A review of carbon-based materials and their coating techniques for biomedical implants applications
Source abstract
Abstract
Carbon-based materials have emerged as an excellent class of biomedical materials due to their exceptional mechanical properties, lower surface friction, and resistance to wear, tear, and corrosion. Experimental studies have shown the promising results of carbon-based coatings in the field of biomedical implants. The reasons for their successful applications are their ability to suppress thrombo-inflammatory reactions which are evoked as an immune response due to foreign body object implantation. Different types of carbon coatings such as diamond-like carbon, pyrolytic carbon, silicon carbide, and graphene have been extensively studied and utilized in various fields of life including the biomedical industry. Their atomic arrangement and structural properties give rise to unique features which make them suitable for multiple applications. Due to the specificity and hardness of carbon-based precursors, only a specific type of coating technique may be utilized for nanostructure development and fabrication. In this paper, different coating techniques are discussed which were selected based on the substrate material, the type of implant, and the thickness of coating layer. Chemical vapor deposition-based techniques, thermal spray coating, pulsed laser deposition, and biomimetic coatings are some of the most common techniques that are used in the field of biomaterials to deposit a coating layer on the implant. Literature gathered in this review has significance in the field of biomedical implant industry to reduce its failure rate by making surfaces inert, decreasing corrosion related issues and enhancing biocompatibility.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Diamond and Carbon-based Materials Research · Bone Tissue Engineering Materials · Graphene and Nanomaterials Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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