Perovskite solar cells have shown a rapid increase of performance and overcome the threshold of 20% power conversion efficiency (PCE). The main issues hampering commercialization are the lack of deposition methods for large areas, missing long-term device stability and the toxicity of the commonly used Pb-based compounds. In this work, we present a novel chemical vapor deposition (CVD) process for Pb-free air-stable methylammonium bismuth iodide (MBI) layers, which enables large-area production employing close-coupled showerhead technology. We demonstrate the influence of precursor rates on the layer morphology as well as on the optical and crystallographic properties. The impact of substrate temperature and layer thickness on the morphology of MBI crystallites is discussed. We obtain smooth layers with lateral crystallite sizes up to 500 nm. Moreover, the application of CVD-processed MBI layers in non-inverted perovskite solar cells is presented.
Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.
Recently, Pb-based organometal halide perovskite solar cells have passed 20% power conversion efficiency (PCE). However, the main issue hampering commercialization is toxic Pb contained in these cells. Therefore, great attention is devoted to replace Pb by less harmful metals such as Bi. Yet, the most efficient methylammonium bismuth iodide (MBI) perovskite solar cells reported in literature reach PCE up to 0.2%. In this work, MBI perovskite solar cells, which are processed by spin-coating under inert nitrogen atmosphere, employing a standard non-inverted stack are presented. The control of perovskite morphology by modifying the process has been highlighted and the impact on photovoltaic (PV) characteristics has been shown. It is observed that the concentration of the perovskite solution (0.15-0.30 M) has a huge impact on the crystallite size, and the rotation speed during the spin-coating process determines the layer coverage. Exposure of MBI solar cells to ambient air is found to be essential to obtain the highest short-circuit current and open-circuit voltage. The PCE increases over time, from 0.004% directly after processing up to 0.17% after 48 h. The fabricated cells exhibit an open-circuit voltage of 0.72 V, which is the highest value published for this type of solar cell. Experimental SectionUnless otherwise noted, materials were purchased from Sigma-Aldrich and used as received without further purification.The device layout of the processed perovskite solar cells is shown in Figure 1. First, F-doped SnO 2 (FTO)-on-glass substrates (6-9 Ω/sq, VisionTek Systems Ltd.) were cleaned thoroughly with dimethyl sulfoxide (DMSO), acetone, isopropyl alcohol, and deionized water (DI) and finally dried with nitrogen.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.