ACM Research, Inc. (ACM) (NASDAQ: ACMR), a supplier of wafer processing solutions for semiconductor and advanced wafer-level packaging (WLP) applications, today announced volume purchase orders for 29 Ultra C wb wet bench tools for 300 mm wafer applications. The orders are from multiple China-based customers, and include repeat orders for 16 tools from an emerging foundry customer to support its ongoing fab expansion. Shipments are scheduled in two phases, beginning in the first half of 2022.
“Our wet bench systems were developed to meet our customers’ needs for a full range of wet cleaning technologies across multiple nodes,” said Dr. David Wang, ACM’s President and CEO. “These orders validate ACM’s strategy to expand our portfolio beyond advanced cleaning with a highly competitive product offering. Securing volume orders from new and repeat customers speaks to our success—both with the foundry customer and the broader wet bench market. We view this as a clear demonstration of our technical capability, our growing market leadership and our ability to respond to customer demand. Together with our advanced dry technologies, ACM’s bench products can cover almost all cleaning process steps that require bench cleaning.”
Additionally, ACM today introduced its Ultra Low Pressure Dry (ULD) technology for 300 mm bench systems. The process is specifically designed to mitigate post-bench clean drying challenges associated with high-aspect-ratio structures of 3D NAND and logic devices on advanced semiconductor wafers. ACM’s new ULD bench module uses a low-pressure isopropyl alcohol (IPA) drying process to address these requirements for most bench clean dry processes, including pre-furnace clean, post-ion implant cleaning and post-dry-etch photoresist removal, post-chemical-mechanical planarization (CMP) cleaning, and pre-cleaning before film deposition, oxide etch and nitride removal. ACM shipped its first ULD module to a leading China-based memory semiconductor manufacturer in the third quarter of 2021, and ACM believes the initial process data validate the effectiveness of the ULD module in advanced node manufacturing.
