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Evaluating the Impact of Emerging Contaminants on Membrane Performance in Ultrapure-Water Production for Semiconductor Manufacturing: A PRISMA-Directed Meta-Analysis

IEEE Transactions on Semiconductor Manufacturing 2026
Hafiz Usama Tanveer, Hasham Tanveer, Sheeza Fatima, Rai Faisal Aslam, Hamza Tanveer, Muhammad Hashier Muneeb Farrukh

Summary

This meta-analysis evaluated how emerging contaminants — including PFAS, pharmaceuticals, and microplastics — compromise membrane filtration systems used to produce ultrapure water for semiconductor manufacturing. The findings show these contaminants can cause fouling and reduce membrane performance, posing risks to manufacturing quality at sub-5nm chip geometries.

Study Type Review

Ultrapure water (UPW) is indispensable in semiconductor manufacturing, where it serves as the foundational input for wafer cleaning, chemical dilution, and rinsing steps. As device geometries shrink below 5 nm, even parts-per-trillion (ppt) levels of contaminants can compromise yield, reliability, and compliance with industry standards such as SEMI F63 and ASTM D5127. Emerging contaminants (ECs) including per- and polyfluoroalkyl substances (PFAS), pharmaceuticals and personal care products (PPCPs), chemical mechanical planarization (CMP) organics, and micro/nanoplastics pose new challenges for membrane-based UPW treatment systems, especially under evolving regulations like the EPA PFAS Rule (2024). This PRISMA-guided meta-analysis evaluates 31 peer-reviewed studies (2002–2025) to quantify how reverse osmosis (RO), nanofiltration (NF), and ultrafiltration (UF) membranes perform under EC exposure. RO consistently achieved >99% rejection for long-chain PFAS and PPCPs but showed lower efficacy (93.8–99.2%) for short-chain compounds. NF demonstrated variable rejection (86–98%) depending on compound characteristics but offered energy savings in suitable contexts. UF was effective for microplastics but suffered significant flux decline (15–45%) with CMP-related organics. These findings offer critical, data-driven insights for semiconductor facilities seeking to maintain compliance, reduce operating costs, and optimize yield amid stricter water quality demands.

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