ArticleACS omega2022
Unraveling the Mechanism of Maskless Nanopatterning of Black Silicon by CF
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- All silicon MIR super absorber using fractal metasurfaces.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The process of deep texturization of the crystalline silicon surface is intimately related to its promising diverse applications, such as bactericidal surfaces for integrated lab-on-chip devices and absorptive optical layers (black silicon-BSi). Surface structuring by a maskless texturization appeals as a cost-effective approach, which is up-scalable for large-area production. In the case of silicon, it occurs by means of reactive plasma processes (RIE-reactive-ion etching) using fluorocarbon CF
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Registered trials
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.