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Record W3136710475 · doi:10.1002/nano.202000244

Cerium doped ZIF nanoparticles and hydroxyapatite co‐deposited coating on titanium dioxide nanotubes array exhibiting biocompatibility and antibacterial property

2021· article· en· W3136710475 on OpenAlex
Ziqi Zhang, Yan Zhang, Yingqi Liu, Siqi Zhang, Kaida Yao, Yueqiu Sun, Yang Liu, Xiangzhi Wang, Weimin Huang, Jun Lu

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

VenueNano Select · 2021
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMinistry of Education and Child Care
FundersState Key Laboratory of Supramolecular Structure and MaterialsPeople's Government of Jilin ProvinceNatural Science Foundation of Jilin Province
KeywordsMaterials scienceCeriumBiocompatibilityTitanium dioxideNanoparticleCoatingCorrosionChemical engineeringCerium oxideAnodizingAlloyComposite numberCeramicPorosityOxideNanotechnologyMetallurgyComposite material

Abstract

fetched live from OpenAlex

Abstract Cerium has been used as an implanted alloy additive for many years for it can enhance the mechanical properties of the alloy and restrain the corrosion of the implant. Moreover, cerium oxide nanoparticles are often used as an antibacterial material. However, there were few researches focusing on the antibacterial properties of Ce 3+ and Ce 4+ ions, instead of their corresponding oxide, as potential antibacterial coatings. Thus in this work, we loaded Ce ions into the porous structure of the ZIF‐8 nanoparticles and co‐deposited them with hydroxyapatite as a composite coating onto anodized titanium dioxide nanotubes array in order to test whether it can improve the anti‐corrosion and antibacterial properties of the materials without affecting the biocompatibility.

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 categoriesMeta-epidemiology (narrow)
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 score0.009
Threshold uncertainty score1.000

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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