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Record W3210981984 · doi:10.3390/polym13213794

Influence of TiO2 and ZrO2 Nanoparticles on Adhesive Bond Strength and Viscosity of Dentin Polymer: A Physical and Chemical Evaluation

2021· article· en· W3210981984 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymers · 2021
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
FundersKing Saud University
KeywordsBond strengthAdhesiveMaterials scienceViscosityPolymerDentinComposite materialNanoparticleChemical bondChemical engineeringNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The present study aimed to formulate an experimental adhesive (EA) and reinforce it with 5 wt.% titanium dioxide (TiO2) or zirconium oxide (ZrO2) to yield 5% TiO2 and 5% ZrO2 adhesives, respectively, and then analyze the impact of this reinforcement on various mechanical properties of the adhesives. The EA contained a blend of monomers such as bisphenol A glycol dimethacrylate (BisGMA), triethylene glycol dimethacrylate (TEGDMA), 2-hydroxyethyl methacrylate (HEMA), and ethyl 4-dimethylamino benzoate and camphorquinone. The EA included ethyl 4-dimethylamino benzoate and camphorquinone photo-initiators, and diphenyliodonium hexafluorophosphate (DPIHP) was also included to act as an electron initiator. The TiO2 and ZrO2 nanoparticles were incorporated into the EA post-synthesis. To characterize the filler nanoparticles, scanning electron microscopy (SEM) and line-energy dispersive X-ray (EDX) spectroscopy were performed. The adhesives were characterized by analyzing their rheological properties, shear-bond strength (SBS), and interfacial failure types. Further, the resin–dentin interface was also analyzed via SEM. The TiO2 nanoparticles were spherically shaped on the SEM micrographs, while the ZrO2 nanoparticles were seen as non-uniformly shaped agglomerates. The EDX mapping demonstrated the presence of Ti and oxygen for TiO2 and Zr and oxygen for the ZrO2 nanoparticles. Both 5% TiO2 and 5% ZrO2 adhesives revealed decreased viscosity as compared with the EA. The 5% TiO2 adhesive demonstrated higher SBS values for both non-thermocycled (NTC) and thermocycled samples (NTC: 25.35 ± 1.53, TC: 23.89 ± 1.95 MPa), followed by the 5% ZrO2 adhesive group (NTC: 23.10 ± 2.22, TC: 20.72 ± 1.32 MPa). The bulk of the failures (>70%) were of adhesive type in all groups. The SEM analysis of the resin–dentin interface revealed the development of a hybrid layer and resin tags (of variable depth) for the EA and 5% TiO2 groups. However, for the 5% ZrO2 group, the hybrid layer and resin tag establishment appeared compromised. Reinforcement of the EA with TiO2 or ZrO2 caused an increase in the adhesive’s SBS (with the 5% TiO2 group demonstrating the highest values) in comparison with the EA (without nanoparticles). However, both nanoparticle-containing adhesives revealed decreased viscosity compared with the EA (without nanoparticles). Further studies investigating the impact of diverse filler concentrations on the properties of adhesives are suggested.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.280
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it