Evidence map›Paper›PMID 42513075›Full record

ReviewMicromachines2026

Mechanisms of Film-Formation-Related Defects in EUV Photoresists for Sub-3 nm Nodes and Synergistic Materials-Process-Intelligence Co-Optimization.

Junlin Wu, Yanqing Luo, Junzhe Hu, Shirong Li, Sen Cai, Tiedong Cheng, Ping Zhang, Pei Li, Shengkun Jiang, Ziqiang Liu and 3 more

Abstract readReview
In one paragraph

Review in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Junlin WuSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Yanqing LuoSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Junzhe HuSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Shirong LiSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Sen CaiSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Tiedong ChengSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.ORCID 0000-0003-2599-7823
Ping ZhangSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Pei LiSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Shengkun JiangSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Ziqiang LiuSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Guitai WuSchool of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.ORCID 0009-0005-1873-7275
Sergey Mikhailovich KopytovDepartment of Industrial Electronics, Komsomolsk-on-Amur State Technical University, Komsomolsk-on-Amur 681013, Russia.
Jin YangInstitute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China.

Funding

Jiangxi Provincial Department of Science and Technology 20242BCE0074Jiangxi Provincial Department of Science and Technology Nos. 20242BAB21001
6 · The paper itself

Abstract

With the advancement of High-NA EUV lithography and the continued evolution of transistor architectures toward GAA and CFET, semiconductor manufacturing has entered the sub-3 nm technology node era. At advanced nodes, photon shot noise becomes increasingly significant, while the process tolerance window narrows substantially. Photoresist film-formation-related defects may originate from multiple stages of the fabrication process, including coating, exposure, post-exposure bake, development, and etching/stripping, and are strongly influenced by microscopic stochastic effects. However, the isolated optimization of materials, processes, or intelligent control strategies still suffers from significant limitations. Therefore, this review systematically examines the formation mechanisms and cross-process evolution of photoresist film-formation-related defects within the development trajectory of advanced lithography. An integrated materials-process-intelligence co-optimization framework is proposed to elucidate the coupling mechanisms among these three dimensions and the construction of a full-chain closed-loop control strategy. The current challenges and future development directions are summarized, providing optimization insights for both academic research and industrial implementation. This review aims to establish a defect-control framework integrating fundamental understanding with engineering considerations, thereby supporting low defectivity, high robustness, and improved manufacturability for sub-3 nm node patterning.

Indexed as

chemically amplified resist (CAR)closed-loop co-optimizationdigital twinEUV lithographynon-chemically amplified resist (non-CAR)photoresist film-formation-related defectsprocess controlstochastic effectssub-3 nm nodevirtual metrology

Identifiers

PMID42513075
PMCPMC13413909

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.