Evidence map›Paper›PMID 28940164›Full record

ArticleNanoscale research letters2017

Fabrication of Nanoscale Pits with High Throughput on Polymer Thin Film Using AFM Tip-Based Dynamic Plowing Lithography.

Yang He, Yanquan Geng, Yongda Yan, Xichun Luo

Abstract read
In one paragraph

Article in Nanoscale research letters, 2017. 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. Article
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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

4 authors.

Yang HeThe State Key Laboratory of Robotics and Systems, Robotics Institute, Harbin Institute of Technology, Harbin, Heilongjiang, 150080, People's Republic of China.
Yanquan GengThe State Key Laboratory of Robotics and Systems, Robotics Institute, Harbin Institute of Technology, Harbin, Heilongjiang, 150080, People's Republic of China. gengyanquan@hit.edu.cn.
Yongda YanThe State Key Laboratory of Robotics and Systems, Robotics Institute, Harbin Institute of Technology, Harbin, Heilongjiang, 150080, People's Republic of China. yanyongda@hit.edu.cn.
Xichun LuoCentre for Precision Manufacturing, Department of Design, Manufacture and Engineering Management, University of Strathclyde, Glasgow, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We show that an atomic force microscope (AFM) tip-based dynamic plowing lithography (DPL) approach can be used to fabricate nanoscale pits with high throughput. The method relies on scratching with a relatively large speed over a sample surface in tapping mode, which is responsible for the separation distance of adjacent pits. Scratching tests are carried out on a poly(methyl methacrylate) (PMMA) thin film using a diamond-like carbon coating tip. Results show that 100 μm/s is the critical value of the scratching speed. When the scratching speed is greater than 100 μm/s, pit structures can be generated. In contrast, nanogrooves can be formed with speeds less than the critical value. Because of the difficulty of breaking the molecular chain of glass-state polymer with an applied high-frequency load and low-energy dissipation in one interaction of the tip and the sample, one pit requires 65-80 penetrations to be achieved. Subsequently, the forming process of the pit is analyzed in detail, including three phases: elastic deformation, plastic deformation, and climbing over the pile-up. In particular, 4800-5800 pits can be obtained in 1 s using this proposed method. Both experiments and theoretical analysis are presented that fully determine the potential of this proposed method to fabricate pits efficiently.

Indexed as

AFMDPLFast-scan nanolithographyNanogrooveNanoscale pitPMMA film

Identifiers

PMID28940164
PMCPMC5610139

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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.