Evidence map›Paper›PMID 39343798›Full record

ArticleScientific reports2024

Influence of various cleaning solutions on the geometry, roughness, gloss, hardness, and flexural strength of 3D-printed zirconia.

HongXin Cai, Min-Yong Lee, Heng Bo Jiang, Jae-Sung Kwon

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

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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

4 authors.

HongXin CaiDepartment and Research Institute of Dental Biomaterials and Bioengineering, Yonsei University College of Dentistry, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Min-Yong LeeDepartment and Research Institute of Dental Biomaterials and Bioengineering, Yonsei University College of Dentistry, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Heng Bo JiangDepartment of Stomatological Technology, School of Stomatology, Shandong First Medical University, Jinan, 250117, Shandong, China.
Jae-Sung KwonDepartment and Research Institute of Dental Biomaterials and Bioengineering, Yonsei University College of Dentistry, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. jkwon@yuhs.ac.

Funding

National Research Foundation of Korea 2022R1C1C1010304
6 · The paper itself

Abstract

This study aimed to investigate the impact of various cleaning solutions on the geometry, roughness, gloss, hardness, and flexural strength of 3D-printed zirconia. Cleaning solutions, including isopropyl alcohol (IPA, 99.9%), ethyl alcohol (EtOH, 99.9%), and tripropylene glycol monomethyl ether (TPM, ≥ 97.5%), were diluted to a concentration of 70% and categorized into six groups: IPA99, EtOH99, TPM97, IPA70, EtOH70, and TPM70. Zirconia discs, printed via digital light processing, were sintered after cleaning. The geometry, roughness, gloss, hardness, and flexural strength were analyzed. Statistical analysis was performed using one-way ANOVA with Tukey's post hoc test (p < 0.05). The thickness of TPM70 was the highest. The diameter of TPM70 was significantly larger than that of EtOH99 and IPA70 (p < 0.05). The weight of the TPM groups was significantly higher than that of IPA70 (p < 0.05). The roughness Ra of TPM70 was significantly greater than that of IPA99, EtOH99, and EtOH70 (p < 0.05). The differences in surface gloss, hardness, and flexural strength among the different groups were not statistically significant (p > 0.05). Different cleaning solutions did not affect the surface gloss, hardness, and flexural strength of 3D-printed zirconia. High and low concentrations of the same cleaning solution did not affect the surface gloss, hardness, and flexural strength. IPA70, TPM97, and EtOH can be considered viable post-printing cleaning alternatives to the traditional gold standard, IPA99.

Indexed as

Additive manufacturingCeramicCleaning solutionPost-processing

Identifiers

PMID39343798
PMCPMC11439905

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LicenceCC BY-NC-ND
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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.