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Enregistrement W2286874765 · doi:10.1149/ma2015-01/17/1247

Electro-Polishing of Additive Manufactured Porous Titanium for Medical Implants

2015· article· en· W2286874765 sur OpenAlex

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Notice bibliographique

RevueECS Meeting Abstracts · 2015
Typearticle
Langueen
DomaineEngineering
ThématiqueAdditive Manufacturing and 3D Printing Technologies
Établissements canadiensMcGill UniversityConcordia University
Organismes subventionnairesnon disponible
Mots-clésPolishingPorosityMaterials scienceTitaniumMetallurgyComposite material

Résumé

récupéré en direct d'OpenAlex

Advances in Additive Manufacturing (AM) allow for high resolution fabrication of complex three dimensional structures. This enables the construction of fully porous lattice materials with tailored micro-architecture to achieve variable graded properties. One promising application of this approach is the development of graded open cell lattices for orthopaedic bone implants [1]. The use of a graded lattice allows for the material properties of the structure, including stiffness, to match those of the local host bone. In addition, the morphological parameters (including porosity, pore size, and diffusivity) of the individual lattice unit cell can be optimized to achieve optimal bone ingrowth and fixation for long-term implant success. Because of its bio-inertness and high strength, TI6Al4V is an appealing monolithic material for constructing fully porous lattice orthopaedic devices [2]. However, from the process of Direct Metal Laser Sintering (DMLS) and Electron Beam Melting (EBM) processes, semi-melted beads appear to be attached to the individual struts of the lattice. The beads used here generally range from 10-45 microns for DMLS and from 45-106 microns for EBM. The strut diameter of the lattice typically ranges from 150-300 microns. Because the designed strut diameter and bead size are of similar length scale, the addition of semi-melted beads can lead to significant discrepancies between the designed and manufactured strut thickness. This is especially prevalent in struts with thin diameter,near the resolution limit of AM. This discrepancy may induce morphological mismatches that negatively impact the lattice performance. Electrochemical polishing provides an interesting approach to control the reduction of semi-melted beads. This helps to ensure that the manufactured part is identical to the designed structure, allowing for the optimal performance of the implant. Electrochemical polishing can also be used for the creation of micro and nano-roughness surface modifications on the individual struts of the lattice, an outcome that can increase in-vitro cell response and in-vivo bone response [3]. The addition of surface roughness modifications imparted by electrochemical polishing may serve to further improve the bone tissue response of fully porous lattice implants. In this electrochemical process, mass transport controlled dissolution results in surface smoothing. Multiple parts with complex geometry can concurrently be polished. Preliminary results show the potential to use pulse technology (with pulse width of 50µs – 500µs, and duty cycle < 50%) that eliminates surface asperities more effectively than direct current. Surface roughness for a titanium work-piece of around R a = 4 nm could be obtained with a 4 hours treatment [4]. In the current study, electro-polishing was performed on a fully porous Ti6Al4V manufactured with EBM by applying cyclic voltammetry. The Ti6Al4V work-piece was employed as working electrode, and then immersed in a solution of ethylene glycol and 0.9 molar sodium chloride. The anodic polarization was applied by sweeping the voltage from 15V to 0V at a scan rate of 10 mV/s, using an Ag/AgCl reference electrode. The original average diameter of the beads is 50 µm. The semi-melted beads can clearly be observed in figure 1.A. Figure 1.B. shows the work-piece after the electro-polish treatment (3 cycles) in the solution. The semi-sintered beads are greatly reduced and a smooth surface is achieved. These preliminary results are promising and warrant further investigation. [1] S. A. Khanoki, D. Pasini, Journal of the mechanical behavior of biomedical materials, vol. 22, pp. 65-83, 2013. [2] H. J. Rack, J. I. Qazi, Materials Science and Engineering: C, vol. 26, pp. 1269-1277, 9, 2006. [3] G. Zhao, O. Zinger, Z. Schwartz, M. Wieland, D. Landolt, B. D. Boyan, Clinical Oral Implants Research, vol. 17, pp. 258-264, 2006. [4] A. F. Teixeira, Master of Applied Science - Thesis, Concordia University, March 2011. Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,890
Score d'incertitude au seuil0,874

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,244
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle