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Record W4391786670 · doi:10.2341/23-025-l

Effect of Radiant Exposure on the Physical and Mechanical Properties of 10 Flowable and High-viscosity Bulk-fill Resin Composites

2024· article· en· W4391786670 on OpenAlexaff
RA de Deus, LRS Oliveira, SSL Braga, MTH Ribeiro, Richard Bengt Price, Alejandra Núñez, Alessandro Dourado Loguércio, Carlos José Soares

Bibliographic record

VenueOperative Dentistry · 2024
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceComposite materialRadiodensityShrinkage

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the effect of the different radiant exposures from a multipeak light curing unit on the physical and mechanical properties of flowable and high-viscosity bulk-fill resin-based composites (RBC). METHODS: Five flowable bulk-fill RBCs (Tetric N-Flow Bulk-fill, Ivoclar Vivadent; Filtek Bulk Fill Flow, 3M Oral Care; Opus Bulk Fill Flow APS, FGM; Admira Fusion x-base, Voco and; and SDR Plus Bulk Fill Flowable, Dentsply Sirona) and five high-viscosity bulk-fill RBCs (Tetric N-Ceram Bulk-fill, Ivoclar Vivadent; Filtek One Bulk Fill, 3M Oral Care; Opus Bulk Fill APS, FGM; Admira Fusion x-tra, Voco; and SonicFill 2, Kerr) were photo-cured using a VALO Cordless light (Ultradent) for 10, 20, and 40 seconds at an irradiance of 1200, 800, or 400 mW/cm2, resulting in the delivery of 4, 8, 12, 16, 24, 32, or 48 J/cm2. Post-gel shrinkage (Shr) was calculated using strain-gauge test. The degree of conversion (DC, %) was calculated using FTIR. Knoop hardness (KH, N/mm2) and elastic modulus (E, MPa) were measured at the top and bottom surfaces. Logarithmic regressions between the radiant exposures and mechanical properties were calculated. Radiodensity was calculated using digital radiographs. Data of Shr and radiodensity were analyzed using two-way analysis of variance (ANOVA), and the DC, KH, and E data were analyzed with two-way ANOVA using split-plot repeated measurement tests followed by the Tukey test (a = 0.05). RESULTS: Delivering higher radiant exposures produced higher Shr values (p<0.001) and higher DC values (R2=0.808-0.922; R2=0.648-0.914, p<0.001), KH (R2=0.707-0.952; R2=0.738-0.919; p<0.001), and E (R2=0.501-0.925; R2=0.823-0.919; p<0.001) values for the flowable and high-viscosity RBCs respectively. Lower KH, E and Shr were observed for the flowable bulk-fill RBCs. All bulk-fill RBCs had a radiopacity level greater than the 4-mm thick aluminum step wedge. The radiant exposure did not affect the radiopacity. CONCLUSION: The Shr, DC, KH, and E values were highly correlated to the radiant exposure delivered to the RBCs. The combination of the higher irradiance for longer exposure time that resulted in radiant exposure between 24 J/cm2 to 48 J/cm2 produced better results than delivering 400 mW/cm2 for 40 s (16 J/cm2), and 800 mW/cm2 for 20 seconds (16 J/cm2) or 1200 mW/cm2 for 10 seconds (12 J/cm2). All the bulk-fill RBCs were sufficiently radiopaque compared to 4 mm of aluminum.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.270
Teacher spread0.257 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2024
Admission routes1
Has abstractyes

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