Evidence map›Paper›PMID 29649239›Full record

ArticlePloS one2018

Using hydrodynamic focusing to predictably alter the diameter of synthetic silk fibers.

Bradley Hoffmann, Catherine Gruat-Henry, Pranothi Mulinti, Long Jiang, Benjamin D Brooks, Amanda E Brooks

Abstract read
In one paragraph

Article in PloS one, 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. Review
  2. Article
  3. Article
  4. Straining Flow Spinning of Artificial Silk Fibers: A Review.Biomimetics (Basel, Switzerland) · 2018
    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

6 authors.

Bradley HoffmannDepartment of Mechanical Engineering, North Dakota State University, Fargo, North Dakota, United States of America.ORCID 0000-0002-3855-5939
Catherine Gruat-HenryDepartment of Electrical Engineering, North Dakota State University, Fargo, North Dakota, United States of America.
Pranothi MulintiDepartment of Pharmaceutical Sciences, North Dakota State University, Fargo, North Dakota, United States of America.
Long JiangDepartment of Mechanical Engineering, North Dakota State University, Fargo, North Dakota, United States of America.
Benjamin D BrooksDepartment of Electrical Engineering, North Dakota State University, Fargo, North Dakota, United States of America.
Amanda E BrooksDepartment of Pharmaceutical Sciences, North Dakota State University, Fargo, North Dakota, United States of America.ORCID 0000-0001-9785-5969

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spiders and silkworms provide a model of superior processing for multifunctional and highly versatile high-performance fibers. Mimicking the spider's complex control system for chemical and mechanical gradients has remained an ongoing obstacle for synthetic silk production. In this study, the use of hydrodynamic fluid focusing within a 3D printed biomimetic spinning system to recapitulate the biological spinneret is explored and shown to produce predictable, small diameter fibers. Mirroring in silico fluid flow simulations using a hydrodynamic microfluidic spinning technique, we have developed a model correlating spinning rates, solution viscosity and fiber diameter outputs that will significantly advance the field of synthetic silk fiber production. The use of hydrodynamic focusing to produce controlled output fiber diameter simulates the natural silk spinning process and continues to build upon a 3D printed biomimetic spinning platform.

Indexed as

HydrodynamicsBiomimetic MaterialsRheologyShear StrengthSilkSilk

Identifiers

PMID29649239
PMCPMC5896967

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.