2022
DOI: 10.1016/j.bprint.2021.e00180
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Surface engineering of additively manufactured titanium alloys for enhanced clinical performance of biomedical implants: A review of recent developments

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Cited by 46 publications
(20 citation statements)
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“…Roughening dental implant surfaces can be done by various methods ( Shayganpour et al., 2015 ; Muthaiah et al., 2022 ). Roughness sizes vary depending on the surface treatment.…”
Section: Surface Modification Of Ti Implantsmentioning
confidence: 99%
“…Roughening dental implant surfaces can be done by various methods ( Shayganpour et al., 2015 ; Muthaiah et al., 2022 ). Roughness sizes vary depending on the surface treatment.…”
Section: Surface Modification Of Ti Implantsmentioning
confidence: 99%
“…These implanted scaffolds are translational therapeutic approaches [5] using tissue engineering techniques [6] to treat degenerative diseases [7] and improve cartilage regeneration efficiency [8] for osteoarthritis patients. At present, titanium filler [9] is still the most commonly used in metallic scaffolds [10] in advanced combinations with polymer-based biomaterials [11][12][13] during the green composite fabrication processes [14]. However, the existing titanium dioxide filler in these applications [15] was over-strengthened or too hard, resulting in a thin oxide surface layer not being discussed [16].…”
Section: Introductionmentioning
confidence: 99%
“…Notably, in earlier work with conventionally manufactured alloys, the surfaces were initially smoothened to low roughness prior to the EPD of nanoHAp. , However, we successfully prepared these coatings even on surfaces of the additively manufactured parts with markedly higher roughness. Surface engineering of additively manufactured metallic implants and specifically for titanium implants is an active area fo research . These results will enable the fabrication of orthopedic implants of complex geometry, leveraging the opportunities of additive manufacturing, and their clinical performance can be augmented by coating with nanoHAp prepared by EPD.…”
Section: Resultsmentioning
confidence: 99%