Electronic structure and multiscale modelling of the hydroxyapatite-TiO2 bio-interface: from self-interaction error to predictive coating design.

Hydroxyapatite-titanium dioxide (HA-TiO2) heterojunction coatings are commonly applied to enhance the osseointegration of load-bearing orthopedic implants, but their clinical performance is limited due to coating delamination and fibrous tissue encapsulation at the implant-bone interface. Density functional theory (DFT) offers excellent pre-synthesis predictions on HA-TiO2-based designs, but self-interaction error (SIE) remains a major hurdle due to the well-known underestimation of the band gaps of TiO2 and oxygen vacancy formation kinetics. This leads to inaccurate predictions of localized oxidative stress, electron transport, and early-stage corrosion at the interface. A comprehensive review of the accuracy-cost trade-off of DFT+U, hybrid functionals (HSE06), and machine-learning interatomic potentials (MLIPs) for modelling the HA-TiO2 interface is given here. The electronic-structure corrections related to mesoscale phenomena accessible by molecular dynamics (MD) are also described. A systematic description of the stiff, ice-like hydration layer formed at the TiO2 surfaces is provided to shed light on the transport of Ca2+ and PO4 3- during biomineralization. Further, the dynamics of the hydroxyl dipoles, doping and nanostructuring that affect the nature and strength of the resulting interfacial adhesion energy are elaborated in detail. This multiscale approach that connects the accuracy of the electronic structure with the mesoscale hydration and ion-transport kinetics offers a physics-based, computationally informed path to the rational design of HA-TiO2 biomaterial coatings.