Chemical Mechanical Planarization Research Articles

Synergetic Effect of Chemical Components in a Tungsten CMP Slurry and the Evolution of Tungsten Surface Species

Abstract A novel slurry containing 50 ppm Fe3+, 2 wt.% H2O2, 75 ppm oxalic acid, and abrasive nano-silica particles were utilized in a W chemical mechanical planarization process. Using this slurry, a W material removal rate of 710 Å/min and surface roughness of 1 nm were achieved. According to X-ray photoelectron spectroscopy data, surface W was first transformed to WO2 via its dissolution in H2O2, and then Fe3+ ions serving as a catalyst promoted the conversion of tungsten to WO3 through the WO2 intermediate in the presence of H2O2. Oxalic acid was added to coordinate with H2O2 and thus improve the slurry stability through a “wrapping” mechanism without decreasing the W material removal rate. Scanning electron microscopy and atomic force microscopy observations revealed that the W surface morphology changed first from coarse elongated grains to a discontinuous structure after the uneven oxidation by H2O2 and then to a wrinkled soft surface by Fe3+ and H2O2. Finally, it was ground with abrasive nano-silica particles to achieve a high degree of flatness.

Synergetic Effect of Chemical Components in a Tungsten CMP Slurry and the Evolution of Tungsten Surface Species

Abstract A novel slurry containing 50 ppm Fe3+, 2 wt.% H2O2, 75 ppm oxalic acid, and abrasive nano-silica particles were utilized in a W chemical mechanical planarization process. Using this slurry, a W material removal rate of 710 Å/min and surface roughness of 1 nm were achieved. According to X-ray photoelectron spectroscopy data, surface W was first transformed to WO2 via its dissolution in H2O2, and then Fe3+ ions serving as a catalyst promoted the conversion of tungsten to WO3 through the WO2 intermediate in the presence of H2O2. Oxalic acid was added to coordinate with H2O2 and thus improve the slurry stability through a “wrapping” mechanism without decreasing the W material removal rate. Scanning electron microscopy and atomic force microscopy observations revealed that the W surface morphology changed first from coarse elongated grains to a discontinuous structure after the uneven oxidation by H2O2 and then to a wrinkled soft surface by Fe3+ and H2O2. Finally, it was ground with abrasive nano-silica particles to achieve a high degree of flatness.

Molecular interactions in Copper chemical mechanical planarization: A Phenomenological study

Molecular interactions in Copper chemical mechanical planarization: A Phenomenological study

An eddy current sensor for end-point detection in chemical mechanical planarization using composition signal filtration and a digital potentiometer

End-point detection (EPD) is important for controlling the chemical mechanical polishing process to prevent underpolishing and overpolishing. One EPD method using the relative current density on a Cu wafer involves an eddy current, which has advantages of noncontact and a fast response speed. However, the eddy current method has a large mean error at a low relative current density. To overcome the disadvantage, composition signal filtration uses a high mean error and long delay time using a moving average and 1-D Kalman filtration. After applying composition filtration, the mean error improved by approximately 94.7 %. Still, it is difficult to measure a thickness of 4000 Å or less with existing systems. A digital potentiometer was developed that changed the resistance in real time and improved the detection range. The step number for changing the resistance was 120 steps in the resistance range of 100–5000 Ω at approximately 40 Ω/step. When a digital potentiometer was applied, the EPD detection range improved by 85.8 % over the existing system. In other words, the developed system could measure a Cu wafer thickness of 586 Å.

Comparative first-principles analysis of crystalline versus amorphous CeO2 particles: implications for chemical mechanical planarization

Comparative first-principles analysis of crystalline versus amorphous CeO2 particles: implications for chemical mechanical planarization

Efficient nanoscale characterization of wafer surfaces using intelligent sampling and Bayesian optimization

The geometrical attributes of a wafer, such as thickness, uniformity, and local curvature, serve as eminent determinants of its quality. Therefore, measurements that are both rapid and accurate are paramount as multi-stage fabrication processes hinge on them to ensure high product reliability, proper process control, and maximum efficiency. The manual wafer profiling measurement approach in use today is, unfortunately, a time-consuming process. This creates a need for fast and prompt analysis of wafer attributes. This research thus proposes an iterative sampling method that boasts reducing the number of samplings down to a minimum without the need to discard a sufficient level of accuracy for the purpose of reliable attribute estimation. Subsequently, we suggest a series of methods to improve the monitoring and evaluation of the surface topography, all within the context of ultra-precision/nanoscale manufacturing processes, such as ultra-precision machining (UPM) and chemical–mechanical planarization (CMP). For the purpose of both real-time and exception-based detection of anomalies in the UPM process, we constructed a process-machine interaction (PMI) model with Bayesian learning, which amalgamates the received data across heterogeneous sensors such as force, vibration, and acoustic emission in situ. Similarly, the CMP process is quantitatively characterized by a multi-scaled multilayer nonlinear decomposition model with predictive capabilities. This model helps understand the physio-mechanical phenomena underlying both CMP and the UPM processes and describe and predict the nonlinear interactions, as evidenced by the experimentally collected vibration signal patterns.

Development of rigid polishing materials for use in microelectronics

The paper presents the results of development of conditions for obtaining hard polishing materials based on polyetherurethane solutions for chemical-mechanical planarization of semiconductor silicon wafers.

Deep ensemble learning for material removal rate prediction in chemical mechanical planarization with pad surface topography

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 Å/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.

Recovery and reuse of magnetic silica-coated iron oxide particles for eco-friendly chemical mechanical planarization

Chemical mechanical planarization (CMP), a crucial process in semiconductor manufacturing, raises environmental concerns due to increased waste generation, prompting questions about its long-term sustainability. To address this issue, we explore an innovative approach to the waste management and recycling process by introducing magnetite (Fe3O4) particles coated with SiO2 layers, aimed at enhancing the CMP recycling efficiency. These core-shell particles exhibit controlled shell thickness, and modified surface charges, as confirmed by various analytical techniques. Our results reveal that slurries containing Fe3O4@SiO2 particles significantly improve W removal rates and surface smoothness compared to conventional slurries, attributed to the optimal mechanical properties. Moreover, the magnetite core facilitates the magnetic separation and recovery of used particles from spent slurries, offering a cost-effective and environmentally friendly solution. The recycling efficacy of these particles is demonstrated through multiple CMP cycles, showing consistent removal rates and surface quality, highlighting the potential of magnetic separation in sustainable CMP.

Particle size dependence of nanoclustered ceria abrasives on surface activity and chemical mechanical planarization performance

The particle size of cerium oxide (ceria) abrasives plays a crucial role in the design and development of advanced self-stopping slurries for the chemical mechanical planarization (CMP) process in semiconductor device manufacturing. However, a lack of ceria nanoparticles (NPs) with a narrow size distribution and uniform shape poses challenges in investigating the fundamental principles of the relationship between abrasive size and CMP performance. In this study, we thoroughly investigated the effect of ceria NP size on the removal rate (RR) of silicon oxide using uniform-sized nanoclustered (NC) ceria NPs with three diameters: 51.4 nm (NC51), 68.6 nm (NC69), and 108.0 nm (NC108). While all three types of ceria NPs shared a crystallinity of ∼ 70.6 %, they exhibited distinct physicochemical characteristics. As the particle size decreased, the specific surface area and chemical activity (i.e., Ce3+/Ce4+) increased by 155 % and 69 %, respectively. In the CMP process, where direct contact between the abrasives and wafer occurs, the abrasive size influences CMP performance. Experimentally, NC51 achieved the highest RR among the three slurries, along with complex size-dependent contact properties and chemical activities. These experimental results offer significant insights into precise semiconductor manufacturing in a practical manner.

Novel Probability Density Function of Pad Asperity by Wear Effect over Time in Chemical Mechanical Planarization.

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.

Experimental and Density Functional Theory Study of Inhibitors on Cobalt Corrosion for Chemical Mechanical Planarization Process

In the localized and global chemical mechanical planarization (CMP) process of Co barrier layers, corrosion inhibitors play a crucial role in the removal rate (RR) of Co and the post-polishing surface quality. In this study, quantum chemical calculations were employed to investigate the molecular reactivity of benzotriazole (BTA), 5-methyl benzotriazole (TTA), and 2,2’-{[(methyl-1H-benzotriazol-1-yl)methyl]imino}bis-ethanol (TT-LYK), and their inhibitory performance was predicted to follow the order of TT-LYK > TTA > BTA. The experimental results validated the accuracy of the predicted order under static conditions. However, the performance order of the inhibitors shifted to TTA > BTA > TT-LYK due to varying degrees of damage caused by mechanical friction to the inhibitory film. Nevertheless, all three inhibitors are capable of effectively inhibiting the Co RR to meet industrial requirements. Ultimately, considering the outstanding inhibitory performance of TT-LYK and its ease of removal during post-cleaning processes, TT-LYK is determined as the most promising inhibitor for Co barrier layer CMP.

Understanding and mitigating temperature-induced agglomeration in silica-based chemical mechanical planarization (CMP) slurry storage

This study explores the impact of temperature on silica particle agglomeration in Chemical Mechanical Planarization (CMP) slurries during storage. Slurries were stored at 15 °C, room temperature, and 45 °C, and analyzed. ATR-FTIR, RAMAN, SEM, zeta potential, and LPC were employed providing qualitative and quantitative data on slurry stability and agglomeration tendencies. Elevated temperature storage significantly increased agglomeration and large particle counts with particle counts value of ∼1.2×107 Part./ml, likely due to water molecule dehydration leading to destabilization. Low-temperature storage also induced agglomeration but to a lesser extent with particle counts the value of ∼4.0×106 Part./ml compared with the RT (∼2.0×106 Part./ml). Short-term storage yielded soft agglomerates with LPC of ∼(2.0–4.0)×106 Part./ml, while long-term high-temperature storage led to hard agglomerates with LPC of ∼3.0×107 Part./ml. The ATR-FTIR and Raman analysis indicate that the spectroscopic features of the original slurry exhibited changes upon variation of storage temperature from RT to 15 and 45 °C. The study also explored the reversibility of agglomeration post-treatment, indicating a potential mitigation pathway. The results demonstrated an inverse relationship between temperature and dissolved oxygen (DO) in silica slurries. For example. the curves depict a decrease in oxygen content from ∼10 ppm at RT to 7 ppm at 45 °C with increasing aging time. A mechanism outlining the temperature and aging-induced agglomeration was proposed, linking temperature fluctuations and thermodynamic aspects to colloidal stability. These findings offer a robust understanding of temperature-induced agglomeration in silica-based CMP slurry storage, paving the way for developing strategies to alleviate these issues and ensuring consistent CMP performance in semiconductor manufacturing.

Development of Novel Conditioning Method Using Thermal Shape Memory Characteristics of Polyurethane CMP Pad

Traditionally, the pad roughness has been maintained by wearing down the polyurethane pad with diamond disk. However, that method generates debris and reduces pad lifetime. This study propose a new approach to pad surface recovery by synthesizing a polyurethane-based raw material that exhibits shape memory behavior and can recover its shape upon heating. The findings suggest that the pad’s surface can be maintained by utilizing its shape memory trait and designing a system to heat the pad. The pad recovery tests were conducted using universal test machine (UTM) samples and found that, in terms of heat recovery, increasing the temperature had a greater effect than increasing the exposure time. CMP test was performed by using three conditioning potions: diamond disk conditioning, heat conditioning, and no conditioning. The results showed that pad asperity was recovered more efficiently with heat conditioning than with no conditioning (demonstrated by a 19% higher removal rate). The experimental results can be expected that combines diamond disk conditioning with heat conditioning could be a superior alternative for pad surface refreshment. Shape memory pads can return to their original form, leading to better chemical mechanical planarization (CMP) performance and an extended pad lifetime.

Virtual metrology for chemical mechanical planarization of semiconductor wafers

Virtual metrology for chemical mechanical planarization of semiconductor wafers

Experimental Strategies for Studying Tribo-Electrochemical Aspects of Chemical–Mechanical Planarization

Chemical–mechanical planarization (CMP) is used to smoothen the topographies of a rough surface by combining several functions of tribology (friction, lubrication), chemistry, and electrochemistry (corrosion, wear, tribo-corrosion). The surface layer of interest is structurally weakened by the chemical and/or electrochemical reactions of selected additives in a polishing slurry, and the modified surface is flattened by the abrasion of a polishing pad with or without abrasive particles. The chemically active CMP slurry also serves as a lubricant for polishing and enables planarization at a microscopic level while avoiding the formation of defects at the processed surface. Applications of CMP are wide-ranging in various material-processing technologies and, specifically, it is a critical manufacturing step of integrated circuits. The CMP of metals is a significant part of this processing scheme and is associated with highly complex tribo-electrochemical mechanisms that are now additionally challenging due to various new requirements of the advanced technology nodes. The present review examines the current statuses of experimental strategies for collecting important mechanistic details of metal CMP that are necessary to design and assess CMP consumables. Both traditional and underexplored experimental techniques are discussed with illustrative results, including many previously unpublished findings for certain CMP systems of current interest.

Effect of 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTCA) on Cu/Ta chemical mechanical planarization (CMP) in the barrier layer: A novel complexing agent and the dual role on Cu

Tantalum and its nitrides are used in barrier layers in copper interconnected ultra-large-scale integrated circuits. However, due to the different physical and chemical properties of copper (Cu) and tantalum (Ta), the difference in removal rates is a problem. This study developed an acidic barrier layer slurry with better Cu/Ta rate-selective properties. During the research and development process, it is found that the introduced novel complexing agent, 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTCA), has a bisexual effect on Cu while effectively enhancing the Ta removal rate. Therefore, the detailed analysis was carried out on the mechanism of PBTCA on Cu/Ta. In this study, the effects of the slurry fundamental composition, include pH value, oxidant H2O2 and complexing agent PBTCA, on Cu/Ta removal rate were firstly investigated by electrochemical and chemical mechanical planarization (CMP) experiments. Subsequently, XPS, SEM and AFM tests were utilized for in-depth analysis of the micro-activity mechanism of PBTCA. The concentration of PBTCA between 0.2 wt% and 0.3 wt% was found to have complexation effect on Cu, and the concentration between 0.3 wt% and 0.8 wt% was found to have corrosion inhibition effect on Cu, which verified that PBTCA has a dual effect on Cu. This phenomenon effectively reduces the difference of Cu/Ta removal rate and facilitates surface flattening. In addition, PBTCA is an environmentally friendly and biodegradable organophosphate condensate. Finally, the slurry stability experiments were carried out by average particle size and zeta potential tests. CMP experiments and atomic force microscopy (AFM) tests were employed to verify the performance of the slurry. It was concluded that the slurry was well stabilized with the oxidant addition, and the storage time had almost no effect on the removal rate and surface morphology of Cu and Ta. The results of the study provide a feasible method for barrier layer CMP.

Two decades of ceria nanoparticle research: structure, properties and emerging applications.

Cerium oxide nanoparticles (CeNPs) are versatile materials with unique and unusual properties that vary depending on their surface chemistry, size, shape, coating, oxidation states, crystallinity, dopant, and structural and surface defects. This review encompasses advances made over the past twenty years in the development of CeNPs and ceria-based nanostructures, the structural determinants affecting their activity, and translation of these distinct features into applications. The two oxidation states of nanosized CeNPs (Ce3+/Ce4+) coexisting at the nanoscale level facilitate the formation of oxygen vacancies and defect states, which confer extremely high reactivity and oxygen buffering capacity and the ability to act as catalysts for oxidation and reduction reactions. However, the method of synthesis, surface functionalization, surface coating and defects are important factors in determining their properties. This review highlights key properties of CeNPs, their synthesis, interactions, and reaction pathways and provides examples of emerging applications. Due to their unique properties, CeNPs have become quintessential candidates for catalysis, chemical mechanical planarization (CMP), sensing, biomedical applications, and environmental remediation, with tremendous potential to create novel products and translational innovations in a wide range of industries. This review highlights the timely relevance and the transformative potential of these materials in addressing societal challenges and driving technological advancements across these fields.

Synergistic Control on Co/Cu Galvanic Corrosion and Its Application for Co Barrier Chemical Mechanical Planarization in Alkaline Slurry

Selective chelation and protective film formation were synergistically combined to achieve Co/Cu galvanic corrosion control. Chelating agent imionodisuccinic acid and protective film formation agent benzotriazole are strategically chosen for fulfilling the above proposed task in alkaline solution for Co barrier chemical mechanical planarization (CMP). Chronopotentiometry and linear dynamic potential polarization methods are used to investigate the thermodynamics and kinetics of Co and Cu corrosion. A synergistic control of Co/Cu corrosion was accomplished by judiciously balancing the power of selective chelation and protective film formation. This systematic approach can be expanded to systematically design other metal CMP slurries to fulfil the desired polishing performance.

Predicting the Material Removal Rate in Chemical Mechanical Planarization Based on Improved Neural Network

Predicting the Material Removal Rate in Chemical Mechanical Planarization Based on Improved Neural Network