In the realm of next-generation EUV masks, several material candidates show promising absorber behaviors, ranging from binary to phase-shift types. However, the mask repair process presents challenges when managing wafer windows for repaired defects. Precious profile control, high repair-defect durability and clean reticle surface need to be sustained to ensure lithography processes window. In this paper, several materials’ opaque defect etching is evaluated by using ZEISS e-beam based MeRiT® neXT repair tools, which offer an optimal physico-chemical process with right precursor chemistry and an optimized scanning of the e-beam over the surface to ensure repair quality. Moreover, longer repair time for next generation masks also challenges post-repair clean yield due to poor wettability from etching byproduct redeposition on reticle surface. Thus, we control a plasma flushing vacuum chamber application to eliminate surface wettability degradation, ensuring high post-repair clean yield. Our comprehensive strategy not only addresses current challenges with better reticle quality and longer lifetime but also paves the way for the seamless integration of advanced EUV mask materials into the future of semiconductor lithography.
With EUV reticle features shrinking and becoming more complicated, conventional 193 nm inspection tools pose significant challenges due to poor signal-to-noise (SNR) ratio, low optical image stability, and limited data processing capability. To meet these challenges, we have implemented machine learning techniques in EUV reticle inspection starting from advanced technology nodes, which effectively improve defect SNR and eliminates false counts. This accomplishment has been made possible through a combination of several innovations addressed in KLA’s third generation Teron™ 640e Series system: 1. Aberration Control Compensation Techniques: These techniques reduce intrinsic optical noise, enhancing accurate defect detection. 2. Focus drift improvement: Controlling focus drift within tens of nanometers through a full mask area scan is achieved by deploying high-frequency focus trajectory calibration and a low thermal expansion stage. 3. X30 Die-to-Database (DB) Inspection Mode: Leveraging Gen-2 deep learning algorithms, this encompasses a comprehensive analysis of layout dimensions and the integration of design elements through to the final pattern generation. The objective is to enhance the modeling process, thereby diminishing noise levels for superior inspection sensitivity. 4. Curvilinear-Friendly Geometry Classification Scheme: KLA-designed Gen-2 feature map for advanced inspection sensitivity control. 5. Enhanced Data Preparation Server: Efficiently handling data sizes of OASIS P49 MULTIGON format four times larger than traditional Manhattan formats, this server ensures comparable data preparation time. The 3rd generation Teron™ 640e Series system has been demonstrated to meet production requirements for N technology node and beyond. The next step will focus on cutting-edge optical and algorithm design to overcome resolution limitations and implementing these advanced technologies in the most suitable areas of EUV mask inspection.
New designs "meta-atom" and "meta-material" composed from all-dielectric resonators with high Q and low loss, this
kind metamaterial is coupled from propagating plane wave and generates electromagnetic response like
electromagnetically induced transparency in atomic vapor. The "meta-atom" or "meta-molecular" are not only workable
in room temperature but also enable three dimensional ommidirectionally incident with superposition stacking.
Meanwhile, the EIT-like via dielectric metamaterial with high transmittance, dramatic index change and tunable
operating frequency. The simulation result agrees the possibility electromagnetically induced transparency -like bulk
exists from microwave to THz region.
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