Evidence map›Paper›PMID 35410416›Full record

ArticleNature communications2022

3D nanoprinting via spatially controlled assembly and polymerization.

Thomas G Pattison, Shuo Wang, Robert D Miller, Gang-Yu Liu, Greg G Qiao

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Dehydropolymerization of HACS catalysis · 2022
    Article
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.

Thomas G PattisonPolymer Science Group, Department of Chemical Engineering, The University of Melbourne, Parkville, VIC, 3010, Australia.ORCID http://orcid.org/0000-0002-3029-5896
Shuo WangDepartment of Chemistry, University of California, Davis, CA, 95616, USA.
Robert D MillerInternational Business Machines-Almaden Research Center, 650 Harry Road, San Jose, CA, 95120, USA.
Gang-Yu LiuDepartment of Chemistry, University of California, Davis, CA, 95616, USA. gyliu@ucdavis.edu.ORCID http://orcid.org/0000-0003-3689-0685
Greg G QiaoPolymer Science Group, Department of Chemical Engineering, The University of Melbourne, Parkville, VIC, 3010, Australia. gregghq@unimelb.edu.au.ORCID http://orcid.org/0000-0003-2771-9675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macroscale additive manufacturing has seen significant advances recently, but these advances are not yet realized for the bottom-up formation of nanoscale polymeric features. We describe a platform technology for creating crosslinked polymer features using rapid surface-initiated crosslinking and versatile macrocrosslinkers, delivered by a microfluidic-coupled atomic force microscope known as FluidFM. A crosslinkable polymer containing norbornene moieties is delivered to a catalyzed substrate where polymerization occurs, resulting in extremely rapid chemical curing of the delivered material. Due to the living crosslinking reaction, construction of lines and patterns with multiple layers is possible, showing quantitative material addition from each deposition in a method analogous to fused filament fabrication, but at the nanoscale. Print parameters influenced printed line dimensions, with the smallest lines being 450 nm across with a vertical layer resolution of 2 nm. This nanoscale 3D printing platform of reactive polymer materials has applications for device fabrication, optical systems and biotechnology.

Indexed as

PolymersPrinting, Three-DimensionalPolymerizationTechnologyPolymers

Identifiers

PMID35410416
PMCPMC9001713

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.