Enhanced performance in low band gap polymer solar cells via surface lattice resonance of non-noble metals
Abstract
Thin-film solar cells, such as organic solar cells (OSCs), suffer from limited light absorption due to their small active-layer thickness, which is constrained by the short charge-carrier diffusion length. Plasmonic light trapping offers an effective strategy to enhance absorption without increasing the film thickness. In this work, we explore the potential of non-noble metals, namely aluminum (Al) and copper (Cu), for plasmonic enhancement in low-bandgap polymer-based OSCs and compare their performance with commonly used but costly noble metals, gold (Au) and silver (Ag), in the form of nanorods (NRs). For PTB7:PC71BM-based OSCs, the power conversion efficiency (PCE) increases from 9.13% to 9.75% and 10.06% with Al and Cu NRs, respectively, and to 10.05% and 10.26% with Ag and Au NRs, respectively. These results indicate that a single non-noble metal NR, particularly Cu, can provide efficiency comparable to noble metals, owing to its localized surface plasmon resonance (LSPR) being closer to the absorption maximum of the active layer (AL). Furthermore, embedding NR arrays within the AL leads to a substantial enhancement in performance, with PCE improvements of 28.43% and 51.58% for Al and Cu, respectively, and 48.72% and 72.50% for Ag and Au, respectively. This enhancement is attributed to the emergence of surface lattice resonances (SLRs) arising from the hybridization of individual NR LSPRs with Rayleigh anomalies, which red-shift the plasmonic response and improve spectral overlap with the absorption of the PTB7:PC71BM based AL. Near-field enhancement is identified as the dominant mechanism for Au and Cu embedded devices, while far-field light scattering governs the performance improvement in Ag and Al embedded devices despite their blue-shifted LSPRs. Overall, this study highlights the strong potential of cost-effective non-noble plasmonic materials for high-performance OSCs and provides valuable insights for designing efficient light-trapping architectures.

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