Evidence map›Paper›PMID 42280520›Full record

ArticlePolymers2026

Rheological and Structural Evaluation of Dental Flowable Composites for Optimized Performance in Transparent Aligner Systems.

Elena Palmieri, Maria Elena Cataldi, Loredana Cerroni, Luca Montaina, Matteo Bonomo, Gaetana Petrone, Denise Bellisario, Leonardo Mattiello, Guido Pasquantonio, Andrea Liscio and 3 more

Abstract read
In one paragraph

Article in Polymers, 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

13 authors.

Elena PalmieriInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.ORCID 0000-0002-0977-1528
Maria Elena CataldiDepartment of Clinical Sciences and Translational Medicine, University of Rome "Tor Vergata", Via Montpellier, 1, 00133 Rome, Italy.
Loredana CerroniDepartment of Clinical Sciences and Translational Medicine, University of Rome "Tor Vergata", Via Montpellier, 1, 00133 Rome, Italy.ORCID 0000-0001-7888-4895
Luca MontainaInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.
Matteo BonomoDepartment of Basic and Applied Science for Engineering, SBAI Sapienza, University of Rome, Via del Castro Laurenziano, 7, 00161 Rome, Italy.ORCID 0000-0002-1944-2664
Gaetana PetroneInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.ORCID 0000-0002-4612-2009
Denise BellisarioDepartment of Industrial Engineering, University of Rome "Tor Vergata", Via del Politecnico, 1, 00133 Rome, Italy.ORCID 0000-0001-5588-8738
Leonardo MattielloDepartment of Basic and Applied Science for Engineering, SBAI Sapienza, University of Rome, Via del Castro Laurenziano, 7, 00161 Rome, Italy.ORCID 0000-0002-9517-0226
Guido PasquantonioDepartment of Clinical Sciences and Translational Medicine, University of Rome "Tor Vergata", Via Montpellier, 1, 00133 Rome, Italy.
Andrea LiscioInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.ORCID 0000-0003-2986-3398
Francesco MaitaInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.ORCID 0000-0002-0822-2850
Luca MaioloInstitute for Microelectronics and Microsystems, National Research Council, CNR-IMM, Via del Fosso del Cavaliere, 100, 00133 Rome, Italy.ORCID 0000-0003-3220-5353
Roberta CondòDepartment of Clinical Sciences and Translational Medicine, University of Rome "Tor Vergata", Via Montpellier, 1, 00133 Rome, Italy.ORCID 0000-0003-2139-7927

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear aligner therapy (CAT) increasingly relies on composite-based attachments to improve force transmission and aligner retention, yet the role of flowable composite properties in clinical performance remains poorly understood. In this study, five commercially available flowable composites used for orthodontic attachments-Aligner FLOW LC, SIMPLY SHADE, SOFT ENA Flow, TETRIC EvoFlow, and VENUS Bulk Flow One-were comparatively investigated through physicochemical, morphological, optical, thermal, and rheological characterization. Scanning electron microscopy coupled with energy-dispersive X-ray analysis, thermogravimetric analysis, UV-Vis-NIR and ATR-FTIR spectroscopy, and rheological measurements before and after curing were employed to probe composition, filler content, viscoelastic behavior, and mechanical response. The results revealed marked differences among the investigated materials, with post-curing storage modulus spanning nearly two orders of magnitude, from 0.06 MPa for SOFT ENA Flow to approximately 5 MPa for SIMPLY SHADE. Similarly, the elastic modulus ranged from about 20 MPa to nearly 1000 MPa for the softest and stiffest resins, respectively. Interestingly, SOFT ENA Flow, the softest material after curing, also exhibited the highest pre-curing viscosity, nearly one order of magnitude greater than the least viscous resin, Aligner FLOW LC. These findings highlight an intrinsic trade-off between pre-cure processability and post-cure mechanical stability, providing a rational framework for material selection in orthodontic attachments and supporting more predictable and durable CAT outcomes.

Indexed as

filler–matrix interactionflowable resin compositespolymeric dental materialsrheological behavior

Identifiers

PMID42280520
PMCPMC13259519

What OpenQuestion holds

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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.