Dmitriy Likhachev

Low-k n&k variation impact on CD accuracy of scatterometry

Scatterometry is one of the advanced optical metrology techniques has been implemented in semiconductor manufacturing for monitoring and controlling critical dimensions, sidewall angle and grating heights as well as thicknesses of underlying films, due to its non-destructive nature, high measurement precision and speed. In traditional scatterometry approach, the optical properties (n&ks) of film stack have been used as fixed inputs in a scatterometry model, therefore, the process engineers have to assume that there is no significant impact on measurement results by small deviation from pre-extracted n&ks. However, n&ks of actual production wafers will always vary from the fixed values used in the model. The magnitude of the variations and its impact on the accuracy of scatterometry measurements has not been well-characterized yet. In this study, a low-k dielectric stack with noticeable n&ks variations was generated. The low-k dielectric stack has the refractive index (n) variation around 0.01 @ 633nm within a wafer, and is under two layers of patterned PR and BARC. Different scatterometry models with fixed and floated n&ks have been analyzed. Although comparable repeatability was obtained with either fixed or floated n&ks model, the correlation (R2) to CD-SEM result has been improved by floating n&k in the model in comparison to that of fixed n&k model. In this paper, we also discuss some differences in applying various optical models (i.e, EMA and Cauchy) in scatterometry measurements.

Integrated ODP metrology with floating n&k's for lithography process

Advanced DRAM manufacturing demands rigorous and tight process control using high measurement precision, accurate, traceable and high throughput metrology solutions. Scatterometry is one of the advanced metrology techniques which satisfies all the above mentioned requirements and it has been implemented in semiconductor manufacturing for some time for monitoring and controlling critical dimensions and other important structural parameters. One of the major contributions to the optical critical dimensions metrology uncertainty is the variations in optical properties (n&ks) of film stack materials. And it is well-known that the optical properties of materials depend very much on process conditions (such as operating conditions of deposition tools). However, in traditional scatterometry approach all the n&ks have been used as fixed inputs in a scatterometry model which might result in significant metrology error. This paper shows the use of the integrated scatterometry system in a real production environment. The significant improvement in accuracy of CD data was achieved following the implementation of new floating n&ks option for the Optical Digital Profilometry (ODPTM) system. It has been clearly shown that to achieve desired sub-nanometer accuracy in scatterometry measurements for advanced processes we need to pay scrupulous attention to every detail of the scatterometry modeling and measurement. Still further work is needed to better understand the impact of n&ks variations on tool-to-tool matching.

Context-based virtual metrology

Hybrid and data feed forward methodologies are well established for advanced optical process control solutions in highvolume semiconductor manufacturing. Appropriate information from previous measurements, transferred into advanced optical model(s) at following step(s), provides enhanced accuracy and exactness of the measured topographic (thicknesses, critical dimensions, etc.) and material parameters. In some cases, hybrid or feed-forward data are missed or invalid for dies or for a whole wafer. We focus on approaches of virtual metrology to re-create hybrid or feed-forward data inputs in high-volume manufacturing. We discuss missing data inputs reconstruction which is based on various interpolation and extrapolation schemes and uses information about wafer’s process history. Moreover, we demonstrate data reconstruction approach based on machine learning techniques utilizing optical model and measured spectra. And finally, we investigate metrics that allow one to assess error margin of virtual data input.

In-line control of material properties of SiOC:H based low-k dielectrics utilizing optical metrology

Manufacturing process control of porous SiOC:H low-k dielectrics is challenging due to their hybrid nature and process damage vulnerability. We discuss advanced optical modeling of various low-k dielectrics that allows one to reflect their material properties and improves accuracy and precision of scatterometry models widely utilized in manufacturing process control. Furthermore, we explore usage of optical material model data for investigating UV-curing and deposition chamber signatures as well as variety of process damage that requires strict control.

In-line control of material properties of SiOC:H based low-k dielectrics utilizing optical metrology AM: Advanced metrology

Manufacturing process control of porous SiOC:H low-k dielectrics is challenging due to their hybrid nature and process damage vulnerability. We discuss advanced optical modeling of various low-k dielectrics that allows one to reflect their material properties and improves accuracy and precision of scatterometry models widely utilized in manufacturing process control. Furthermore, we explore usage of optical material model data for investigating UV-curing and deposition chamber signatures as well as variety of process damage that requires strict control.

Advanced optical modeling of TiN metal hard mask for scatterometric critical dimension metrology

The majority of scatterometric production control models assume constant optical properties of the materials and only dimensional parameters are allowed to vary. However, this assumption, especially in case of thin-metal films, negatively impacts model precision and accuracy. In this work we focus on optical modeling of the TiN metal hardmask for scatterometry applications. Since the dielectric function of TiN exhibits thickness dependence, we had to take this fact into account. Moreover, presence of the highly absorbing films influences extracted thicknesses of dielectric layers underneath the metal films. The later phenomenon is often not reflected by goodness of fit. We show that accurate optical modeling of metal is essential to achieve desired scatterometric model quality for automatic process control in microelectronic production. Presented modeling methodology can be applied to other TiN applications such as diffusion barriers and metal gates as well as for other metals used in microelectronic manufacturing for all technology nodes.

B-spline parameterization of the dielectric function and information criteria: the craft of non-overfitting

Johs and Hale developed the Kramers–Kronig consistent B-spline formulation for the dielectric function modeling in spectroscopic ellipsometry data analysis. In this article we use popular Akaike, corrected Akaike and Bayesian Information Criteria (AIC, AICc and BIC, respectively) to determine an optimal number of knots for B-spline model. These criteria allow finding a compromise between under- and overfitting of experimental data since they penalize for increasing number of knots and select representation which achieves the best fit with minimal number of knots. Proposed approach provides objective and practical guidance, as opposite to empirically driven or “gut feeling” decisions, for selecting the right number of knots for B-spline models in spectroscopic ellipsometry. AIC, AICc and BIC selection criteria work remarkably well as we demonstrated in several real-data applications. This approach formalizes selection of the optimal knot number and may be useful in practical perspective of spectroscopic ellipsometry data analysis.

Dielectric function parameterization by penalized splines

In this article, we investigate the penalized spline (P-spline) approach to restrict flexibility of dielectric function parameterization by B-splines and prevent overfitting of the ellipsometric data. The penalty degree is easily controlled by a certain smoothing parameter. The P-spline approach offers a number of advantages over well-established B-spline parameterization. First of all, it typically uses an equidistant knot arrangement which simplifies the construction of the roughness penalties and makes it computationally efficient. Since P-splines possess the “power of the penalty” property, a selection of the number of knots is no longer crucial, as long as there is a minimum knot number to capture all significant spatial variability of the data curves. We demonstrate the proposed approach by real-data application with ellipsometric spectra from aluminum-coated sample.

Integrated ODP Metrology Matching To Reference Metrology For Lithography Process Control

Advanced DRAM manufacturing demands rigorous and tight process control using high measurement precision, accurate, traceable and high throughput metrology solutions. Scatterometry is one of the advanced metrology techniques which satisfies all of these requirements. Scatterometry has been implemented in semiconductor manufacturing for monitoring and controlling critical dimensions and other important structural parameters. One of the major contributing factors to the acceptance and implementation of scatterometry systems is the ability to match to reference metrology. Failure to understand the optimum matching conditions, can lead to wrong conclusions with respect to hardware stability and/or incorrect analysis of production data. This paper shows the use of the integrated scatterometry system to control the lithography processes in a real production environment. In the control system, the scatterometry Optical Digital Profilometry (ODP™) data is referenced to sampled CD‐SEM data. A significant improvemen...