Journal of the Microelectronics and Packaging Society

Bonding wires are composed of conductive metals of Au, Ag & Cu with excellent electrical conductivities for transmitting power and signals to wafer chips. Wire metals do not provide electrical insulation, adhesion promoter and corrosion passivation. Adhesion between metal wires is extremely weak, which is responsible for wire cut failures during thermal cycling. Organic coating for electrical insulation does not satisfy bondability and manufacturability, and it is complex to apply very thin organic coating on metal wires. Automotive packages require enhanced reliability of packages under harsh conditions. LED and power packages are susceptible to wire cut failures. Contrary to conventional OCB behaviors, forming gas was not required for free air ball formation for both Ag and Pd-coated Cu wires with Al₂O₃ passivation.

Insulated wire, Adhesively-promoted wire, Passivated wire, Al₂O₃ coating, Bonding wire, Nano ceramic

The effect of the residual impurity on the prepreg surface on the wettability of encapsulant for chip on board package was analyzed with microstructure, compositions and chemical bonds using a scanning electron microscope and X-ray photoelectron spectroscopy. As a result, the contact angle of w/ residual impurity sample was measured to be 28° higher than that of w/o residual impurity sample, and the C-O bond was decreased to be 4% lower than that of w/o residual impurity sample. The surface energy of the prepreg decreased because the impurity ions, Na and F, generated by the manufacturing process and wet etching, reacted chemically with the C on the prepreg surface, forming C-F bonds and breaking the C-O bonds on the prepreg surface. Therefore, the wettability of the encapsulant was degraded because the contact angle between the encapsulant and the prepreg was increased.

Prepreg, Encapsulant, Surface energy, Wettability, Contact angle

With advances of artificial intelligence (AI) technology, the demand is increasing for high-end semiconductors in various places such as data centers. In order to improve the performance of semiconductors, reducing the pitch of patterns and increasing density of I/Os are required. For this issue, 2.5dimension(D) packaging is gaining attention as a promising solution. The core technologies used in 2.5D packaging include microbump, interposer, and bridge die. These technologies enable the implementation of a larger number of I/Os than conventional methods, enabling a large amount of information to be transmitted and received simultaneously. This paper proposes the Molded Bridge die on Substrate (MBoS) process technology, which combines molding and Redistribution Layer (RDL) processes. The proposed MBoS technology is expected to contribute to the popularization of next-generation packaging technology due to its easy adaption and wide application areas.

Molding, 2.5D Packaging, Bridge Die, Interposer

In this study, the time-dependent warpage behavior caused by the viscoelastic properties of prepreg in a printed circuit board (PCB) was analyzed by finite element method (FEM). The accurate viscoelastic properties of the prepreg were measured by stress relaxation test, which were then incorporated into constructed warpage analysis model. When the PCB was subjected to repeated thermal cycles, the warpage of the PCB was restored to its initial state when only the elastic properties of the prepreg were considered, but when the viscoelastic properties were also considered, the warpage was not restored and permanent warpage change occurred. The warpage analysis for three different types of prepreg was conducted to compare their mechanical reliability, and the results showed that materials with elastic properties dominating over viscoelastic properties experienced less warpage, resulting in better mechanical reliability.

Printed circuit board (PCB), Warpage, Prepreg, Finite element method (FEM), Viscoelastic property

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

Artificial intelligence, Cu interconnects, Corrosion, Non-destructive evaluation, Smith chart

Copper electrodeposition technology is essential for producing copper films and interconnects in the microelectronics industries including semiconductor packaging, semiconductors and secondary battery, and there are extensive efforts to control the microstructure of these films and interconnects. In this study, we investigated the influence of crystallographic orientation on the local plastic deformation of copper films for secondary batteries deformed by uniaxial tensile load. Crystallographic orientation maps of two electrodeposited copper films with different textures were measured using an electron backscatter diffraction (EBSD) system and then used as initial conditions for crystal plasticity finite element analysis to predict the local plastic deformation behavior within the films during uniaxial tension deformation. Through these processes, the changes of the local plastic deformation behavior and texture of the films were traced according to the tensile strain, and the crystal orientations leading to the inhomogeneous plastic deformation were identified.

Electrodeposited copper film, Crystallographic orientation, Plastic deformation, Electron backscatter diffraction (EBSD), Crystal plasticity finite element method

The maintenance of semiconductor equipment is crucial for the continuous growth of the semiconductor market. System management is imperative given the anticipated increase in the capacity and complexity of industrial equipment. Ensuring optimal operation of manufacturing processes is essential to maintaining a steady supply of numerous parts. Particularly, monitoring the status of substrate transfer robots, which play a central role in these processes, is crucial. Diagnosing failures of their major components is vital for preventive maintenance. Fault diagnosis methods can be broadly categorized into physics-based and data-driven approaches. This study focuses on data-driven fault diagnosis methods due to the limitations of physics-based approaches. We propose a methodology for data acquisition and preprocessing for robot fault diagnosis. Data is gathered from vibration sensors, and the data preprocessing method is applied to the vibration signals. Subsequently, the dataset is trained using Gradient Tree-based XGBoost machine learning classification algorithms. The effectiveness of the proposed model is validated through performance evaluation metrics, including accuracy, F1 score, and confusion matrix. The XGBoost classifiers achieve an accuracy of approximately 92.76% and an equivalent F1 score. ROC curves indicate exceptional performance in class discrimination, with 100% discrimination for the normal class and 98% discrimination for abnormal classes.

Transfer robot, Fault diagnosis, Vibration sensor, Data preprocessing, Machine learning

SICM (Scanning Ion Conductivity Microscopy) is a technique for measuring surface topography in an environment where electrochemical reactions occur, by detecting changes in ion conductivity as a nanopipette tip approaches the sample. This study includes an investigation of the current response curve, known as the approach curve, according to the distance between the tip and the sample. First, a simulation analysis was conducted on the approach curves. Based on the simulation results, then, several measuring experiments were conducted concurrently to analyze the difference between the simulated and measured approach curves. The simulation analysis confirms that the current squeezing effect occurs as the distance between the tip and the sample approaches half the inner radius of the tip. However, through the calculations, the decrease in current density due to the simple reduction in ion channels was found to be much smaller compared to the current squeezing effect measured through actual experiments. This suggests that ion conductivity in nano-scale narrow channels does not simply follow the Nernst-Einstein relationship based on the diffusion coefficients, but also takes into account the fluidic hydrodynamic resistance at the interface created by the tip and the sample. It is expected that SICM can be combined with SECM (Scanning Electrochemical Microscopy) to overcome the limitations of SECM through consecutive measurement of the two techniques, thereby to strengthen the analysis of electrochemical surface reactivity. This could potentially provide groundbreaking help in understanding the local catalytic reactions in electroless plating and the behaviors of organic additives in electroplating for various kinds of patterns used in semiconductor damascene processes and packaging processes.

SICM, Microscopy, UME, Electrochemistry, Electrode

With the increasing use of transparent displays and flexible devices, polymer substrates offering excellent flexibility and strength are in demand. Since polymers are sensitive to heat, precise temperature control during the process is necessary. The study proposes a temperature measurement system for the laser processing area within the polymer base, aiming to address the drawbacks of using these polymer bases in laser-based selective processing technology. It presents the possibility of optimizing the process conditions of the polymer substrate through local temperature change measurements in the laser processing area. We developed and implemented the PDPT (Photodiode-based Planck Thermometry) to measure temperature in the laser-processing area. PDPT is a non-destructive, contact-free system capable of real-time measurement of local temperature increases. We monitored the temperature fluctuations during the laser processing of the polymer substrate. The study shows that the proposed laser-based temperature measurement technology can measure real-time temperature during laser processing, facilitating optimal production conditions. Furthermore, we anticipate the application of this technology in various laser-based processes, including essential micro-laser processing and 3D printing.

Photodiode-based Planck Thermometry (PDPT), Laser-based packaging processes, Real-time temperature monitoring, High-resolution temperature measurement

Due to the miniaturization and multifunctionality of electronic devices, a surface mount technology in the form of molded interconnect devices (MID), which directly forms electrodes and circuits on the plastic injection parts and mounts components and parts on them, is being introduced to overcome the limitations in the mounting area of electronic components. However, when using plastic injection parts with low thermal stability, there are difficulties in mounting components through the conventional reflow process.
In this study, we developed a process that utilizes induction heating, which can selectively heat specific areas or materials, to melt solder and mount components without causing any thermal damage to the plastic. We designed the shape of an induction heating Cu coil that can concentrate the magnetic flux on the area to be heated, and verified the concentration of the magnetic flux and the degree of heating on the pad part through finite element method (FEM). LEDs, capacitors, resistors, and connectors were mounted on a polycarbonate substrate using induction heating to verify the mounting process, and their functionality was confirmed. We presented the applicability of a selective heating process through magnetic induction that can overcome the limitations of the reflow method.

low heat resistant material, Induction heating soldering, electronic component mounting, MID, Induction Heating Selective Bonding

The electrochemical reduction of carbon dioxide (CO₂) is gaining attention as an effective method for converting CO₂ into high-value carbon compounds. This paper reports a facile meth od for synth esizing and characterizing g-C₃N₄- modified porous Au (pAu) electrodes for electrochemical CO₂ reduction using e-beam deposition and anodization techniques. The fabricated pAu@g-C₃N₄ electrode (@ -0.9 V_RHE) demonstrated superior electrochemical performance compared to the pAu electrode. Both electrodes exhibited a Faradaic efficiency (FE) of 100% for CO production. The pAu@g-C₃N₄ electrode achieved a maximum CO production rate of 9.94 mg/s, which is up to 2.2 times higher than that of the pAu electrode. This study provides an economical and sustainable approach to addressing climate change caused by CO₂ emissions and significantly contributes to the development of electrodes for electrochemical CO₂ reduction.

Electrochemical (EC), CO₂ reduction (CO₂RR), Carbon monoxide (CO), graphitic carbon nitride (g-C₃N₄), Au catalyst, porous structure

In this study, we investigated a method of growing single crystal β-Ga₂O₃ thin films on a c-plane sapphire substrate using MOCVD. We confirmed the optimal growth conditions to increase the crystallinity of the β-Ga₂O₃ thin film and confirmed the effect of the ratio between O₂ and Ga precursors on crystal growth on the crystallinity of the thin film. The growth temperature range was 600~1100℃, and crystallinity was analyzed when the O₂/TMGa ratio was 800~6000. As a result, the highest crystallinity thin film was obtained when the molar ratio between precursors was 2400 at 1100°C. The surface of the thin film was observed with a FE-SEM and XRD ω-scan of the thin film, the FWHM was found to be 1.17° and 1.43° at the (201) and (402) diffraction peaks. The optical band gap energy obtained was 4.78 ~ 4.88 eV, and the films showed a transmittance of over 80% in the near-ultraviolet and visible light regions.

β-Ga₂O₃, MOCVD, Heteroepitaxy, Temperature, Single crystal