Massive metrology using fast e-beam technology improves OPC model accuracy by >2x at faster turnaround time

2018 
Classical SEM metrology, CD-SEM, uses low data rate and extensive frame-averaging technique to achieve high-quality SEM imaging for high-precision metrology. The drawbacks include prolonged data collection time and larger photoresist shrinkage due to excess electron dosage. This paper will introduce a novel e-beam metrology system based on a high data rate, large probe current, and ultra-low noise electron optics design. At the same level of metrology precision, this high speed e-beam metrology system could significantly shorten data collection time and reduce electron dosage. In this work, the data collection speed is higher than 7,000 images per hr. Moreover, a novel large field of view (LFOV) capability at high resolution was enabled by an advanced electron deflection system design. The area coverage by LFOV is >100x larger than classical SEM. Superior metrology precision throughout the whole image has been achieved, and high quality metrology data could be extracted from full field. This new capability on metrology will further improve metrology data collection speed to support the need for large volume of metrology data from OPC model calibration of next generation technology. The shrinking EPE (Edge Placement Error) budget places more stringent requirement on OPC model accuracy, which is increasingly limited by metrology errors. In the current practice of metrology data collection and data processing to model calibration flow, CD-SEM throughput becomes a bottleneck that limits the amount of metrology measurements available for OPC model calibration, impacting pattern coverage and model accuracy especially for 2D pattern prediction. To address the trade-off in metrology sampling and model accuracy constrained by the cycle time requirement, this paper employs the high speed e-beam metrology system and a new computational software solution to take full advantage of the large volume data and significantly reduce both systematic and random metrology errors. The new computational software enables users to generate large quantity of highly accurate EP (Edge Placement) gauges and significantly improve design pattern coverage with up to 5X gain in model prediction accuracy on complex 2D patterns. Overall, this work showed >2x improvement in OPC model accuracy at a faster model turn-around time.
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