Evidence map›Paper›PMID 36459274›Full record

ArticleNano convergence2022

Near-field infrared nanoscopic study of EUV- and e-beam-exposed hydrogen silsesquioxane photoresist.

Jiho Kim, Jin-Kyun Lee, Boknam Chae, Jinho Ahn, Sangsul Lee

Abstract read
In one paragraph

Article in Nano convergence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

5 authors.

Jiho KimPohang Accelerator Laboratory, POSTECH, Pohang, 37673, Republic of Korea.
Jin-Kyun LeeDepartment of Polymer Science and Engineering, Inha University, Incheon, 22212, Republic of Korea.
Boknam ChaePohang Accelerator Laboratory, POSTECH, Pohang, 37673, Republic of Korea.
Jinho AhnDivision of Materials Science and Engineering, Hanyang University, Seoul, 04763, Republic of Korea. jhahn@hanyang.ac.kr.
Sangsul LeePohang Accelerator Laboratory, POSTECH, Pohang, 37673, Republic of Korea. sangsul@postech.ac.kr.ORCID http://orcid.org/0000-0003-4697-1462

Funding

National Research Foundation of Korea NRF-2020M3H4A3081917Samsung Research Funding & Incubation Center of Samsung Electronics SRFC-TA1703-051
6 · The paper itself

Abstract

This article presents a technique of scattering-type scanning near-field optical microscopy (s-SNOM) based on scanning probe microscopy as a nanoscale-resolution chemical visualization technique of the structural changes in photoresist thin films. Chemical investigations were conducted in the nanometer regime by highly concentrated near-field infrared on the sharp apex of the metal-coated atomic force microscopy (AFM) tip. When s-SNOM was applied along with Fourier transform infrared spectroscopy to characterize the extreme UV- and electron-beam (e-beam)-exposed hydrogen silsesquioxane films, line and space patterns of half-pitch 100, 200, 300, and 500 nm could be successfully visualized prior to pattern development in the chemical solutions. The linewidth and line edge roughness values of the exposed domains obtained by s-SNOM were comparable to those extracted from the AFM and scanning electron microscopy images after development. The chemical analysis capabilities provided by s-SNOM provide new analytical opportunities that are not possible with traditional e-beam-based photoresist measurement, thus allowing information to be obtained without interference from non-photoreaction processes such as wet development.

Indexed as

Hydrogen silsesquioxane (HSQ)Infrared nanoscopyNanoscale chemical visualizationPhotoreactionPhotoresistPhotoresist metrologyScattering-type scanning near-field optical microscope (s-SNOM)

Identifiers

PMID36459274
PMCPMC9718909

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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.