Evidence map›Paper›PMID 40508738›Full record

ArticlePolymers2025

Investigation of Thermomechanical Properties of Hollow Glass Microballoon-Filled Composite Materials Developed by Additive Manufacturing with Machine Learning Validation.

Md Sakhawat Hossain, Sazid Noor Rabi, Sakib Mohammad, Kaden Cook, Farhan Chowdhury, Sabrina Nilufar

Abstract read
In one paragraph

Article in Polymers, 2025. 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. 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.

Md Sakhawat HossainSchool of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.ORCID 0009-0009-7588-7500
Sazid Noor RabiSchool of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.
Sakib MohammadSchool of Electrical, Computer, and Biomedical Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.ORCID 0009-0000-0692-2426
Kaden CookSchool of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.ORCID 0009-0002-7661-9822
Farhan ChowdhurySchool of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.ORCID 0000-0003-1527-2677
Sabrina NilufarSchool of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.

Funding

Single-molecule approaches to study epiblast stem cell fate decisionR15GM140448 · NIGMS · SOUTHERN ILLINOIS UNIVERSITY CARBONDALE · PI Farhan H Chowdhury · 2021 to 2026
$1.1M
National Science Foundation 2138459NIH HHS R15GM140448
6 · The paper itself

Abstract

Stereolithography (SLA) is a popular additive manufacturing (AM) method frequently used in research and various industrial sectors. The acrylate resin used in this research is renowned for its flexibility and durability, enabling the creation of flawless 3D-printed parts with exceptional mechanical properties. This study aims to enhance the thermomechanical properties of 3D-printed hollow glass microballoon (HGM)-filled composite materials by adding minimal HGM into the acrylate resin. We investigated the material properties through uniaxial compression tests, dynamic mechanical analysis (DMA), and scanning electron microscopy (SEM). To validate the results, a numerical investigation and a machine learning (ML) approach were carried out and compared with the experimental results. Adding a small number of microballoons increases compressive strength and stiffness. The viscoelastic behavior of the samples also provides an estimate of resilience at higher temperatures, considering the addition of filler material into the resin. Our study shows that the addition of 0.04% of HGM increased compressive strength by around 99.30% compared to the neat sample, while the stiffness increased by around 31.42% compared to the neat sample at 0.05% of HGM. It can also be estimated that the suitable range of HGM addition for the resin we used exists between 0.04% and 0.05%, where the materials achieve their maximum strength and stiffness. In addition, a predictive machine learning (ML) model, namely Random Forest Regressor (RFR), shows low mean squared error (MSE), mean absolute error (MAE), and excellent R

Indexed as

dynamic mechanical analysisfinite element methodhollow glass microballoonmachine learningrepresentative volume elementstereolithography

Identifiers

PMID40508738
PMCPMC12157956

What OpenQuestion holds

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LicenceCC BY
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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.