This deliverable describes the simulation work carried out during the first 18 months of the project and serves as the foundation for the updated report to be delivered at M36. The activities focus on developing and validating computational models to predict the optoelectronic response of photonic-enhanced interdigitated back-contact (IBC) crystalline silicon solar cells and on optimizing their design to maximize photovoltaic (PV) efficiency within the BURST project (Task T2.1). Optical simulations, based on the finite-difference time-domain (FDTD) method and performed by NOVA using ANSYS Lumerical, were coupled with an intelligent-search optimization algorithm to identify photonic geometries that enhance broadband absorption in silicon, using the optically inferred photocurrent density (Jph) as the main figure of merit. The work also focused on refining refractive index (n, k) fittings, resulting in more realistic photocurrent generation. Simulations conducted on thin c-Si slabs (1 µm) with optimized photonic crystal dimensions achieved photocurrent densities of 25.5 mA·cm-2 when integrated with photonic structures, compared to 15.6 mA·cm-2 for planar references, which corresponds to 77 % of the theoretical Green (Lambertian) limit. The resulting optical gains translated into a rise in power conversion efficiency (PCE) from 6.6 % to 12.3 %, an ~87 % relative improvement while maintaining VOC and FF. The modelling also accounted for diffuse transmittance, diffraction modes (fast Fourier transform analysis), angle-resolved incidence (0–80°), and polarization effects (both transverse electric, TE, and transverse magnetic, TM, modes). It was observed that patterned nanovoids primarily scatter transmitted light between 10° – 40°, particularly at shorter wavelengths, whereas upright periodic pyramids enhance transmission above 40°. Overall, periodic arrays of nanovoids achieved photocurrents close to those attained by upright random or inverted regular pyramids. An integrated FDTD and rigorous coupled-wave analysis (RCWA) framework was also developed. The aim is to combine the high spatial accuracy of FDTD, essential to describe near-field and wave-optical effects, with the scalability of RCWA which facilitates the description of far-field wave propagation in structures much thicker than the wavelengths, thus enabling the full simulation of device-scale IBC cell architectures. Preliminary results show strong agreement between both methods in reflectance and absorption profiles, confirming energy conservation and validating the RCWA simulations for 3D nanostructures. However, minor numerical artifacts linked to the Gibbs phenomenon remain under investigation before generation-rate data can be reliably exported for electrical modelling. At the same time, TUD developed a dedicated simulation framework that integrates optical data from its in-house GenPro4 solver into a TCAD-based drift diffusion platform capable of capturing the detailed semiconductor physics governing solar cell operation. The optical modeling combines scalar scattering theory, RCWA and ray tracing to describe both diffractive and refractive regimes. However, RCWA simulations of MST structures exhibited numerical instabilities, mainly due to the need for new GenPro4 code compatible with legacy modules to produce consistent one-dimensional optical generation profiles. Consequently, optical profiles generated via FDTD simulations at NOVA allowed to replicate the optical conditions of the photonic crystal (PC) structures and were employed as an input for the established TCAD framework, enabling detailed electrical modeling of thin c-Si solar cells with an absorber thickness of 10 µm. Ultimately, the joint effort combines the strengths of both partners, with NOVA providing accurate optical characterization and TUD contributing physics-based TCAD simulations, resulting in a consistent multiscale approach to assessing the impact of nanophotonic architectures on device performance. Ongoing work is being developed to consolidate the optical–electrical coupling, extend modelling to larger-scale IBC architectures (> 100 µm), and refine the hybrid FDTD/RCWA–TCAD framework to further guide the identification of optimal photonic-enhanced IBC configurations towards high-efficiency, photonic-enhanced solar cell performance.
Vicente et al. (Wed,) studied this question.