RESUMEN
High quality tin-lead perovskite solar cells (SnâPb PSCs) can be fabricated via simple solution processing methods. However, the instability of precursor solutions and their narrow usage windows still pose challenges in manufacturing efficient and reproducible SnâPb PSCs, hindering the commercialization of PSCs. Fluorine tin (SnF2) is widely used as an antioxidant to improve the crystallinity of perovskite. In this study, another role of SnF2 as a stabilizer is found to restrain the deprotonation of methylammonium iodide (MAI) in the precursor solution, which improves their stability and expands their usage windows. Due to the inhibition of SnF2 on oxidation and deprotonation, stable large-sized colloidal clusters form gradually in perovskite precursor solution during aging, leading to uniform nucleation/crystallization during film growth, significantly reducing the roughness and defect density in the films. Because of the competitive deprotonation and oxidation process of Sn2+, the benefit of larger cluster maximizes after about ten days storage of precursor solution. The champion efficiency of SnâPb PSCs prepared with 10 days aged precursor solution is 22.00%. High performance of devices fabricated with precursor solution stored for even ≈40 days discloses the wide usage windows of precursor solution with SnF2 additive.
RESUMEN
Suppressing Sn2+ oxidation and rationally controlling the crystallization process of tin-lead perovskite (Sn-Pb PVK) films by suitable bonding methods have emerged as key approaches to achieving efficient and stable Sn-Pb perovskite solar cells (PSCs). Herein, the chelating coordination is performed at the top and bottom interfaces of Sn-Pb PVK films. The chelation strength is stronger toward Sn2+ than Pb2+ by introducing oligomeric proanthocyanidins (OPC) at the bottom interface. This difference in chelation strength resulted in a spontaneous gradient distribution of Sn/Pb within the perovskite layer during crystallization, particularly enhancing the enrichment of Sn2+ at the bottom interface and facilitating the extraction and separation of photogenerated charge carriers in PSCs. Simultaneously, this top-down distribution of gradually increasing Sn content slowed down the crystallization rate of Sn-Pb PVK films, forming higher-quality films. On the top interface of the PVK, trifluoroacetamidine (TFA) was used to inhibit the generation of iodine vacancies (VI) through chelating with surface-uncoordinated Pb2+/Sn2+, further passivating defects while suppressing the oxidation of Sn2+. Ultimately, the PSCs with simultaneous chelation at both top and bottom interfaces achieved a power conversion efficiency (PCE) of 23.31% and an open-circuit voltage (VOC) exceeding 0.90 V. The stability of unencapsulated target devices in different environments also improved.
RESUMEN
In-sensor and near-sensor computing are becoming the next-generation computing paradigm for high-density and low-power sensory processing. To fulfil a high-density and efficient neuromorphic visual system with fully hierarchical emulation of the retina and visual cortex, emerging multimodal neuromorphic devices for multi-stage processing and a fully hardware-implemented system with versatile image processing functions are still lacking and highly desirable. Here we demonstrate an emerging multimodal-multifunctional resistive random-access memory (RRAM) device array based on modified silk fibroin protein (MSFP), exhibiting both optoelectronic RRAM (ORRAM) mode featured by unique negative and positive photoconductance memory and electrical RRAM (ERRAM) mode featured by analogue resistive switching. A full hardware implementation of the artificial visual system with versatile image processing functions is realised for the first time, including ORRAM mode array for the in-sensor image pre-processing (contrast enhancement, background denoising, feature extraction) and ERRAM mode array for near-sensor high-level image recognition, which hugely improves the integration density, and simply the circuit design and the fabrication and integration complexity.