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As the cell size of memory devices continues to shrink, tighter on-product overlay (OPO) specs require more accurate and robust overlay control. The overlay error budget mainly consists of the reticle, scanner, process, and metrology errors. The metrology budget is generally required to be <10% of the OPO control budget so that the accuracy and robustness of overlay metrology become more crucial as pattern size gets smaller on current 1x nm DRAM nodes. For overlay control in high-volume manufacturing (HVM), the primary optical overlay metrology typically used is Image-Based Overlay (IBO). In many cases, scatterometry overlay (SCOL), using a direct grating-scanning method, was shown to achieve more accurate After Development Inspection (ADI) overlay measurements. Using a tunable source and customized illumination pupil to directly scan within the grating cell, this technology improves accuracy by reducing the contribution of pattern surroundings in the scribe line, resulting in improved OPO control stability. Since the purpose of overlay control is to minimize actual device pattern misregistration, as measured after the etching process (AEI), achieving accurate and stable characterization of the systematic deviation between ADI and AEI overlay known as Non-Zero-Offset (NZO) is critically important. Accurate NZO applied to the scanner via the Advanced-Process-Control (APC) loop enables effective scanner overlay control at the post-lithography ADI step. This paper demonstrates a new scatterometry overlay technology adopted in DRAM use cases that resulted in OPO and NZO stability improvement. In addition, we demonstrate an efficient method to monitor HVM run-to-run overlay performance and NZO stability by comprehensive dataset modeling combining ADI and AEI.

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Total measurement uncertainty (TMU) is a commonly used key performance indicator (KPI) for tool-induced error in metrology systems. Several definitions of TMU are being used today for overlay metrology (OVL), with the leading definition being the root-sum-square (RSS) of three other KPIs: the wafer mean Tool Induces Shift (TIS𝜇), the wafer variability of TIS (TIS3σ), and the OVL measurement reproducibility (OVL precision). A multitude of TIS management methods has been developed and implemented over the years for calibrating out the raw TIS from OVL. With these TIS management methods in place, the use of the raw TISμ and TIS3σ in TMU no longer serves as a good characterization of the total tool-induced error. In this paper, we describe a procedure for evaluating the actual, post-TIS management, OVL Metrology TMU through the introduction of two new wafer level indicators: the effective wafer means TIS (eTISμ), and the effective wafer TIS variability (eTIS3σ).

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