Evidence map›Paper›PMID 35478820›Full record

ArticleRSC advances2021

Hydrophilic modification of SLA 3D printed droplet generators by photochemical grafting.

Tristan W Bacha, Dylan C Manuguerra, Robert A Marano, Joseph F Stanzione

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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

9 citing papers in PubMed, 33 citations in OpenAlex.

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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 at 1 institution in 1 country.

Tristan W BachaDepartment of Chemical Engineering, Rowan University 201 Mullica Hill Rd, Glassboro NJ 08028 USA stanzione@rowan.edu.ORCID https://orcid.org/0000-0002-3562-1881
Dylan C ManuguerraDepartment of Chemical Engineering, Rowan University 201 Mullica Hill Rd, Glassboro NJ 08028 USA stanzione@rowan.edu.
Robert A MaranoDepartment of Chemical Engineering, Rowan University 201 Mullica Hill Rd, Glassboro NJ 08028 USA stanzione@rowan.edu.
Joseph F StanzioneDepartment of Chemical Engineering, Rowan University 201 Mullica Hill Rd, Glassboro NJ 08028 USA stanzione@rowan.edu.
Rowan University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Few droplet generators manufactured using desktop stereolithography 3D printers have been reported in the literature. Moreover, 3D printed microfluidic chips are typically hydrophobic, limiting their application to water in oil droplets. Herein, we present designs for concentric and planar 3D printed microfluidic devices suitable for making polymeric microparticles using an off-the-shelf commercial stereolithography printer and resin. The devices consist of a microscope slide, binder clips, and printed components. Channels were modified by an ultraviolet grafting of methacrylic acid to the surface of chips, yielding a hydrophilic coating without modification to the bulk polymer. The water contact angle decreased from 97.0° to 25.4° after grafting. The presence of the coating was confirmed by microscopy and spectroscopy techniques. Polystyrene microparticles in the <100 μm size range were generated with varying molecular weights using the described microfluidic chips. Our work provides a facile method to construct droplet generators from commercial stereolithography printers and resins, and a rapid surface modification technique that has been under-utilized in 3D printed microfluidics. A wide range of microfluidic devices for other applications can be engineered using the methods described.

Identifiers

PMID35478820
PMCPMC9034120
OpenAlexW3176390212

What OpenQuestion holds

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LicenceCC BY-NC
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.