autoencoder to generate a high-level compression of sEMG features aimed at motion prediction. Considering the variability in the distribution of sEMG signals, the proposed network introduces a vision-based joint regression network to maintain the stability of combined features. Taking into account latency, occlusion, and shading issues with vision data acquisition, the feature fusion network utilizes high-frequency sEMG features as weights for specific features extracted from image data. The proposed method achieves effective human body joint angle estimation for motion analysis and motion intention prediction by mitigating the effects of non-stationary sEMG signals.

Additive technologies for improving the strength and deformation characteristics of plastic washer joints of wooden structures

Introduction. Modern wooden structures are mostly connected by mechanical working joints. To increase the reliability of nodal joints, various kinds of washers can be pressed, inserted, or glued into the wood of the elements, thus ensuring the transmission of forces from one element to another. Joints on glued washers can transfer significant forces on a relatively small area of mutual contact, which is due to their high loadbearing capacity. Thus, the gluing of steel washers in places of increased stress concentration during force transfer ensures a significant redistribution of buckling/cracking stresses over a larger area of the connected parts. However, steel washers are highly corrosive, so additional measures are required to protect metal parts from corrosion or to replace the material with the composites. The results of full-scale tests of the samples with glued-in plastic washers are used to consider the ways of increasing the strength and deformation characteristics of the plastic washer material by applying additive technologies.Aim. To increase the load-bearing capacity of the wooden structure joints by increasing the strength and deformation characteristics of the glued washer material.Materials and methods. A method for full-scale tests of wooden specimens with glued fiberglass washers is presented. The wooden elements are made of second grade pine, while the washers are of REC Formax and REC Friction plastics. The test was performed in compression along the fibers, with control of vertical shear deformations. The methods of increasing the strength and deformation characteristics of plastic washers by using additive technologies are considered.Results. Using the data of full-scale tests the diagrams of sample deformations on glued plastic washers are drawn, the obtained results are analyzed. The sufficiently high plasticity of washer materials is established. The ways for increasing the strength and deformation characteristics of plastic washers, particularly by reinforcing the plastic washers is suggested.Conclusions. In order to increase the load-bearing capacity of the joints on the glued fiberglass washers, the reinforcement of plastic using additive CFC printing technologies and the use of different reinforcing fiber materials is adopted.

Metal–Polymer Joining by Additive Manufacturing: Effect of Printing Parameters and Interlocking Design

Additive manufacturing has a strong potential to produce sound metal–polymer joints using controlled polymer deposition on a metallic substrate. In this way, this study aimed to explore the morphological and mechanical properties of metal–polymer joints produced through material-extrusion-based AM using a pin-based macro-mechanical interlocking mechanism. Joints were fabricated with polylactic acid deposited onto a heated aluminium alloy substrate to form the connection. The optimisation process was focused on improving the printing parameters and pin geometries to reduce voids and enhance joint integrity. The results indicate that optimised samples exhibit superior mechanical resistance, achieving a maximum load improvement with an overall strength increase of 368.97% compared to non-optimised joints. A combined pin geometry (50% cylindrical, 50% conical) was found to be the most effective. Morphological analysis confirmed uniform polymer deposition, ensuring reliable joint performance. These findings underscore the critical role of geometric optimisation in enhancing the strength and durability of metal–polymer joints in AM applications.

Application of Machine Learning Methods to Analyze the Dependence of Vibration Acceleration Signals on the Tightening Forces of Bolted Connections

The article is devoted to the application of machine learning methods for the analysis of vibration acceleration signals in bolted joints that occur under impact. The relevance of the work is due to the need to ensure the reliability and operability of bolted joints under loads. One of the promising areas of non-destructive testing is the analysis of the characteristics of vibration acceleration signals that change with changes in the state of structures, for example, with an increase in the tightening torque. This allows for the timely detection of possible defects and the prevention of emergency situations, ensuring the safety and durability of structures. The vibration acceleration signals under impact action on a bolted joint were analyzed. After calculating the signal characteristics, data sets were formed, including the values of tightening torques and the corresponding calculated signal characteristics, a search for a correlation between the tightening torque of bolted joints and the obtained set of vibration signal parameters was carried out. The frequency spectrum of signals, the Higuchi fractal dimension, detrended fluctuations, spectral power density and position of signal peaks were calculated. Machine learning models such as decision trees, the nearest neighbor method, the k-means method and neural networks were used for the analysis. For these methods, an optimal set of parameters correlating with the tightening torque was searched for. The main results show that machine learning methods are effective in classifying signals and finding correlations with stress state parameters. They allow us to detect the relationship between a set of signal characteristics and tightening torque, which opens up opportunities for more accurate and reliable monitoring of the condition of bolted connections. This should help to increase their operational reliability and durability, as well as reduce the likelihood of failures and accidents. The use of such methods can improve the quality of monitoring and diagnostics of bolted connections.

The Effect of Bi Addition on the Electromigration Properties of Sn-3.0Ag-0.5Cu Lead-Free Solder

As electronic packaging technology advances towards miniaturization and integration, the issue of electromigration (EM) in lead-free solder joints has become a significant factor affecting solder joint reliability. In this study, a Sn-3.0Ag-0.5Cu (SAC305) alloy was used as the base, and different Bi content alloys, SAC305-xBi (x = 0, 0.5, 0.75, 1.0 wt.%), were prepared for tensile strength, hardness, and wetting tests. Copper wire was used to prepare EM test samples, which were subjected to EM tests at a current density of approximately 0.6 × 104 A/cm2 for varying durations. The interface microstructure of the SAC305-xBi alloys after the EM test was observed using an optical microscope. The results showed that the 0.5 wt.% Bi alloy exhibited the highest ultimate tensile strength and microhardness, improving by 33.3% and 11.8% compared to SAC305, respectively, with similar fracture strain. This alloy also displayed enhanced wettability. EM tests revealed the formation of Cu6Sn5 and Cu3Sn intermetallic compounds (IMCs) at both the cathode and anode interfaces of the solder alloy. The addition of Bi inhibited the diffusion rate of Sn in Cu6Sn5, resulting in similar total IMC thickness at the anode interface across different Bi contents under the same test conditions. However, the total IMC thickness at the cathode interface decreased and stabilized with increasing EM time, with the SAC305-0.75Bi alloy demonstrating the best resistance to EM.

Estimation of solder joint reliability in electronic packaging: Insights from finite element analysis on intermetallic compounds and voids

Estimation of solder joint reliability in electronic packaging: Insights from finite element analysis on intermetallic compounds and voids