Evidence map›Paper›PMID 29765086›Full record

ArticleScientific reports2018

Fabrication and characterization of a scalable surface textured with pico-liter oil drops for mechanistic studies of bacteria-oil interactions.

Maryam Jalali, Andrew R White, James Marti, Jian Sheng

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Maryam JalaliDepartment of Engineering, Texas A&M University, Corpus Christi, Texas, USA.
Andrew R WhiteDepartment of Engineering, Texas A&M University, Corpus Christi, Texas, USA.
James MartiNano Fabrication Center, University of Minnesota, Twin City, Minnesota, USA.
Jian ShengDepartment of Engineering, Texas A&M University, Corpus Christi, Texas, USA. jian.sheng@tamucc.edu.ORCID 0000-0002-8815-1051

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Texturing a large surface with oily micro-drops with controlled size, shape and volume provides an unprecedented capability in investigating complex interactions of bacteria, cells and interfaces. It has particular implications in understanding key microbial processes involved in remediation of environmental disasters, such as Deepwater Horizon oil spill. This work presents a development of scalable micro-transfer molding to functionalize a substrate with oily drop array to generate a microcosm mimicking bacteria encountering a rising droplet cloud. The volume of each drop within a large "printed" surface can be tuned by varying base geometry and area with characteristic scales from 5 to 50 μm. Contrary to macroscopic counterparts, drops with non-Laplacian shapes, i.e. sharp corners, that appears to violate Young-Laplacian relationship locally, are produced. Although the drop relaxes into a spherical cap with constant mean curvature, the contact line with sharp corners remains pinned. Relaxation times from initial to asymptotic shape require extraordinarily long time (>7 days). We demonstrate that non-Laplacian drops are the direct results of self-pinning of contact line by nanoparticles in the oil. This technique has been applied to study biofilm formation at the oil-water interface and can be readily extended to other colloidal fluids.

Indexed as

BacteriaBiodegradation, EnvironmentalModels, BiologicalOilsParticle SizePetroleum PollutionOils

Identifiers

PMID29765086
PMCPMC5954110

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.