Russell Dover

Source mask optimization methodology (SMO) and application to real full chip optical proximity correction

Due to the continuous shrinking in half pitch and critical dimension (CD) in wafer processing, maintaining a reasonable process window such as depth of focus (DOF) & exposure latitude (EL) becomes very challenging. With the source mask optimization (SMO) methodology, the lithography process window can be improved and a smaller mask error enhancement factor (MEEF) can be achieved. In this paper, the Tachyon SMO work flow and methodology was evaluated. The optimum source was achieved through evaluation of the critical designs with Tachyon SMO software and the simulated performance was then verified on another test case. Criteria such as DOF, EL & MEEF were used to determine the optimum source achieved from the evaluation. Furthermore, the process variation band (PV-Band) and the number of hot spot (design weak points) were compared between the POR and the optimum source. The simulation result shows the DOF, MEEF & worst PV-Band were improved by 13%, 17% & 12%, respectively with the optimum SMO source. In order to verify the improvement from the optimum SMO at the silicon level, a new OPC model was recalibrated with wafer CD from the optimized source. The OPC recipe was also optimized and a reticle was retrofitted with the new OPC. By comparing the process window, hotspots and defects between the original vs. new reticle, the benefit of the optimized source was verified on silicon.

Demonstration of an effective flexible mask optimization (FMO) flow

The 2x nm generation of advanced designs presents a major lithography challenge to achieve adequate correction due to the very low k1 values. The burden thus falls on resolution enhancement techniques (RET) in order to be able to achieve enough image contrast, with much of this falling to computational lithography. Advanced mask correction techniques can be computationally expensive. This paper presents a methodology that enables advanced mask quality with the cost of much simpler methods. Brion Technologies has developed a product called Flexible Mask Optimization (FMO) which identifies hotspots, applies an advanced technique to improve them, performs model based boundary healing to reinsert the repaired hotspot cleanly (without introducing new hotspots), and then performs a final verification. STMicroelectronics has partnered with Brion to evaluate and prove out the capability and performance of this approach. The results shown demonstrate improved performance on 2x nm node complex 2D hole layers using a hybrid approach of rule based sub resolution assist features (RB-SRAF) and model based SRAF (MB-SRAF). The effective outcome is to achieve MB-SRAF levels of quality but at only a slightly higher computational cost than a quick, cheap rule based approach.

Improving COO on KLA-Tencor wafer fab reticle inspections by implementing pixel migration as new STARlight2+ capability

KLA-Tencor has introduced the new TeraFab reticle inspection systems for wafer fabs to address market demand for systems with high productivity and high sensitivity. The core inspection technology of the TeraFab systems is STARlight2+ (SL2+). STARlight is the industry accepted method for mask inspection in wafer fabs for reticle requalification. STARlight uses transmitted and reflected light images of a reticle to generate reference images of the reticle that are used to detect defects that have been added to the reticle while the reticle has was exposed or in storage. The improvements in reference generation in SL2+ relative to previous generations of STARlight is made possible, in part, by increases in computation resources for TeraFab systems. Improved modeling capability of SL2+ leads to increased usable sensitivity in dense geometries. Improved modeling capability also allows the user to optimize inspection cost of ownership (COO) if the maximum sensitivity of the TeraFab system is not required for a specific application. This paper describes an investigation of sensitivity versus throughput using SL2+ on multi-die production reticles with haze at the 65nm technology node. SL2+ data is also provided showing the feasibility of using larger inspection pixels (pixel migration) while retaining good sensitivity at the 45nm technology node.

Improving Cost of Ownership on KLA-Tencor Wafer Fab Reticle Inspections by Implementing Pixel Migration via New STARlight2+ Capability

In the ever-changing semiconductor industry, wafer fabs and mask shops alike are adding low cost of ownership (CoO) to the list of requirements for inspections tools. KLA-Tencor has developed and introduced STARlight2+ (SL2+) to satisfy this need. This new software algorithm is available on all TeraScanHR and TeraFab models. KLA-Tencor has cooperated with United Microelectronics Corporation (UMC) to demonstrate and improve SL2+, including its ability to lower CoO, on 65nm and below photomasks. These improvements are built on the rich history of STARlight. Over the years, STARlight has become one of the industry standards for reticle inspection. Like its predecessors, SL2+ uses only transmitted and reflected light images from a reticle to identify defects on the reticle. These images along with plate-specific information are then processed by SL2+ to generate reference images of how the patterns on the reticle should appear. These reference images are then compared with the initial optical images to identify the defects. The new and improved SL2+ generates more accurate reference images. These images reduce background noise and increase the usable sensitivity. With the results from controlled engineering tests, a fab or mask shop can then decide to inspect reticles at a given technology node with a large pixel; this is sometimes referred to as pixel migration. The larger pixel with SL2+ can then perform the inspections at similar sensitivity settings and higher throughput, thus lowering CoO.

Results of new mask contamination inspection capability STARlight2+ 72nm pixel with cell-to-cell HiRes5 for qualifying memory masks in wafer fabs

As the industry embarks on sub 50nm half pitch design nodes, higher resolution and advanced photomask inspection algorithm are needed to resolve shrinking features and find critical yield limiting defects. In this paper, we evaluate the detection capability of STARlight2+ 72nm pixel on sub-50nm memory masks. The mask sets targeted for this evaluation were focused on critical layers. Although memory mask sets are dominated by multi-die layout, single die layout masks were also inspected because of their significance during research and development. Inspection results demonstrated the performance of STARlight2+ based on its sensitivity to contamination defects and the inspectability of masks with this detection method. The most common plan of record for mask inspection in a wafer fab is die-to-die transmitted pattern inspection modes, which limits the inspection area to the die region only and cannot be used for single-die reticle inspections. However, STARlight2+ has single die inspection capability, which is also needed in order to inspect scribe-lines and frame areas. The primary defects of interest are photo induced crystal defects or haze. Haze continues to be the primary reason for mask returns at 193nm exposure across the industry. The objective of this paper is to demonstrate STARlight2+ 72nm capability to support memory wafer fab mask qualification requirements.

Results of new mask contamination inspection capability STARlight2+ 72nm pixel for qualifying memory masks in wafer fabs

As the industry embarks on sub 50nm half pitch design nodes, higher resolution and advanced inspection algorithm are needed to resolve shrinking features and find critical yield limited defects. In this paper, we evaluate the detection capability of STARlight2+ 72nm pixel on DRAM masks. The mask sets targeted for this evaluation were focused on critical layers. Although memory mask sets are dominated by multi-die layout, single die layout masks were also inspected because of their significance during research and development. Inspection results demonstrated the performance of STARlight2+ based on its sensitivity to contamination defects, inspectability, first time success rate and throughput. STARlight2+ has single die inspection capability, which is also needed in order to inspect scribe-lines and frame areas. The primary defects of interest are photo induced defects or contamination, causing mask degradation. Contamination continues to be the primary reason for mask returns at 193nm exposure across the industry. The objective of this paper is to demonstrate STARlight2+ 72nm capability to support memory wafer fab mask qualification requirements.