Panel-level packaging is an emerging solution for realizing More than Moore architectures with high productivity. CMP is a key process for forming fine, accurate 3D structures by providing a planar surface. This paper discusses the key considerations for implanting CMP in panel-level packaging. Pre-investment considerations are summarized in terms of goals, capacity/throughput and cost. Technical considerations for production are also addressed, including process, slurry and equipment to enhance productivity and quality.

Pad conditioning restores degraded pad surfaces after wafer polishing in chemical mechanical planarization (CMP) using diamond-embedded conditioner discs. However, conditioning also causes pad cutting, thickness reduction, and profile deformation. While previous studies mainly focused on reducing pad cut rate (PCR) and improving profile uniformity, the fundamental cutting mechanism between conditioner cutting edges and the pad remains unclear. This study investigates the cutting mechanism using CVD conditioner discs with different cutting edge densities under varying conditioning loads to control contact area and load distribution. PCR and pad profile analyses revealed that cutting behavior is primarily governed by the load applied to individual cutting edges. Higher localized loads increased the contribution of cutting to overall material removal. In the pad edge region, where the conditioner partially overhangs the pad, altered contact geometry caused a transition in cutting mode. In this region, the number of active cutting edges had a greater influence than the load per edge. These findings clarify the cutting interactions between CVD conditioner edges and pad surfaces during conditioning and provide a physical foundation for optimizing conditioning parameters to improve pad management in CMP processes.

In this study, a spectrophotometry-based method was developed to quantitatively assess PVA brush contamination during post-CMP cleaning without inducing physical damage. The approach measures changes in the absorbance of deionized water after contact with the brush, directly indicating the amount of residual slurry particles released during cleaning. To establish a quantitative framework, slurry-diluted samples were prepared at controlled concentrations, and their absorbance was used to construct a calibration curve. This calibration exhibited excellent linearity (R-2 = 99.9 %), enabling precise correlation between absorbance and particle concentration across a wide dilution range. Using this method, brush contamination levels were evaluated across four strategies. Inner DIW injection reduced particle concentration by similar to 90 % within 3 min, while ultrasonic cleaning achieved near-complete removal in seconds. Squeeze bar cleaning further removed surface-bound particles through direct mechanical contact. In contrast to these post-contact methods, buffing served as a pre-removal approach by eliminating particles from the wafer surface prior to brush contact. This effectively reduced particle accumulation on the brush and minimized recontamination risks during subsequent cleaning. Overall, this non-destructive and rapid method offers a practical tool for monitoring brush performance and evaluating cleaning strategies, supporting process optimization, brush lifetime extension, and reduced cleaning costs in semiconductor manufacturing.

Pad conditioning is a key process for maintaining a stable material removal rate (MRR) in chemical mechanical polishing (CMP) by regenerating the microtexture of degraded polishing pad surfaces. However, the complex and nonlinear relationship between pad surface microtexture evolution and MRR keeps pad conditioning dependent on empirical approaches. Therefore, this study quantitatively investigates the spatiotemporal evolution of surface texture throughout the pad lifecycle and its impact on MRR, using a composite roughness parameter (Rq/Rp) that directly correlates with the material removal function. The results revealed that once sufficient pad conditioning aggressiveness was ensured, the pad reached a steady state characterized by uniform surface texture across the entire radius. Subsequently, both the texture and MRR remained constant even with increases in pad conditioning downforce and time. Notably, the decoupling behavior of Rp observed within the Rq/Rp convergence regime implies that independent control of asperity height is achievable without compromising the MRR. Furthermore, long-term pad conditioning experiments demonstrated that although the pad cut rate exhibited up to a sixfold difference depending on the pad conditioning disc type, the terminal surface texture converged to the same steady state response governed by intrinsic pad properties. This paper establishes quantitative guidelines for the conditioning endpoint and provides new insights into polishing pad surface microtexture control.

This study investigates the correlation between structured surface pad (SSP) design parameters and material removal rate (MRR) in chemical mechanical polishing (CMP). A series of designed SSPs with varying unit figure (UF) size, density, and shape were fabricated to analyze their influence on polishing performance. Taguchi analysis identified UF size as the most influential factor on MRR, followed by density and shape. In addition, real contact area (RCA) and real contact length (RCL) were quantitatively measured using optical microscopy and binary image processing under controlled compression conditions, allowing for comparison between designed and actual contact characteristics. The results reveal that MRR increases with designed contact length (DCL), with its effect modulated by designed contact area (DCA), and that RCA and RCL exhibit a complex, nonlinear relationship with MRR. Based on these findings, the study provides guidance for structured surface pad design by quantitatively linking design parameters to actual contact characteristics and polishing outcomes.

Chemical Mechanical Polishing (CMP) is the most sophisticated planarization technique among finishing processes in precision engineering and is an essential technology in semiconductor manufacturing. Although CMP is used in the fabrication of nearly all semiconductors, predicting CMP results remains difficult due to the complexity of process parameters. Traditionally, the material removal rate (MRR) in CMP has been predicted based on engineers’ experience or mathematical models, yet accurate prediction of CMP results continues to be a major challenge in the field. With the recent advancement of artificial intelligence (AI) technologies, studies on predicting CMP results and optimizing CMP processes using AI have been actively conducted. To effectively utilize AI in CMP, high-quality and reliable data are required not only from CMP machines but also from consumables. This study reviews the current state of AI-based CMP research and the development status of CMP pads and PVA brushes aimed at enabling more predictable CMP processes. In addition, this paper introduces potential application areas in which AI-based CMP technologies and consumable innovations should be applied in the future.

Polyvinyl acetal (PVA) brush is commonly used to remove residual particles from wafer surfaces in post-CMP cleaning. However, their porous structure often causes cross contamination by re-depositing particles removed. In order to solve this issue, authors propose a micropatterned (MP) pad buffing process as a precleaning step to reduce the burden on the PVA brush. The MP pad's structured surface suppresses particle penetration and enables easier removal. We investigated key design parameters-Designed Contact Area (DCA), Designed Contact Length (DCL), and pattern size -using nine MP pads. A DCA of 15 % consistently achieved the highest particle removal efficiency (PRE), while 25 % DCA showed the lowest due to particle trapping and reduced contact pressure. In order to investigate the cause, we compared two pads with identical DCA: the Basic Figure (BF) design showed 68 % higher PRE than the Repetitive Pattern Figure (RPF), indicating the importance of pattern spacing for particle displacement. Furthermore, adding grooves to the high-DCA pad significantly improved particle sliding, increasing PRE by over six fold within 10 s. These results highlight that both detachment and displacement of particles are essential for effective cleaning. MP pad buffing shows a strong potential as a complementary step to enhance post-CMP cleaning and reduce PVA brush contamination in semiconductor manufacturing.

The surface texture of the polishing pad used in chemical mechanical polishing (CMP) governs the contact characteristics during material removal. However, quantifying this texture is challenging because of the porous structural characteristics and viscoelastic behavior of polyurethane polishing pads. In this paper, we propose a novel contact characterization parameter that effectively explains material removal by combining it with the polishing pad surface roughness parameter. Experiments were conducted on three types of pads with different surface microstructures, and various combinations of surface roughness parameters were explored using an exhaustive search method based on the coefficient of determination (R2). A two-dimensional parameter derived as the optimal combination of the root mean square height (Rq) and maximum peak height (Rp) achieved a maximum accuracy of 94.54 % in explaining variations in the material removal rate. This combined parameter demonstrated enhanced explanatory power over single parameters across diverse pad surface conditions and ensured consistently high R2 values without overfitting, even when compared with higher-dimensional combinations. The proposed parameter, representing the relative peak prominence of the overall roughness, enhances our understanding of material removal mechanisms and provides new insights into the contact behavior of surface degradation during continuous wear processes.

Growing demand for high-performance system semiconductors has highlighted the importance of hybrid bonding, where precise control of copper dishing is essential. This requirement reinforces the role of chemical mechanical planarization (CMP). Many studies have sought to control dishing by modifying slurry chemistry or adjusting mechanical parameters, but these approaches have not been sufficient. This study addresses the overlooked effect of process temperature and demonstrates its role in integrating both chemical and mechanical behaviors in CMP. Removal rates of Cu, Ta, and SiO2 films were evaluated through blanket wafer experiments, and all exhibited Arrhenius-type behavior as a function of temperature and activation energy. The results showed that maintaining the process temperature at 30 °C balanced selectivity and minimized dishing on patterned wafers. To enable precise temperature control, a vortex-tube-based pad cooling system was developed. Without temperature control, dishing increased by 12 nm in the 100 µm pattern and 16 nm in the 50 µm pattern. With temperature control, dishing was reduced to 4 nm and below 1 nm, respectively. These results demonstrate that process temperature is a key parameter for controlling selectivity and ensuring precise dishing control, which is critical to meeting the requirements of hybrid bonding.

Chemical Mechanical Planarization (CMP) is the most well-known process for global planarization of wafer surfaces. The importance of interposers has been growing due to ultra-micronization and densification of semiconductors. Through-Glass-Via used in interposers has over-deposited copper layer after via filling. This copper bulk layer needs to be planarized by CMP for post-processing. At the heterogeneous material interface, defects such as dishing occur due to different material removal selectivities. In addition, the chemical reaction of copper with chemical additives is very sensitive to temperature. Therefore, temperature is an essential consideration for an efficient CMP process. In this study, we compared the effect of slurry additive properties that change with temperature on material removal. For the BTA-based slurry, the initial dishing at high temperature was 95 nm and increased by 25 nm per minute. It shows an increase of more than twice compared to the results at low temperatures. Conversely, for TTA-based slurry used in this study, the initial dishing at high temperature was 70 nm and increased by 15 nm per minute. It shows decrease of more than twice compared to the results at low temperatures. Therefore, we aim to achieve low dishing by utilizing the increasing process temperatures, on the contrary.

We investigated the impact of the designed contact area (DCA) and designed contact length (DCL) on material removal rates (MRR) when using a pad with a structured surface in chemical mechanical polishing. The structure of the structured surface pad (SSP) was precisely defined, and an examination was conducted to assess the influence of variations in the shape, size, and spacing of the unit figure (UF) on the MRR. The results revealed that maintaining the DCA constant while altering the UF shape to extend the DCL led to a 203% increase in the MRR. Furthermore, modifications in the UF size enhanced the MRR by approximately 630%. The relationship between the DCL and MRR was dependent on the DCA. The characteristics of the SSP, particularly the concentrated pressure and involvement of slurry particles at the edges of the contact area, indicated that an increase in the DCL could augment the active slurry particles. This study offers valuable insights into the pad figure structure, simultaneously advancing our understanding of the pad surface topography and its influence on material removal. By focusing on both structural engineering and practical applications, this study paves the way for future research and enables further exploration in this field.

Chemical mechanical planarization (CMP) reduces film thickness, eliminates step height, and achieves high levels of planarity in semiconductor manufacturing. However, research into its mechanisms is still in progress, and there are many issues to be resolved. To solve problems in CMP, it is necessary to understand the contact phenomenon that occurs at the pad–wafer interface, especially pad asperity. Moreover, understanding the non-uniform distribution of pad asperity, such as height and radius, is essential for predicting the material removal rate (MRR). In this study, based on the existing Greenwood–Williamson (GW) theory and probability density function (PDF), a modified mathematical model that includes changes in asperity distribution was developed and validated experimentally. The contact model proposed in this study included functions that calculated the time-dependent height and radius wear of the pad asperities. Specifically, the experimentally obtained values were compared with the values obtained by the model, and the comparison results were analyzed. Thereby, it was found that the contact model and MRR model considering the change in asperity wear and distribution due to CMP proposed in this study are in better agreement with the experimental results than the existing model, which shows that the MRR can be predicted by a mathematical model using the change in asperity distribution.

Chemical mechanical planarization (CMP) is an essential polishing process in semiconductor manufacturing. Advances in memory technology, including increased capacity and performance, have increased the importance of electronic packaging. In heterogeneous integration, the interposer acts as an important intermediary between the logic die and the substrate, solving numerous I/O bump problems in high-bandwidth memory (HBM) and logic chips. Traditionally, board-to-memory connections were made through wire bonding, which required additional space for wire connections and introduced latency due to extended signal transmission paths. A through-type approach has emerged as a solution that can significantly reduce waiting time and installation space by improving space efficiency and enabling vertical connections without extending wiring. Due to these new approaches, the importance of CMP is reemerging. Implementation of this important process requires precise control of the CMP dishing/protrusion of bonding surfaces. Improper selection of Cu pad dishing/protrusion can cause problems such as increased RC delay time and signal short circuit in the wiring. In this paper, we proposed a strategy to control dishing using CMP, especially for Through-glass-via (TGV).

Chemical mechanical planarization (CMP) stands as a critical process in semiconductor manufacturing, necessitating precise prediction of material removal rate (MRR) to achieve optimal global planarization of material surface step heights. A notable hurdle in MRR prediction lies in the nonlinear pad-wafer interaction stemming from variations in the polishing pad surface. Despite numerous extant studies examining the asperity of the pad surface and the wafer-pad contact, aspects such as slurry lubrication and micro-topographical structure of the pad surface remain unaddressed. This study firstly proposes a deep ensemble learning-based approach for MRR prediction, leveraging the intricate interactions between the overall features of the pad surface and the polishing pressure. We experimentally generated diverse pad surfaces by controlling the process variables governing pad surface topography. The Multi-TabNet model, constructed by independently training multiple TabNet instances with distinct initialization and hyperparameters, furnishes a framework for MRR prediction across a broad spectrum of pad surface features, encompassing pores and cores. The results demonstrate a root mean square error of 80 & Aring;/min, with the error margin reduced by up to 70 % compared to predictions utilizing a single parameter of the pad surface. Furthermore, it exhibits an error improvement exceeding 17 % relative to the existing method solely considering asperity. This study not only imparts insights for addressing MRR variations contingent on pad condition but also facilitates dependable material removal even on variable pad surfaces due to conditioner wear.

Chemical mechanical polishing (CMP) is a global planarization process that effectively reduces the step height of patterns. Conventional mathematical models for predicting step height reduction in oxide CMP have been successful; however, a relatively large error is obtained when applied to copper CMP because of the effects of chemical factors on copper removal rate. This study focuses on temperature as a parameter and develops a modified semi-empirical model that considers its effects. The temperature function was obtained using experiments that measured the copper etching and removal amounts according to the temperature. The developed copper model had an error rate of less than 10 %, whereas the oxide model had an error rate of approximately 30 %, indicating that the model with temperature consideration is more effective in predicting copper CMP results.

In general, the shape of the polished pattern is not flat but has a rounded curved profile. Unlike micro-patterns that have similar scales to pad asperities, macro-patterns have a very large scale compared to asperities, so bulk deformation must also be considered. To derive the pad bulk deformation, real contact area (RCA) measurements were performed in this study. Based on the preceding contact model, a semi-empirical model for RCA and bulk deformation was derived. After including the constructed pad bulk deformation function in the existing Greenwood–Williamson model, a new model that can derive the material removal rate profile according to the position in the pattern was presented. Unlike the general upper and lower removal rate behavior, this model shows a unique behavior. At the beginning of polishing, the edge shows a higher removal rate than the center, but after a specific step height, the center has a higher removal rate due to the curved shape. Analysis was performed for comparison between the proposed model equation and the experimental value. When the polishing profile in the 10 mm pattern was compared with the previous model and the proposed model, respectively, the existing model did not predict the removal rate distribution according to the position in the pattern. However, this model has the advantage of predicting both over-polishing at the edge of the pattern and high removal rate at the bottom. In addition, it was confirmed through simulation that the 4 mm and 2 mm patterns had excellent matching properties.

Chemical Mechanical Planarization (CMP) is an essential process for device integration and planarization in a semiconductor manufacturing process. The most critical function in the CMP process, is to predict and cover the geometrical characteristics of various sizes and densities, of patterned wafers for local and global planarization. To achieve the wafer-level and die-level planarization, it is necessary to understand the contact mechanism between the CMP pads and the macro-scale patterns. In the macro-scale pattern, pad deformation is divided into two layers: an asperity layer and a bulk pad layer. Through bulk pad deformation, asperity contact distribution within the pattern is predicted. In this paper, the distribution of asperity contact according to the pattern geometrical characteristics was analyzed, through large-area real contact area (RCA) measurement. Bulk pad deformation was predicted by analyzing RCA distribution according to pattern geometry such as pattern size and density, pattern shape and step height according to the polishing time, and applied pressure. Additionally, through the distribution of the contact area and the number of contact points, the rounding phenomenon and planarization characteristics in the pattern CMP were predicted.

Most of the consumables used in the CMP (Chemical Mechanical Planarization) process are discarded because it is difficult to reuse them. Slurry accounts for most of the consumables, so research is being conducted to reduce the amount of slurry used. A previous study explains that when the same amount of slurry is injected, the material removal rate is improved when the slurry is injected wide and thin instead of the tube nozzle, which is the conventional slurry injection method. However, there was no change in the injection method due to the problems of the injection method suggested in previous studies and the lack of follow-up studies. Thus, in this paper, an injection method through an ultrasonic spray nozzle is proposed to improve the problems of the injection method proposed in previous studies. Additionally, it is intended to calculate the slurry film thickness according to the spraying range and to explain the effect of the film thickness on the material removal rate.

This study focused on the damaged layer of silicon carbide produced during polishing. For the experiment, 2-inch single-crystal 4H-SiC was used. In order to analyze the damaged layer, microscope methods such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM) could be used. However, this study used nondestructive X-ray diffraction (XRD). The surface roughness value and surface image of the material before and after were confirmed using atomic force microscopy, and the full width at half maximum (FWHM) was measured using XRD. After mechanical polishing (MP), the depth of the damaged layer was 400 nm, and the corresponding FWHM value was 0.01711°. After 100 s of chemical mechanical polishing (CMP), the depth of the damaged layer was 69 nm and the corresponding FWHM value was 0.00444°. After 120 s of CMP, the depth of the damaged layer was 37 nm and the corresponding FWHM value was 0.00394°. The relationship between the surface roughness value and the FWHM was confirmed by comparing the values before and after each process. Furthermore, the SEM and TEM images enabled confirmation of the relationship between the damaged layer depth and the FWHM.