Master thesis : Mechanical Characterisation of Intraocular Lens Materials With a View to Finite Element Modelling (including introduction to research methodology)

Abstract

Intraocular lenses (IOLs) are implanted in the eye to correct vision or even restore visual function. Their mechanical behaviour plays a key role in both surgical handling and in vivo performance.

This study focuses on the comprehensive mechanical characterisation of seven materials used in the manufacturing of intraocular lenses. The primary objective is to establish reliable material properties that are intrinsic to the materials themselves and independent of any specific lens geometry. These data are intended to provide a robust basis for material selection, product development, and numerical simulations within BVI, the company that hosted and supervised this work. Recognising the critical importance of understanding both the bulk and surface mechanical behaviours, two complementary experimental techniques were developed. On one hand, the uniaxial tensile test allows to probe the material’s bulk properties. On the other hand, the nanoindentation measurements aim to investigate the mechanical response at the surface. As a secondary objective, the experimental results are used to investigate calibration strategies for constitutive models in finite element analyses.

Given the unique challenges related to soft and highly hydrated materials, special methodologies were developed and tailored to ensure reliable testing conditions, minimise sample alteration, and account for factors such as hydration, adhesion, and time-dependent effects. The preparation and execution of both experiments required well-defined protocols, ranging from environmental controls to the use of specialised grips and indenter geometries. In parallel, a significant effort was devoted to advanced data processing, including customised filtering, curve fitting, and error analysis, to guarantee the robustness and reproducibility of the results.

The uniaxial tensile experiments revealed a highly nonlinear stress-strain behaviour, typical of hyperelastic materials, confirming the need for appropriate constitutive modelling. Nanoindentation results highlighted clear differences between the bulk and the surface, an observation that is directly relevant to practical issues encountered by the company. These findings underscore the necessity of considering both scales to fully understand and optimise the material’s function in its final application. For the modelling part, a Neo-Hookean hyperelastic model was successfully calibrated using the experimental datasets in FEBio, providing a solid first approximation of the material’s mechanical response. The work also discusses the potential for adopting more sophisticated models, such as the Yeoh model able to capture additional complexities observed in the material’s behaviour.

Overall, this research delivers substantial added value to the company, which until now had not focused specifically on the intrinsic mechanical properties of its lens materials. Because the entire characterisation process was conducted in-house, the resulting data is highly reliable and credible, directly reflecting the actual materials and manufacturing conditions unique to the company. By providing a deeper and more nuanced understanding, the study opens the door to better product design, targeted problem-solving, and more effective quality control. The methodologies and insights developed in this work also could serve the broader academic community, offering a replicable framework for the characterisation and modelling of soft and hydrated materials. Ultimately, this work establishes a solid foundation for the integration of finite element modelling into the design process, enabling more predictive simulations and virtual prototyping of intraocular lenses. By establishing calibrated FEM models, it becomes possible to significantly reduce the need for extensive laboratory experiments, while still gaining material-specific insights that guide innovation. This approach paves the way for improved reliability, optimised performance and better patient outcomes.