Electron Transport Layer Engineering Induced Carrier Dynamics Optimization for Efficient Cd-Free Sb2 Se3 Thin-Film Solar Cells.

Antimony selenide (Sb2 Se3 ) is a highly promising photovoltaic material thanks to its outstanding optoelectronic properties, as well as its cost-effective and eco-friendly merits. However, toxic CdS is widely used as an electron transport layer (ETL) in efficient Sb2 Se3 solar cells, which largely limit their development toward market commercialization. Herein, an effective green Cd-free ETL of SnOx is introduced and deposited by atomic layer deposition method. Additionally, an important post-annealing treatment is designed to further optimize the functional layers and the heterojunction interface properties. Such engineering strategy can optimize SnOx ETL with higher nano-crystallinity, higher carrier density, and less defect groups, modify Sb2 Se3 /SnOx heterojunction with better interface performance and much desirable "spike-like" band alignment, and also improve the Sb2 Se3 light absorber layer quality with passivated bulk defects and prolonged carrier lifetime, and therefore to enhance carrier separation and transport while suppressing non-radiative recombination. Finally, the as-fabricated Cd-free Mo/Sb2 Se3 /SnOx /ITO/Ag thin-film solar cell exhibits a stimulating efficiency of 7.39%, contributing a record value for Cd-free substrate structured Sb2 Se3 solar cells reported to date. This work provides a viable strategy for developing and broadening practical applications of environmental-friendly Sb2 Se3 photovoltaic devices.

High Performance Inverted RbCsFAPbI3 Perovskite Solar Cells Based on Interface Engineering and Defects Passivation.

Lead halide-based perovskites solar cells (PSCs) are intriguing candidates for photovoltaic technology due to their high efficiency, low cost, and simple fabrication processes. Currently, PSCs with efficiencies of >25% are mainly based on methylammonium (MA)-free and bromide (Br) free, formamide lead iodide (FAPbI3 )-based perovskites, because MA is thermally unstable due to its volatile nature and Br incorporation will induce blue shift in the absorption spectrum. Therefore, MA-free, Br-free formamidine-based perovskites are drawing huge research attention in recent years. The hole transporting layer (HTL) is crucial in fabricating highly efficient and stable inverted p-i-n structured PSCs by enhancing charge extraction, lowering interfacial recombination, and altering band alignment, etc. Here, this work employs a NiOx /PTAA bi-layer HTL combined with GuHCl (guanidinium hydrochloride) additive engineering and PEAI (phenylethylammonium iodide) passivation strategy to optimize the charge carrier dynamics and tune defects chemistry in the MA-free, Br-free RbCsFAPbI3 -based perovskite absorber, which boosts the device efficiency up to 22.78%. Additionally, the device retains 95% of its initial performance under continuous 1 sun equivalent LED light illumination at 45 °C for up to 500 h.

How to detect propaganda from social media? Exploitation of semantic and fine-tuned language models.

Online propaganda is a mechanism to influence the opinions of social media users. It is a growing menace to public health, democratic institutions, and public society. The present study proposes a propaganda detection framework as a binary classification model based on a news repository. Several feature models are explored to develop a robust model such as part-of-speech, LIWC, word uni-gram, Embeddings from Language Models (ELMo), FastText, word2vec, latent semantic analysis (LSA), and char tri-gram feature models. Moreover, fine-tuning of the BERT is also performed. Three oversampling methods are investigated to handle the imbalance status of the Qprop dataset. SMOTE Edited Nearest Neighbors (ENN) presented the best results. The fine-tuning of BERT revealed that the BERT-320 sequence length is the best model. As a standalone model, the char tri-gram presented superior performance as compared to other features. The robust performance is observed against the combination of char tri-gram + BERT and char tri-gram + word2vec and they outperformed the two state-of-the-art baselines. In contrast to prior approaches, the addition of feature selection further improves the performance and achieved more than 97.60% recall, f1-score, and AUC on the dev and test part of the dataset. The findings of the present study can be used to organize news articles for various public news websites.