Evidence map›Paper›PMID 30424318›Full record

ArticleMicromachines2018

Anti-Reflectance Optimization of Secondary Nanostructured Black Silicon Grown on Micro-Structured Arrays.

Xiao Tan, Zhi Tao, Mingxing Yu, Hanxiao Wu, Haiwang Li

Abstract read
In one paragraph

Article in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

5 authors.

Xiao TanSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China. by1404143@buaa.edu.cn.ORCID 0000-0001-7225-0162
Zhi TaoSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China. tao_zhi@buaa.edu.cn.
Mingxing YuSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China. yumingxing1314@126.com.
Hanxiao WuSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China. hanxiao_wu_buaa@163.com.
Haiwang LiSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China. 09620@buaa.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Owing to its extremely low light absorption, black silicon has been widely investigated and reported in recent years, and simultaneously applied to various disciplines. Black silicon is, in general, fabricated on flat surfaces based on the silicon substrate. However, with three normal fabrication methods-plasma dry etching, metal-assisted wet etching, and femtosecond laser pulse etching-black silicon cannot perform easily due to its lowest absorption and thus some studies remained in the laboratory stage. This paper puts forward a novel secondary nanostructured black silicon, which uses the dry-wet hybrid fabrication method to achieve secondary nanostructures. In consideration of the influence of the structure's size, this paper fabricated different sizes of secondary nanostructured black silicon and compared their absorptions with each other. A total of 0.5% reflectance and 98% absorption efficiency of the pit sample were achieved with a diameter of 117.1 μm and a depth of 72.6 μm. In addition, the variation tendency of the absorption efficiency is not solely monotone increasing or monotone decreasing, but firstly increasing and then decreasing. By using a statistical image processing method, nanostructures with diameters between 20 and 30 nm are the majority and nanostructures with a diameter between 10 and 40 nm account for 81% of the diameters.

Indexed as

absorptionblack siliconsecondary nanostructures

Identifiers

PMID30424318
PMCPMC6187304

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.