Imprecise knowledge based design and development of titanium alloys for prosthetic applications

Informatics guided FE design of bioactive titanium alloy/composite multi-layered dental implants

A dental implant with three distinct layers, of titanium alloy at core, porous titanium alloy at the intermediate layer and titanium alloy hydroxyapatite composite at the outer layer, is designed to achieve low elastic modulus and adequate strength with bioactive surface. Artificial Neural Network (ANN) along with Rule of Mixture (ROM) is used to generate the objective functions for the Genetic Algorithm (GA) based multi-objective optimization for achieving the optimal designs, which are validated using Finite Element Analysis (FEA) simulations. The composition and processing parameters are correlated with the yield strength and elastic modulus of titanium alloy using ANN. The ANN models are generated to express the strength and effective modulus of the implant using ROM. To determine the optimal composition of titanium alloys, porous layers, and composite layers for a three-layer dental implant, multi-objective genetic algorithm is employed. The Pareto optimal solutions provide the guidelines for designing the implant. A few selected non-dominated solutions are used for studying the actual stress distribution at the bone-implant interface using FEA, and showed significant improvements compared to conventional implants.

In-silico design and experimental validation of TiNbTaZrMoSn to assess accuracy of mechanical and biocompatibility predictive models

Numerical design of TiNbTaZrMoSn alloy preceded its manufacture and mechanical, physico-chemical and in vitro characterisation. The specifications of the alloy required a multi-objective optimisation including lower modulus of elasticity than c.p.Ti, high strength, stabilised β crystal structure with a low martensitic start temperature, a narrow solidification range and high biocompatibility. The results reveal that there was a good match between the bulk mechanical properties exhibited by the alloy experimentally and those predicted. Regarding surface properties, independent of roughness effects, the oxide thickness and surface zeta-potential, measured in biologically relevant electrolytes and at physiological pH, arose as important factors in osteoblastic activity (i.e., cell proliferation, measured via DNA, protein and metabolite content, and differentiation, via ALP levels), but not in cell adhesion and viability. The thinner oxide layer and lower absolute value of surface zeta-potential on the TiNbTaZrMoSn alloy explain its lesser osteogenic properties (i.e., inhibition of ALP activity) compared to the c.p. Ti. This study demonstrates that the numerical models to predict microstructure and bulk mechanical properties of β-Ti alloys are robust, but that the prediction of cellular bioactivity lags behind and still requires parameterisation to account for features such as oxide layer composition and thickness, electro-chemical properties and surface charge, and topography to optimise cell response in silico before committing to the costly manufacture and deployment of these alloys in regenerative medicine.

Evolutionary design of optimal surface topographies for biomaterials

Natural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

Cytocompatibility, stability and osteogenic activity of powder metallurgy Ta-xZr alloys as dental implant materials

Tantalum (Ta) and zirconium (Zr) alloys were found to had low elastic modulus and similar biomechanical characteristics as the human bone. However, the biocompatibility and osteogenic potential of Ta-xZr alloyswith different proportions (20, 30, 40 and 50% Zr by atom) remains to be investigated. In this study, the biocompatibility of Ta-xZr alloys and commercially pure titanium (cpTi) was evaluated in vitro by cell counting kit-8 assay. The adhesion of MG63 osteoblasts to the surface of the alloys was observed by fluorescence microscopy, and their morphology was analyzed by scanning electron microscopy (SEM). The expressions of alkaline phosphatase (ALP), Ki67, osteocalcin (OC), collagen-I (Col-I) and Integrin β1 mRNA in the cultured cells were determined by RT-PCR. As a result, Ta-xZr (x = 20, 30, 40 and 50 at%) alloys were non-toxic and supported proliferation of the MG63 cells. The osteoblasts adhered to the Ta-xZr alloys, and subsequently spread and proliferated rapidly. Furthermore, the cells grown on Ta-20Zr and Ta-30Zr expressed high levels of ALP, Col I and OC, indicating that the Ta-xZr alloys can induce osteogenesis. In conclusion, Ta-xZr alloys promoted the adhesion, proliferation and osteogenic differentiation of MG63 cells. The Ta-xZr composites with a higher proportion of Ta exhibited superior osteogenic activity, and Ta-30Zr is therefore a promising alternative for Ti implants.