Advancing technology nodes in DRAM continues to drive the reduction of on-product overlay (OV) budget. This gives rise to the need for OV metrology with greater accuracy. However, the ever increasing process complexity brings additional challenges related to metrology target deformation, which could contribute to a metrology error. Typically, an accurate OV measurement involves several engineering cycles for target and recipe optimization. In particular, process optimization in either technology development (TD) phase or high volume manufacturing (HVM) phase might influence metrology performance, which requires re-optimization. Therefore, a comprehensive solution providing accuracy and process robustness hereby minimizing the cycle time is highly desirable. In this work, we report multi-wavelength μDBO enhanced with accuracy aware pixel selection as a solution for robust OV measurement against process changes as well as improved accuracy in HVM. Accuracy aware pixel selection is capable of tackling intra-target processing variations and is established on a multi-wavelength algorithm with immunity to target asymmetry impact. DRAM use cases in FEOL critical layers will be discussed in this paper. Superior robustness and accuracy will be demonstrated together with improved on-product OV performance, promising a process of record metrology solution in specific applications throughout the TD and HVM.
In leading-edge lithography, field-by-field corrections, also known as corrections per exposure, are well established. Many manufacturers use a combination of the traditional higher order wafer and intrafield polynomial corrections, combined with linear field-by-field corrections. However, non-linear wafer deformations are usually strongest at the wafer edge. Therefore, specific high order field-by-field corrections are the ultimate correction method to mitigate the effects of these non-linear wafer deformations. However, determining the appropriate amount of high order field-to-field corrections is not trivial. At the wafer edge, exposure fields are often incomplete, so the fields contain less overlay marks and have a less regular distribution than fields that are completely on the wafer. Therefore, even on dense measurements, it is challenging to model these fields with a high order model without applying overcorrection. On the other hand, the metrology capacity for dense measurements is high, so these can typically only be performed with low frequency. Alternatively, smart field-by-field modeling algorithms are available to compute higher order effects based on reduced sampling plans. In this paper, we study different algorithmic approaches to optimize modeling algorithms for both dense and sparse (reduced) sampling plans. We compare the impact of varying the frequency of dense sampling to the performance of different modeling algorithms on sparse sampling.
In the leading-edge production measuring the geometrical dimensions with e-beam inspection (CD-SEM data) or scatterometry technology (OCD data) is one of the most time-consuming steps without adding value to the wafer. Hence the fabs want to limit the effort to minimize the costs per wafer. On the other hand, the output of the metrology steps is needed to feed the SPC and APC systems with sufficient information. We handle that trade-off with a new sampling scheme optimizer supporting CD-SEM and OCD data.
Generally, we can use the sampling scheme optimization for a set of different features and their measured parameters in parallel. Especially in logic, but also for memory, the focus and dose dependencies of several features may be different. Hence, we optimized the distribution of the measured sites to create a perfect representation of the systematic fingerprint for all important anchor features within one single sampling scheme.
For the verification of the approach we investigated two cases. The first case are dense CD measurements, which are usually needed to create and update intra-field dose corrections. We minimize the number of measured sites significantly and distribute the remaining sites over different fields to ensure a good coverage of the systematic effects. Finally, that allows us a much higher update frequency of the dose corrections and yields in smaller CDU values.
The second case optimized the throughput of an OCD metrology system. The applied high-density sampling scheme for the focus monitoring done on reference wafers takes a lot of time during measuring. That specific type of measurement is done for monitoring and updating the focus reference corrections. With our proposed solution, we can achieve the same quality with respect to the reference measurement with more 50% less measured sites.
In a 200 mm high volume environment, we studied data from a dual damascene process. Dual damascene is a combination of lithography, etch and CMP that is used to create copper lines and contacts in one single step. During these process steps, different metal CD are measured by different measurement methods. In this study, we analyze the key numbers of the different measurements after different process steps and develop simple models to predict the electrical behavior* . In addition, radial profiles have been analyzed of both inline measurement parameters and electrical parameters. A matching method was developed based on inline and electrical data. Finally, correlation analysis for radial signatures is presented that can be used to predict excursions in electrical signatures.
Multi-patterning processes have become common in the leading-edge semiconductor industry. These processes require a good patterning uniformity over the wafer while different process steps have impact. The initial lithography steps can be nearly perfect, but the CD variation after a trim process may cause CD variation after the spacer deposition. In fact, that leads to final non-uniformity of the final CD. Monitoring and controlling the individual CD parameters is not sufficient to ensure a stable process. We define a set of new KPIs, taking all contributions into account and using macro measurement data. We show that a reliable monitoring is achieved to meet the process specifications.
Proc. SPIE. 10145, Metrology, Inspection, and Process Control for Microlithography XXXI
KEYWORDS: Distortion, Overlay metrology, Process control, Virtual reality, Metrology, Environmental sensing, Front end of line, Back end of line, Reliability, Statistical analysis, Semiconducting wafers, Model-based design, Metals, Data modeling, Optical alignment
Overlay measurements are done for verification of the exposure and creation of process corrections for the next lots. As throughput of the overlay measurement tools is limited, it is desirable to avoid unnecessary measurements. Another concern can be that in-transparent stacks do not allow measuring a critical overlay relation directly. We developed methods for calculation of the overlay relation between two different layers between which there is no direct overlay measurement. We qualify the impact of sampling plans and the number of dependent layers. The indirect overlay calculation is applied on a significant high volume data set.
An active spindle system with an Electro-Magnetic Actuator (EMA) is developed for micromachining. The process of developing controllers for this mechatronic system requires reasonable models that expose the important dynamic effects without being excessively complicated. This paper develops a MIMO model with four inputs and two outputs based on the bond graph method. This model considers the bidirectional bearing compliance as well as the external load effect. System state space equations are produced automatically from the bond graph model. Simulations in several conditions are done in both time and frequency domain. Results from simulation and experiments are compared.