Evidence map›Paper›PMID 42098168›Full record

ArticleScientific data2026

Rheological Measurement Dataset of Resin and Composite Mixtures for Digital Light Processing based Additive Manufacturing.

Caleb Beckwith, Nikhil Gupta

Abstract read
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Caleb BeckwithComposite Materials and Mechanics Laboratory, Mechanical and Aerospace Engineering Department, New York University Tandon School of Engineering, Brooklyn, NY, 11201, USA. Cib2783@nyu.edu.
Nikhil GuptaComposite Materials and Mechanics Laboratory, Mechanical and Aerospace Engineering Department, New York University Tandon School of Engineering, Brooklyn, NY, 11201, USA.

Funding

Directorate for Engineering CMMI-2036802
6 · The paper itself

Abstract

This work features a dataset intended to aid in the development of processing parameters for particulate composite materials for additive manufacturing (AM) using digital light processing (DLP) method. Hollow glass microspheres (HGMs) are used as particulate fillers to manufacture syntactic foam composites. The standard thermosetting resins have a recommended set of 3D printing parameters. However, when the particles are mixed to 3D print composites, the mixture properties change, and the processing parameters need to be adjusted according to the particle volume fraction, size and other parameters. This dataset provides rheological measurements on the neat resin and resin-HGM composite mixtures intended for vat photopolymerization (VP) based DLP method. Three HGM density grades (0.13, 0.23, and 0.31 g/cm³ true particle densities) were examined at 10, 20, and 40 vol.% to capture the effects of particle density and volume fraction on resin flow behavior. Viscosity was measured using an Anton Paar MCR702 analyzer at a range of shear rates (1-50 s⁻¹) and temperatures (35-125 °C), generating 50 independent data files for 5 trials repeated for each of the 10 compositions. The dataset records the coupled influence of temperature and shear rate for each composition, providing a foundation for modeling viscosity-shear rate-temperature-composition relationships. Interpolations of various parameters at a benchmark viscosity of 0.40 Pa·s enable extraction of processing windows relevant to VP of the composite mixtures and significantly reduce the trial and error involved in processing parameter optimization for composite mixtures. The dataset also includes µCT image stacks for representative specimens, supporting qualitative assessment of particle dispersion and internal structure.

Identifiers

PMID42098168
PMCPMC13365189

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Registered trials

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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.