D2.1 - Modelling report M18

Abstract

This deliverable describes the simulation work carried out during the first 18 months of the projectand serves as the foundation for the updated report to be delivered at M36. The activities focus ondeveloping and validating computational models to predict the optoelectronic response ofphotonic-enhanced interdigitated back-contact (IBC) crystalline silicon solar cells and on optimizingtheir 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 byNOVA using ANSYS Lumerical, were coupled with an intelligent-search optimization algorithm toidentify photonic geometries that enhance broadband absorption in silicon, using the opticallyinferred photocurrent density (Jph) as the main figure of merit. The work also focused on refiningrefractive index (n, k) fittings, resulting in more realistic photocurrent generation. Simulationsconducted on thin c-Si slabs (1 μm) with optimized photonic crystal dimensions achievedphotocurrent densities of 25.5 mA·cm-2 when integrated with photonic structures, compared to15.6 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. Themodelling also accounted for diffuse transmittance, diffraction modes (fast Fourier transformanalysis), angle-resolved incidence (0–80°), and polarization effects (both transverse electric, TE,and transverse magnetic, TM, modes). It was observed that patterned nanovoids primarily scattertransmitted light between 10° – 40°, particularly at shorter wavelengths, whereas upright periodic pyramids enhance transmission above 40°. Overall, periodic arrays of nanovoids achievedphotocurrents 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 waveopticaleffects, with the scalability of RCWA which facilitates the description of far-field wavepropagation in structures much thicker than the wavelengths, thus enabling the full simulation ofdevice-scale IBC cell architectures. Preliminary results show strong agreement between bothmethods in reflectance and absorption profiles, confirming energy conservation and validating theRCWA simulations for 3D nanostructures. However, minor numerical artifacts linked to the Gibbsphenomenon remain under investigation before generation-rate data can be reliably exported forelectrical modelling.At the same time, TUD developed a dedicated simulation framework that integrates optical datafrom its in-house GenPro4 solver into a TCAD-based drift diffusion platform capable of capturingthe detailed semiconductor physics governing solar cell operation. The optical modeling combinesscalar 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 theneed for new GenPro4 code compatible with legacy modules to produce consistent onedimensionaloptical generation profiles. Consequently, optical profiles generated via FDTDsimulations 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 detailedelectrical modeling of thin c-Si solar cells with an absorber thickness of 10 μm. Ultimately, the jointeffort combines the strengths of both partners, with NOVA providing accurate opticalcharacterization and TUD contributing physics-based TCAD simulations, resulting in a consistentmultiscale approach to assessing the impact of nanophotonic architectures on device performance.Ongoing work is being developed to consolidate the optical–electrical coupling, extend modellingto larger-scale IBC architectures (> 100 μm), and refine the hybrid FDTD/RCWA–TCAD frameworkto further guide the identification of optimal photonic-enhanced IBC configurations towards highefficiency,photonic-enhanced solar cell performance.