One of the contributors to layer-to-layer overlay in today’s chip manufacturing process is wafer distortion due to thin film deposition. Mismatch in the film specific material parameters (e.g., thermal expansion coefficients) may result in process-induced warpage of the wafers at room temperature. When these warped wafers are loaded onto the scanner for the next layer exposure, in-plane distortion patterns may be apparent after clamping. The wafer alignment system inside the scanner is designed to correct for these process-induced in-plane wafer distortion signatures. Depending on the complexity of the distortion pattern, the choice of wafer alignment model can be adapted to achieve the required overlay performance. While wafer overlay metrology is used to correct for the systematic part of the wafer distortion, the wafer alignment functionality addresses the random part that is varying from wafer-to-wafer.
In the case of a homogeneous single film of uniform stress deposited on a substrate at elevated temperatures inside a deposition tool, the resulting free-form wafer shape at room temperature will take a parabolic form (either bowl or umbrella). The resulting in-plane distortion can be described by a radial scaling pattern. A linear wafer alignment model can easily correct for these kinds of distortion patterns and the resulting overlay is close to the scanner baseline performance. Also, in the case where there is a slight variation in one of the material parameters across the wafer, the resulting wafer distortion can easily be corrected for by selecting one of the available wafer alignment models. A Higher Order Wafer Alignment model up to the third order (HOWA3) has been proven to be sufficient to bring the overlay performance down to the scanner baseline performance over the past years.
In this paper we will consider the impact of local stress variations on the global wafer deformation. One of the sources of the local stress variation is linked to the intra-field or intra-die pattern density. We will demonstrate that the intra-field stress distribution not only affects the intra-field overlay performance but has also a significant impact on the global wafer distortion. The focus will be mainly on use-cases with high intra-field stress variations similar to what is encountered in 3D-NAND processes. These cases in particular need a more advanced correction approach. However, since the underlying root cause is generic, the same approach may also be applicable to other use-cases like DRAM and Logic.
As device shrink, there are many difficulties with process integration and device yield. Lithography process control is expected to be a major challenge due to tighter overlay and focus control requirement. The understanding and control of stresses accumulated during device fabrication has becoming more critical at advanced technology nodes. Within-wafer stress variations cause local wafer distortions which in turn present challenges for managing overlay and depth of focus during lithography. A novel technique for measuring distortion is Coherent Gradient Sensing (CGS) interferometry, which is capable of generating a high-density distortion data set of the full wafer within a time frame suitable for a high volume manufacturing (HVM) environment. In this paper, we describe the adoption of CGS (Coherent Gradient Sensing) interferometry into high volume foundry manufacturing to overcome these challenges. Leveraging this high density 3D metrology, we characterized its In-plane distortion as well as its topography capabilities applied to the full flow of an advanced foundry manufacturing. Case studies are presented that summarize the use of CGS data to reveal correlations between in-plane distortion and overlay variation as well as between topography and device yield.
With the latest immersion scanners performing at the sub-2 nm overlay level, the non-lithography contributors to the OnProduct-Overlay budget become more and more dominant. Examples of these contributors are etching, thin film deposition, Chemical-Mechanical Planarization and thermal anneal. These processes can introduce stress or stress changes in the thin films on top of the silicon wafers, resulting in significant wafer grid distortions. High-order wafer alignment (HOWA) is the current ASML solution for correcting wafers with a high order grid distortion introduced by non-lithographic processes, especially when these distortions vary from wafer-to-wafer. These models are currently successfully applied in high volume production at several semiconductor device manufacturers. An important precondition is that the wafer distortions remain global as the polynomial-based HOWA models become less effective for very local distortions. Wafer-shape based feed forward overlay corrections can be a possible solution to overcome this challenge. Thin film stress typically has an impact on the unclamped, free-form shape of the wafers. When an accurate relationship between the wafer shape and in-plane distortion (IPD) after clamping is established then feedforward overlay control can be enabled. In this work we assess the capability of wafer-shape based IPD predictions via a controlled experiment. The processinduced IPDs are accurately measured on the ASML TWINSCANTM system using its SMASH alignment system and the wafer shapes are measured on the Superfast 4G inspection system. In order to relate the wafer shape to the IPD we have developed a prediction model beyond the standard Stoney approximation. The match between the predicted and measured IPD is excellent (~1-nm), indicating the feasibility of using wafer shape for feed-forward overlay control.
Within the semiconductor lithographic process, alignment control is one of the most critical considerations. In order to realize high device performance, semiconductor technology is approaching the 10 nm design rule, which requires progressively smaller overlay budgets. Simultaneously, structures are expanding in the 3rd dimension, thereby increasing the potential for inter-layer distortion. For these reasons, device patterning is becoming increasingly difficult as the portion of the overlay budget attributed to process-induced variation increases. After lithography, overlay gives valuable feedback to the lithography tool; however overlay measurements typically have limited density, especially at the wafer edge, due to throughput considerations. Moreover, since overlay is measured after lithography, it can only react to, but not predict the process-induced overlay.
This study is a joint investigation in a high-volume manufacturing environment of the portion of overlay associated with displacement induced by a single process across many chambers. Displacement measurements are measured by Coherent Gradient Sensing (CGS) interferometry, which generates high-density displacement maps (>3 million points on a 300 mm wafer) such that the stresses induced die-by-die and process-by-process can be tracked in detail. The results indicate the relationship between displacement and overlay shows the ability to forecast overlay values before the lithographic process. Details of the correlation including overlay/displacement range, and lot-to-lot displacement variability are considered.
The semiconductor industry makes dramatic device technology changes over short time periods. As the semiconductor industry advances towards to the 10 nm device node, more precise management and control of processing tools has become a significant manufacturing challenge. Some processes require multiple tool sets and some tools have multiple chambers for mass production. Tool and chamber matching has become a critical consideration for meeting today’s manufacturing requirements. Additionally, process tools and chamber conditions have to be monitored to ensure uniform process performance across the tool and chamber fleet. There are many parameters for managing and monitoring tools and chambers. Particle defect monitoring is a well-known and established example where defect inspection tools can directly detect particles on the wafer surface. However, leading edge processes are driving the need to also monitor invisible defects, i.e. stress, contamination, etc., because some device failures cannot be directly correlated with traditional visualized defect maps or other known sources. Some failure maps show the same signatures as stress or contamination maps, which implies correlation to device performance or yield.
In this paper we present process tool monitoring and matching using an interferometry technique. There are many types of interferometry techniques used for various process monitoring applications. We use a Coherent Gradient Sensing (CGS) interferometer which is self-referencing and enables high throughput measurements. Using this technique, we can quickly measure the topography of an entire wafer surface and obtain stress and displacement data from the topography measurement. For improved tool and chamber matching and reduced device failure, wafer stress measurements can be implemented as a regular tool or chamber monitoring test for either unpatterned or patterned wafers as a good criteria for improved process stability.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.