Measuring EPE on logic devices is challenging due to the large variety of features given its random environment and layout. One has to measure an enormous amount of unique features to estimate CD, PPE, LCDU, and LPE of each feature making it impractical for EPE monitoring due to the large metrology load. We developed a simulation-based pattern clustering method that identifies and classifies features with similar EPE behavior to address this challenge. Both geometric design and imaging behavior of the patterns were taken into account to effectively cluster similar features. We report here the verification results of the clustering method which is measured on-wafer for both random layout lines-spaces and vias. With this we make a step towards identification and selection of EPE critical patterns for logic devices, which can be used further for monitoring and control.
A single exposure EUV patterning process has been optimized for hexagonal contact holes (CHs) at pitch 36nm and SRAM via. Defect inspection results are reported using after etch voltage contrast (VC) metrology as well as after metallization. By comparing top-down scanning electron microscopy (SEM) and VC images, the VC technique was proven to detect the close defective CHs not only on the top surface but also at the bottom of CHs. This is confirmed on cross section inspection using transmission electron microscopy (TEM) metrology. To quantify the number of defects (NoDs) per million CHs, both a greyscale analysis and a computer vision-based defect analysis algorithm are used and exhibits the dependence of NoDs on CHs mean CD. This algorithm is capable of detecting, classifying, and incrementally counting the occurrence of defect instances as closed, partially open and open CHs. An advantage of this algorithm is its distortion invariance and independence from GDS alignment.
The grouping method assisted EPE-aware control method is being explored in a multi-feature dual layer Logic use case. EPE metric is estimated using angle resolved optical Scatterometry based overlay and electron beam-based metrology (large field of view SEM) for the reconstruction of edge-to-edge distance between the Metal and Via pattern. In the setup phase, EPE sensitivities to dose and focus have been derived using data from a FEM wafer. EPE-aware optimization, using scanner dose and overlay control sub-recipes, outperforms traditional optimization in simulations showing reduced EPE max per die. This improvement suggests a potential increase in device yield through the adoption of EPE-aware control strategies. To verify this performance improvement on wafers, an experiment is needed with minimal wafer to wafer and lot to lot variations which can be achieved by reducing time between lots and increasing the number of wafers measured.
We demonstrate the use of EPE (Edge Placement Error) as an early defect detection metric in an EUV self-aligned lithoetch-litho-etch (eSALELE) patterning process. Pitch 21nm test structures were investigated on an eSALELE flow consisting of 4 EUV exposures, 2 of which are lines-spaces while the other 2 exposures are for block patterns that defines the tip-to-tip. An HMI eP5 SEM with large field-of-view (8x8µm FOV) was used to measure critical dimension (CD) on wafer at each critical processing step while the overlay between multiple exposures were measured optically on uDBO marks using a YieldStar (YS). On top of CD metrology, patterning defects were measured at the final patterning transfer into dielectric material using an eP5 SEM and built-in defect inspection capability. Line-break defects are reported. Although each metric like CD, LWR or OVL is expected to contribute to the defect performance of the final pattern transfer, using only one information or another is not fully descriptive. Combining these information into an EPE metric on this complicated patterning process showed better correlation to the defect rates at dielectric transfer.
EUV resists, while improving steadily, generate a number of nanobridge or break defects that increases quickly as the pitch approaches 30 nm. Inline inspection methods are therefore needed to reliably detect patterning defects smaller than 20 nm. Massive e-beam metrology provides the high resolution needed to measure these defects, while remaining compatible with HVM throughput requirements. In this work, we used a direct metal (Ru) etch process, to fabricate EUV-patterned electrical structures in the 32 nm-36 nm pitch range. We demonstrate an almost one-to-one correspondence between the e-beam metrology yield of the structures, and their electrical yield. The e-beam inspection is realized with a large-field-of-view HMI eP5 e-beam system. The match between e-beam and electrical yield shows that our e-beam inspection is able to catch all electrically relevant line breaks, while excluding false flags. These results demonstrate the capability of massive e-beam inspection in predicting electrical yield.
This paper, originally published on 26 March 2019, was replaced with a corrected/revised version on 25 June 2019. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
With growing process complexity and the increasing number of process steps, early prediction of device performance has become an important task in semiconductor manufacturing process control. Machine learning (ML) techniques allow us to link in-line measurements to End-Of-Line (EOL) electrical tests. In our paper, we use reflectance spectra obtained from the scatterometry tool to predict both metal-line resistance and capacitance. We used IMEC N14 process flow with LELE double patterning at the M1 stage. Special designs-of-experiments (DOE) for multiple parameters allowed us to create a metrology solution for the entire process window and test its accuracy for all POI. Induced variations of both line CDs and space CDs, together with specially designed measurement sites, created wide variations both in metal-line resistance and capacitance. Reflectance spectra were collected in-line at two process steps defining metal lines: HM etch and Cu CMP at multiple targets, including E-test measurement sites, together with reference metrology for overlay (OV) and CD (by using Diffraction-Based-Overlay (DBO) and CD SEM). EOL electrical test results were used for the ML training procedure for early prediction of patterning effects (both CD and OL) on electrical performance enabling early decisions and cost reduction by discarding out-of-spec wafers before they reached the electrical test. It was shown that ML OCD predictive techniques are complimentary to the OCD model-based solutions for geometrical parameters widely used for in-line APC.
Voltage contrast (VC) is a long known and well established technique to give combined inline sensitivity to electrically relevant measures of defectivity but also local defect isolation and integrated review SEM making the technique a critical piece of fab wafer inspection. By creation of a special mark design with many local repeats of different CD and overlay set points a voltage contrast response is created which allows the local edge placement error population to be estimated while also capturing a connectivity and isolation yield proxy. This enables high throughput local estimates of overlay, CD, overlay and CD process window and local CD uniformity.
A test mask containing these marks was designed and fabricated at IMEC with metrology done on optical and electron beam inspection systems. Both open and short sensitivity are programmed into the marks and this yield proxy data has inherent value on its own. We propose to integrate these special test marks into some critical layers in modern memory and logic process flows with a design which can be added to scribe lines or empty regions/in die test structures in logic or empty regions of the memory periphery. Significant design and process knowledge is required to design a mark which can integrate with the process and give good EPE sensitivity.
Initial mark designs have been targeted at single damascene copper on tungsten with VC inspection after copper polish. Initial results show a high baseline yield loss but also show clear and intuitive CD and Overlay process window quantification from the VC EPE marks. Marks as large as ~100,000 um2 and as small at 250um2 have been designed and enable overlay, CD, LCDU and with yield sensitivity to ~1 part per million for the larger marks and ~1% for the smallest marks. With the expected productivity of the ebeam inspection system we should be able thousands of marks per wafer or field to support diverse overlay, CD and control use models and process fingerprint mapping.
Spacer-assisted pitch multiplication is a patterning technique that is used on many different critical layers for memory and logic devices. Pitch walk can occur when the spacer process, a combination of lithography, deposition and etch processes, produce a repeating, non-uniform grating of space / line CDs. It has been shown that for spacer-assisted double patterning (SADP), where the lithography pitch is doubled, pitch walk can be reduced by controlling the exposure dose such that the uniformity of the final SADP spaces defined by the core resist mandrel (S1) is balanced with the final SADP space defined by the distance between adjacent SADP lines (S2). For higher pitch multiplications, starting with spacer-assisted quadruple patterning (SAQP) reducing systematic pitch walk with exposure dose becomes more complex.
Co-optimization of the lithography and etch processing is expected to be required to achieve the best pitch walk control. Previous work has shown that improving the across wafer CD uniformity of the line patterns after core etch has limited impact on the space CD uniformity after the SADP process, whereas the CD uniformity of the spaces after SAQP did show some dependence. There are additional space populations created by an SAQP process. The variation of these different populations, along with the spacer deposited line populations, is the root cause of the non-uniform grating that results in pitch walk. The complex interactions of the lithography and etch processes’ impact on the CD and profile need to be understood to produce the optimal performance.
Pitch walk is a component of the overall Edge Placement Error (EPE) budget. With current nodes using SAQP for multiple device layers and future nodes expected to continue to implement this patterning technique, minimization of pitch walk variability is an important part of overall patterning optimizations. In this work, we will show how cooptimized exposure dose and etch processes for SAQP patterning can improve pitch walk performance. We will provide a target exposure dose metric for a 32nm pitch SAQP grating. The methodology for achieving the best pitch walk performance by combination of etch process optimization with dose correction will also be shown.
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