Semiconductor Intra-Field Dose Correction via Automated Recipe Generation
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Solution Overview
Problem
Existing semiconductor lithography methods fail to effectively adapt and correct intra-field dose maps for new photolithography masks, leading to non-uniform critical dimension (CD) across chips or dies due to lack of utilization of mask and scanner data, resulting in inefficient dose correction and prolonged setup times.
Innovation Solution
An automatic dose-correction recipe generation system that communicates with reticle, slit, process, and wafer data units to generate and control doses based on current and previous mask, slit, and wafer conditions, including mask error enhancement factor and topography information, enabling direct use of mask data for dose correction without requiring new measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual dose correction methods are used, then setup time is prolonged, but manufacturing precision can be maintained
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing dose correction maps for multiple masks and scanner conditions before actual production. The automated system prepares correction data in advance based on mask metadata and scanner calibration information, so that when production begins, the corrections are immediately available without time-consuming manual setup procedures.
Solution Approach 2:
The system creates copies of dose correction maps from reference data and applies them to new masks through automated transformation. Instead of measuring every new mask manually, the system generates corrected dose maps by copying and adapting correction patterns from existing reference corrections, significantly reducing setup time while maintaining precision.
2Manufacturing precision
If mask and scanner data are not utilized, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The system introduces intermediary data structures and processing layers that mediate between raw mask/scanner data and the final dose correction maps. These intermediaries include standardized data formats, automated parsing modules, and transformation algorithms that convert complex raw data into usable correction parameters, making the system more precise without proportionally increasing operational complexity.
Solution Approach 2:
The system implements universal data processing components that handle multiple types of mask and scanner data through unified algorithms. A single automated pipeline processes various data formats and conditions, making the system versatile and reducing overall complexity by using general-purpose processing modules rather than specialized handlers for each data type.
3Productivity
If new measurements are required for each mask, then manufacturing precision is maintained, but productivity decreases
Solution Approach 1:
The system performs preliminary characterization of mask and scanner conditions during setup, storing correction data that can be reused for production. By conducting measurements and calculations in advance during mask loading and scanner calibration, the system eliminates the need for repeated measurements during actual dose correction operations, significantly improving productivity while maintaining accuracy through stored reference data.
Solution Approach 2:
The system implements feedback mechanisms where measured corrections are fed back into the correction maps and stored for future use. Measurement data from initial characterizations is used to generate correction maps that are then applied to subsequent production runs, creating a feedback loop that maintains precision without requiring repeated measurements. The system continuously refines corrections based on feedback from process monitoring.
Data Source
AI summary
A system and method are provided for automatic dose-correction recipe generation, the system including a dose-correction recipe generator, a reticle data unit in signal communication with the recipe generator, a slit data unit in signal communication with the recipe generator, a process data unit in signal communication with the recipe generator, a wafer data unit in signal communication with the recipe generator, a control unit in signal communication with the recipe generator, and an output unit or a storage unit in signal communication with the control unit; and the method including receiving a current reticle data set and a previous reticle data set, receiving a current slit data set and a previous slit data set, receiving a process condition, receiving a wafer condition, automatically generating a dose-correction recipe in accordance with the received reticle, slit, process and wafer information, and controlling a dose in accordance with the generated recipe.