Evidence map›Paper›PMID 35424419›Full record

ArticleRSC advances2021

Study of aerodynamic focusing lens stacks (ALS) for long focal length aerosol-assisted focused chemical vapor deposition (AAFCVD).

Han Lun Lu, Lei Li, Xi Hui Liang, Jun Jun Wang, Ning Yang Liu, Zhi Tao Chen

Abstract read
In one paragraph

Article in RSC advances, 2021. 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

6 authors.

Han Lun LuInstitute of Semiconductors, Guangdong Academy of Sciences Guangzhou 510650 PR China henserlu@sohu.com iamlpo@126.com.ORCID https://orcid.org/0000-0002-6090-0460
Lei LiGuangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Institute of Mass Spectrometry and Atmospheric Environment, Jinan University Guangzhou 510632 PR China.
Xi Hui LiangInstitute of Semiconductors, Guangdong Academy of Sciences Guangzhou 510650 PR China henserlu@sohu.com iamlpo@126.com.ORCID https://orcid.org/0000-0002-3945-0995
Jun Jun WangInstitute of Semiconductors, Guangdong Academy of Sciences Guangzhou 510650 PR China henserlu@sohu.com iamlpo@126.com.
Ning Yang LiuInstitute of Semiconductors, Guangdong Academy of Sciences Guangzhou 510650 PR China henserlu@sohu.com iamlpo@126.com.
Zhi Tao ChenInstitute of Semiconductors, Guangdong Academy of Sciences Guangzhou 510650 PR China henserlu@sohu.com iamlpo@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mask-free direct printing can alleviate the high cost and high consumption involved in photo-lithography for chip processing. Most of their technical routes are based on the traditional short focal length nozzles, which is suffered from higher probability of nozzle retardation or clogging as well as the higher mechanical burdens. While aerosol-assisted chemical vapor deposition (AACVD) has better deposition adaptability but usually lack of focused printing. In this study, a system that combines of long focal length ALS with AACVD, so called AAFCVD printing system has been developed. The single-point printing capability and aerosol precursor adaptability were verified, and the relationship between the single spot printing performance and the chemical reaction mechanisms were studied. Furthermore, a unique carbon injection effect brought by ALS was discovered. Finally, the linear graphics printing performances of the system were evaluated. This system is expected to become a new generation of high-performance mask-free printing system for chip manufacturing.

Identifiers

PMID35424419
PMCPMC8694530

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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.