In-situ cavitation measurements with a wireless sensor array: applications in megasonic photomask cleaning

Acoustic cavitation continues to be widely used in advanced 193i and EUV megasonic photomask cleaning [1]. However, process challenges remain complex as patterns become smaller [2], denser, and more irregular in shape. For instance, the wide adoption of curvilinear ILT patterns is imminent to defend against shrinking process windows. Operating within a narrow process window that ensures both full particle removal and pattern damage control is a balancing act that requires many parameters to be optimized and controlled. These include the transducer type, drive frequency, power setting, flow rate, gas concentration, temperature, chemistry, and transducer position [3, 4, 5, 6, 7]. While batch processing may be more economical for less critical cleaning steps, advanced lithography processes rely on single photomask cleaning technologies because of the increased need for within mask control. Improved cleaning uniformity is achieved through the continuous movement of the photomask and transducer. correlate acoustic parameters with cleaning performance, an in-situ measurement of the acoustic field is required. Previous work introduced a photomask-shaped cavitation sensor array wired to a cavitation meter which characterized how acoustic cavitation varied with parameters such as drive frequency, generator power, transducer distance, and sensor position were correlated with cavitation pressure under a static condition [7]. In this study, the technology was extended by developing a wireless sensor array to incorporate the dynamic effects of the photomask rotation and the transducer arm translation. The acoustic pressure uniformity across the photomask was evaluated for varying parameters, including mask rotational speed, transducer arm speed, and exposure time. Pressure measurements of the direct field, stable cavitation, and transient cavitation exhibited distinct signatures that may be indicative of cleaning performance, specifically particle removal or pattern damage. The high costs of advanced photomask processes have demanded a zero-defect requirement, a constraint prevalent across the semiconductor industry [8]. The aim of the study is to better understand how process variables affect the acoustic performance to ultimately establish a process control strategy.