Evidence map›Paper›PMID 33846583›Full record

ArticleNature materials2021

Three-dimensional nanolithography guided by DNA modular epitaxy.

Jie Shen, Wei Sun, Di Liu, Thomas Schaus, Peng Yin

Abstract read
PubMed Publisher
In one paragraph

Article in Nature materials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Dynamics of DNA Origami Lattices.Bioconjugate chemistry · 2023
    Review
  13. Review
  14. Article
  15. 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.

Jie ShenWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-1671-007X
Wei SunWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0003-4145-1994
Di LiuWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-0708-7466
Thomas SchausWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4881-4156
Peng YinWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. py@hms.harvard.edu.ORCID http://orcid.org/0000-0002-2769-6357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lithographic scaling of periodic three-dimensional patterns is critical for advancing scalable nanomanufacturing. Current state-of-the-art quadruple patterning or extreme-ultraviolet lithography produce a line pitch down to around 30 nm, which might be further scaled to sub-20 nm through complex post-fabrication processes. Herein, we report the use of three-dimensional (3D) DNA nanostructures to scale the line pitch down to 16.2 nm, around 50% smaller than state-of-the-art results. We use a DNA modular epitaxy approach to fabricate 3D DNA masks with prescribed structural parameters (geometry, pitch and critical dimensions) along a designer assembly pathway. Single-run reactive ion etching then transfers the DNA patterns to a Si substrate at a lateral critical dimension of 7 nm and a vertical critical dimension of 2 nm. The nanolithography guided by DNA modular epitaxy achieves a smaller pitch than the projected values for advanced technology nodes in field-effect transistors, and provides a potential complement to the existing lithographic tools for advanced 3D nanomanufacturing.

Indexed as

DNANanostructuresDNA

Identifiers

What OpenQuestion holds

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Registered trials

None linked

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.