The antibacterial behavior of HA-Ag (silver-doped hydroxyapatite) nanopowder and their composite coatings were investigated against Escherichia coli (DH5a). HA-Ag nanopowder and PEEK (polyether-ether-ketone)-based HA-Ag composite powders were synthesized using in-house powder processing techniques. Bacteria culture assay of HA-Ag nanopowder and their composite powders displayed excellent bacteriostatic activity against E. coli. The antibacterial activity increased with increasing concentration of HA-Ag nanoparticle in these composite powders. These nanocomposite powders were subsequently used as feedstock to generate antibacterial coatings via cold spray technology. The ratios of HA-Ag to PEEK in their composite powders were 80:20, 60:40, 40:60, and 20:80 (wt.%). Microstructural characterization and phase analysis of feedstock powders and as-deposited coatings were carried out using FESEM/EDX and XRD. Antibacterial nanocomposite HA-Ag/PEEK coatings were successfully deposited using cold spraying parameters of 11-12 bars at preheated air temperature between 150 and 160°C. These as-sprayed coatings of HA-Ag/PEEK composite powders comprising varying HA-Ag and PEEK ratios retained their inherent antibacterial property as verified from bacterial assay. The results indicated that the antibacterial activity increased with increasing HA-Ag nanopowder concentration in the composite powder feedstock and cold-sprayed coating.
Zinc-substituted cobalt ferrite nanopowders were prepared via a sol-gel route using citric acid as a chelating agent. The influence of zinc concentration on the microstructure, crystal structure, surface wettability, surface roughness, and antibacterial property of zinc-substituted cobalt ferrite nanopowders was investigated systematically. The substitution of zinc influences slightly the microstructure, surface wettability, surface roughness, and crystal structure but strongly affects the antibacterial property of the cobalt ferrite nanopowders. V
There is currently no method whereby material properties of thermal spray coatings may be predicted from fundamental processing inputs such as temperature-velocity correlations. The first step in such an important understanding would involve establishing a foundation that consolidates the thermal spray literature so that known relationships could be documented and any trends identified. This paper presents a method to classify and reorder thermal spray data so that relationships and correlations between competing processes and materials can be identified. Extensive data mining of published experimental work was performed to create thermal spray property-performance maps, known as ''TS maps'' in this work. Six TS maps will be presented. The maps are based on coating characteristics of major importance; i.e., porosity, microhardness, adhesion strength, and the elastic modulus of thermal spray coatings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.