Purpose: For the realization of optical waveguide components, needed for photonic integrated circuits, multimode-interference based (MMI-based) devices are an excellent component class for the realization of low loss optical splitters. A promising approach to the manufacturing of these components is their embedding in thin glass sheets by ion-exchange diffusion processes, which has not yet been extensively studied. This study aims to significantly enhance the modeling of the diffusion process to support manufacturing of graded-index, MMI-based optical splitters. Design/methodology/approach: The methods of design and analysis of MMI-based components are based on a step-index refractive index profile. In this work, fundamental correlations between the properties of the manufacturing ion-exchange process and the characteristics of the graded-index, MMI-based components are established. The refractive index profile is calculated with a proprietary solver based on the finite element method. Any further investigation with respect to parameter influence is based on the beam propagation method, specifically a finite difference based, semi-vectorial, wide-angle beam propagation algorithm. The influence of the parameters of the self-imaging effect is investigated. On this basis, different approaches for efficient power splitting with graded-index, MMI-based waveguide components are evaluated. Findings: Easy approximations – mostly linear – can be found to model the dependencies of the investigated parameters. The resulting graded-index splitters are characterized by their low excess and insertion loss. Originality/value: These findings are the first step in the direction of the semi-analytical modeling of the respective waveguide components to reduce the numerical effort.

The manufacturing of integrated optical waveguide components can be complex if the design space is highly multivariate or constraints introduced by the process itself are not well-known. Numerical simulation helps to create a basic understanding of the process and the resulting components with their features but is costly with respect to time and hardware resources. The estimation approach in this work introduces a precise, numerically robust and controllable method without any black boxes to estimate the input parameters of the manufacturing ion-exchange process. Therefore, small number of simulation samples is used to determine basic dependencies of desired waveguide component features on the input parameters. A pseudo probability measure is then used to estimate the combination of process parameters that is most likely to result in the required features. The feature data is detached from the sample size of the simulation data with a multidimensional curve fit in order to debloat the estimation model. The implications of the estimation are wide-ranged and not restricted to the physics of the ion-exchange process, i.e. easy to be abstracted to other models. The estimation enables parameter subspace optimization or clustering of solution. Model benchmarks show a very high estimation rate for all types of considered applications.