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Paul Weitz

Publications and source records attributed to Paul Weitz.

3 recordsLinked to original sources

Mobility-lifetime relation links photodegradation in spin-coated and gravure-printed organic solar cells

The degradation mechanisms of organic solar cells (OSCs) have been studied primarily in spin-coated, laboratory-scale devices, whereas scalable processing modifies the device architecture, active-layer morphology, and underlying charge-transport and recombination properties. Whether these changes also alter how solar cells degrade remains unclear. Here, we compare spin-coated and fully roll-to-roll-compatible gravure-printed PM6:Y12 solar cells during $\sim$1000 h of continuous illumination. Despite distinct initial properties and degradation signatures, the loss of power-conversion efficiency systematically follows the mobility-lifetime product $μτ$. Remarkably, ageing of the printed devices increases the recombination lifetime while strongly reducing charge-carrier mobility, showing that a longer lifetime alone does not imply improved device performance. The mobility reduction is accompanied by decreased PM6 lamellar order, whereas the additional open-circuit voltage loss originates predominantly from increased non-radiative recombination. Dark recovery further reveals a metastable contribution specific to the printed architecture. These results identify the mobility-lifetime product as a unifying physical descriptor for photodegradation, linking ageing-induced microscopic changes to macroscopic performance loss across spin-coated and scalable printed OSCs.

cond-mat.mtrl-sci

A Simultaneous Synergistic Protection Mechanism in Hybrid Perovskite-Organic Multi-junctions Enables Long-Term Stable and Efficient Tandem Solar Cells

Perovskite-organic tandem solar cells (P-O TSCs) hold great promise for next-generation thin-film photovoltaics, with steadily improving power conversion efficiency (PCE). However, the development of optimal interconnecting layers (ICLs) remains one major challenge for further efficiency gains, and progress in understanding the improved long-term stability of P-O tandem configuration has been lagging. In this study, we experimentally investigate the enhanced stability of p-i-n P-O TSCs employing a simplified C60/atomic-layer-deposition (ALD) SnOx/PEDOT: PSS ICL without an additional charge recombination layer (CRL), which achieve an averaged efficiency of 25.12% and a hero efficiency of 25.5%. Our finding discovers that the recrystallization of C60, a widely used electron transport layer in perovskite photovoltaics, leads to the formation of grain boundaries during operation, which act as migration channels for the interdiffusion of halide and Ag ions. Critically, we demonstrate for the first time that the tandem device architecture, incorporating organic semiconductor layers, effectively suppresses the bi-directional ion diffusion and mitigates electrode corrosion. Thus, the P-O TSC establishes a mutual protection system: the organic layers stabilize the perovskite sub-cell by suppressing ion diffusion-induced degradation, and the perovskite layer shields the organic sub-cell from spectrally induced degradation. The simultaneous synergistic protection mechanism enables P-O TSCs to achieve exceptional long-term operational stability, retaining over 91% of their initial efficiency after 1000 hours of continuous metal-halide lamp illumination, and to exhibit minimal fatigue after 86 cycles (2067 hours) of long-term diurnal (12/12-hour) testing. These results demonstrate that tandem cells significantly outperform their single-junction counterparts in both efficiency and stability.

physics.app-ph

Influence of Water Droplet Contamination for Transparency Segmentation

Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. While the general usability of these techniques is high, there are still challenging real-world use-cases. Especially transparent structures, which can appear in the form of glass doors, protective casings or everyday objects like glasses, pose a challenge for computer vision methods. This paper evaluates the combination of transparent objects in conjunction with (naturally occurring) contamination through environmental effects like hazing. We introduce a novel publicly available dataset containing 489 images incorporating three grades of water droplet contamination on transparent structures and examine the resulting influence on transparency handling. Our findings show, that contaminated transparent objects are easier to segment and that we are able to distinguish between different severity levels of contamination with a current state-of-the art machine-learning model. This in turn opens up the possibility to enhance computer vision systems regarding resilience against, e.g., datashifts through contaminated protection casings or implement an automated cleaning alert.

cs.CV