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Alka Jaggessar

Researcher at Queensland University of Technology

Publications -  13
Citations -  489

Alka Jaggessar is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Chemistry & Nanostructure. The author has an hindex of 5, co-authored 9 publications receiving 264 citations.

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Bio-mimicking nano and micro-structured surface fabrication for antibacterial properties in medical implants.

TL;DR: Comparison of surface structures of cicada, dragonfly and butterfly wings, shark skin, gecko feet, taro and lotus leaves shows large variations in structure dimension and configuration, indicating that there is no one particular surface structure that exhibits bactericidal behaviour against all types of microorganisms.
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Mechanical, bactericidal and osteogenic behaviours of hydrothermally synthesised TiO2 nanowire arrays.

TL;DR: In this article, various nano-textured surfaces of TiO2 were synthesized using hydrothermal synthesis, by varying NaOH concentration, reaction time and reaction temperature, and their correlations to mechanical, morphological, bactericidal and osteogenic properties of the surfaces were investigated.
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Recent Advances in Manufacturing and Surface Modification of Titanium Orthopaedic Applications

TL;DR: In this paper, the design and manufacturing of porous implant material via additive manufacturing techniques, as well as recent advances in surface modification, to achieve biocompatible surfaces is discussed.
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Bacteria Death and Osteoblast Metabolic Activity Correlated to Hydrothermally Synthesised TiO2 Surface Properties

TL;DR: A thorough examination of the surface, mechanical and wettability properties of multifunctional hydrothermally synthesised nanostructured materials, capable of killing bacteria whilst improving osteoblast metabolic rates, leading to improved osseointegration and antibacterial properties of orthopaedic implants is provided.
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Modelling the growth of hydrothermally synthesised bactericidal nanostructures, as a function of processing conditions

TL;DR: This work uses experimental data from hydrothermally synthesised TiO2 nanostructures, in combination with IBM SPSS Statistics to form a prediction of nanostructure height, as a function of hydrothermal process parameters (NaOH concentration, reaction time and reaction temperature).