Stabilizing high-efficiency perovskite solar cells (PSCs) at operating conditions remains an unresolved issue hampering its large-scale commercial deployment. Here, we report a star-shaped polymer to improve charge transport and inhibit ion migration at the perovskite interface. The incorporation of multiple chemical anchor sites in the star-shaped polymer branches strongly controls the crystallization of perovskite film with lower trap density and higher carrier mobility and thus inhibits the nonradiative recombination and reduces the charge-transport loss. Consequently, the modified inverted PSCs show an optimal power conversion efficiency of 22.1% and a very high fill factor (FF) of 0.862, corresponding to 95.4% of the Shockley-Queisser limited FF (0.904) of PSCs with a 1.59-eV bandgap. The modified devices exhibit excellent long-term operational and thermal stability at the maximum power point for 1000 hours at 45°C under continuous one-sun illumination without any significant loss of efficiency.

In this work, highly efficient ternary-blend organic solar cells (TB-OSCs) are reported based on a low-bandgap copolymer of PTB7-Th, a medium-bandgap copolymer of PBDB-T, and a wide-bandgap small molecule of SFBRCN. The ternary-blend layer exhibits a good complementary absorption in the range of 300-800 nm, in which PTB7-Th and PBDB-T have excellent miscibility with each other and a desirable phase separation with SFBRCN. In such devices, there exist multiple energy transfer pathways from PBDB-T to PTB7-Th, and from SFBRCN to the above two polymer donors. The hole-back transfer from PTB7-Th to PBDB-T and multiple electron transfers between the acceptor and the donor materials are also observed for elevating the whole device performance. After systematically optimizing the weight ratio of PBDB-T:PTB7-Th:SFBRCN, a champion power conversion efficiency (PCE) of 12.27% is finally achieved with an open-circuit voltage (V ) of 0.93 V, a short-circuit current density (J ) of 17.86 mA cm , and a fill factor of 73.9%, which is the highest value for the ternary OSCs reported so far. Importantly, the TB-OSCs exhibit a broad composition tolerance with a high PCE over 10% throughout the whole blend ratios.

Despite modest sequence conservation and rapid evolution, long non-coding RNAs (lncRNAs) appear to be conserved in expression pattern and function. However, analysis of lncRNAs across tissues and developmental stages remains largely uncharacterized in mammals. Here, we systematically investigated the lncRNAs of the Guizhou miniature pig (Sus scrofa), which was widely used as biomedical model. We performed RNA sequencing across 9 organs and 3 developmental skeletal muscle, and developed a filtering pipeline to identify 10,813 lncRNAs (9,075 novel). Conservation patterns analysis revealed that 57% of pig lncRNAs showed homology to humans and mice based on genome alignment. 5,455 lncRNAs exhibited typical hallmarks of regulatory molecules, such as high spatio-temporal specificity. Notably, conserved lncRNAs exhibited higher tissue specificity than pigspecific lncRNAs and were significantly enriched in testis and ovary. Weighted co-expression network analysis revealed a set of conserved lncRNAs that are likely involved in postnatal muscle development. Based on the high degree of similarity in the structure, organization, and dynamic expression of pig lncRNAs compared with human and mouse lncRNAs, we propose that these lncRNAs play an important role in organ physiology and development in mammals. Our results provide a resource for studying animal evolution, morphological complexity, breeding, and biomedical research.Intensive transcriptome sequencing, also known as deep sequencing, has led to the discovery that mammalian genomes encode a vast range of non-protein-coding RNAs (ncRNAs) that differ in size and level of conservation 1,2 . The proportion of ncRNAs in an organism's genome has a direct correlation with its developmental complexity 3 . ncRNAs are generally classified into many different RNA types, including microRNA (miRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), small interfering RNAs (siRNAs), and long noncoding RNA (lncRNAs). LncRNAs are defined as transcribed RNA fragments > 200 bp, and they do not have open reading frames of > 100 amino acids. Several recent studies have shown mammalian lncRNAs to be heterogeneous and diverse as well as critically important in cellular function, development, and disease via their transcriptional and posttranscriptional regulation of gene expression 4 . In this study, we aimed to further elucidate the origin, evolution, and function of mammalian ncRNAs, the genome of S. scrofa 5 , a species widely used in medical research, by analyzing the content and function of its lncRNA.LncRNAs have long been ascribed an important role in the evolution of complex traits, and recent studies have revealed that thousands of lncRNAs are evolutionarily conserved in mammals, though not to the same extent as

We propose an intermediate-phase engineering strategy to achieve the robust interfacial contact by utilizing volatile organic salts. The introduction of organic cations (such as methylammonium and formamidinium) leads to the formation of an organic-inorganic hybrid perovskite intermediate phase in the initial film and promotes the high-quality interfacial contact of all-inorganic perovskite/metal oxide. A champion CsPb(I 0.75 Br 0.25 ) 3 -based device with a power conversion efficiency of 17.0% and an open-circuit voltage of 1.34 V was realized.

Background: Identifying splice sites is a necessary step to analyze the location and structure of genes. Two dinucleotides, GT and AG, are highly frequent on splice sites, and many other patterns are also on splice sites with important biological functions. Meanwhile, the dinucleotides occur frequently at the sequences without splice sites, which makes the prediction prone to generate false positives. Most existing tools select all the sequences with the two dimers and then focus on distinguishing the true splice sites from those pseudo ones. Such an approach will lead to a decrease in false positives; however, it will result in non-canonical splice sites missing. Result: We have designed SpliceFinder based on convolutional neural network (CNN) to predict splice sites. To achieve the ab initio prediction, we used human genomic data to train our neural network. An iterative approach is adopted to reconstruct the dataset, which tackles the data unbalance problem and forces the model to learn more features of splice sites. The proposed CNN obtains the classification accuracy of 90.25%, which is 10% higher than the existing algorithms. The method outperforms other existing methods in terms of area under receiver operating characteristics (AUC), recall, precision, and F1 score. Furthermore, SpliceFinder can find the exact position of splice sites on long genomic sequences with a sliding window. Compared with other state-of-the-art splice site prediction tools, SpliceFinder generates results in about half lower false positive while keeping recall higher than 0.8. Also, SpliceFinder captures the non-canonical splice sites. In addition, SpliceFinder performs well on the genomic sequences of Drosophila melanogaster, Mus musculus, Rattus, and Danio rerio without retraining. Conclusion: Based on CNN, we have proposed a new ab initio splice site prediction tool, SpliceFinder, which generates less false positives and can detect non-canonical splice sites. Additionally, SpliceFinder is transferable to other species without retraining. The source code and additional materials are available at https://gitlab.deepomics. org/wangruohan/SpliceFinder.