Communication—Synergistic Effect of Mixed Particle Size on W CMP Process: Optimization Using Experimental Design

Seo, Jihoon; Moon, Jiho; Kim, Yehwan; Kim, Kijung; Lee, Kangchun; Cho, Yoonsung; Lee, Dong Hee; Paik, Ungyu

doi:10.1149/2.0171701jss

Cited by 12 publications

(9 citation statements)

References 9 publications

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“…The Preston equation can only provide a linear prediction of the variation in the MRR, however, lots of studies have shown that the real MRR during polishing is nonlinear [3]- [11]. In order to simplify our model, we varied the force applied only with three different levels while kept the other parameters fixed.…”

Section: Problem Backgroundmentioning

confidence: 99%

Key Issues for Implementing Smart Polishing in Semiconductor Failure Analysis

Leo¹,

Tan²,

Ma³

et al. 2017

JAMP

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Abstract"Industry 4.0" has become the future direction of manufacturing industry. To prepare for this upgrade, it is important to study the automation of semiconductor failure analysis. In this paper, the sample polishing activity was studied for upgrading to a smart polishing process. Two major issues were identified in implementing the smart polishing process: the optimization of current polishing recipes and the capability of making decisions based on live feedback. With the help of Solver add-in, the current polishing recipes were optimized. To make decisions based on live images captured during polishing, strategies were explored based on finger polishing process study. Our investigation showed that a grey scale line profile analysis on images can be used to build the vision capability of our smart polishing system, on which a decisionmaking capability can be developed.

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Section: Problem Backgroundmentioning

confidence: 99%

Key Issues for Implementing Smart Polishing in Semiconductor Failure Analysis

Leo¹,

Tan²,

Ma³

et al. 2017

JAMP

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“…12,23,27 Moreover, based on statistical model, the synergistic effect with mixing of three different-sizes abrasives and W CMP performance were investigated to obtain the optimal mixing ratio for the highest removal rate. 29 To optimize the slurry components for W barrier CMP process with W-patterned wafers, a response surface methodology and a face center cube design were introduced to investigate the tradeoff between the removal rate and selectivity. 24 All these investigations indicate that the slurry property has a large effect on the removal rate and surface planarity, which should be considered in construction of W CMP model to establish the surface kinetic processes in revealing the polishing mechanism.…”

mentioning

confidence: 99%

A Material Removal Rate Model for Tungsten Chemical Mechanical Planarization

Xu¹,

Cao²,

Liu³

2022

ECS J. Solid State Sci. Technol.

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A tungsten removal rate model is proposed in the chemical mechanical planarization (CMP) process to investigate the removal mechanism with consideration of the synergistic effect of chemical reaction and mechanical abrasion. Based on the fundamentals of steady-state chemical reaction and mechanical abrasion, a chemical reaction kinetics CMP model is first built up to relate the removal rate to the chemical reagent and mechanical rate parameters. Then the Greenwood-Williamson contact theory is introduced into the chemical reaction kinetics model to construct a closed-form equation of removal rate, which captures the synergistic coupling effect of chemical and mechanical interactions. Furthermore, the present model is verified by the collected experimental data and utilized to investigate the impact of the design pattern effects on the removal rate. The consistency of the model prediction and the experimental data as well as the removal characteristics of design pattern structures indicate that the new proposed tungsten CMP model can be adopted to elucidate the synergistic effect of chemical and mechanical interactions and perform the sensitivity analysis of the design pattern dependency on removal rate of tungsten films.

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“…3,4 Physics-based CMP models and simulation methods are quite useful to provide some fundamental insights into the removal rate and the surface planarity and can be used to assist in optimization of the process parameters. 4,21,22 In CMP modeling, all kinds of predictive models have been proposed to capture one or two aspects of the polishing mechanism at different length scales using different methods. Particle-scale CMP models are generated to depict the particle concentration and size distribution on the removal rate based on the elastic-plastic micro-contact mechanics and abrasive wear theory.…”

mentioning

confidence: 99%

“…[43][44][45] Furthermore, mixed lubrication models are developed to analyze CMP process characteristics by using contact mechanics and fluid hydrodynamics. 3,4,15,20,22,46,47 Meanwhile, the contact mechanics-and chemical kinetics-based removal rate models are also proposed to investigate the synergistic effect of chemical reaction and mechanical abrasion. 2,6,12,27 Fluid hydrodynamics-and chemical reaction kinetics-based CMP models are also put forward to reveal the removal mechanism of CMP systems.…”

mentioning

confidence: 99%

A Wafer-Scale Material Removal Rate Model for Chemical Mechanical Planarization

Chen

Liu

et al. 2020

ECS J. Solid State Sci. Technol.

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In this work, a new wafer-scale material removal rate (MRR) model is proposed to investigate the underlying removal mechanism of wafer surface in the chemical mechanical planarization (CMP) process. Based on the governing equation of the plate theory, chemical reaction kinetics and wear theory, an analytical CMP model has been constructed to capture the influence of mechanical abrasion and chemical reactions on the removal rate with high efficiency. The effect of the elastic modulus of the pad, platen rotational speed, polishing temperature and reactant concentrations on the removal mechanism is investigated in detail to elucidate the intrinsic removal behavior. It is found that the material removal rate is sensitive to the elastic modulus of pad, temperature distribution, and chelator concentration, more sensitive to the oxidizer concentration, and most sensitive to the platen rotational speed. The magnitude of the removal rate can be adjusted significantly by properly selecting a good configuration of these influencing factors. The model predictions of the MRR profiles are consistent with the published experimental data at different polishing conditions. Therefore, the present CMP model can give insights into the wear mechanism of polishing process and may be utilized as a simulation tool for further optimization of removal rate and surface uniform control.

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Communication—Synergistic Effect of Mixed Particle Size on W CMP Process: Optimization Using Experimental Design

Cited by 12 publications

References 9 publications

Key Issues for Implementing Smart Polishing in Semiconductor Failure Analysis

Key Issues for Implementing Smart Polishing in Semiconductor Failure Analysis

A Material Removal Rate Model for Tungsten Chemical Mechanical Planarization

A Wafer-Scale Material Removal Rate Model for Chemical Mechanical Planarization

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