Nanostructure engineering for ferroelectric photovoltaics.

Ferroelectric photovoltaics have attracted increasing attention since their discovery in the 1970s, due to their above-bandgap photovoltage and polarized-light-dependent photocurrent. However, their practical applications have been limited by their weak visible light absorption and low photoconductivity. Intrinsic modification of the material, such as bandgap tuning through chemical doping, has proven effective, but usually leads to the degradation of ferroelectricity.

Dual-Induced Directed Deposition Mechanism Based on Anionic Surfactants Enables Long Cycle Aqueous Zinc Ion Batteries.

Aqueous zinc-ion battery has low cost, and environmental friendliness, emerging as a promising candidate for next-generation battery systems. However, it still suffers from a limited cycling life, caused by dendritic Zn growth and severe side reactions. Recent research highlights that the Zn (002) crystal plane exhibits superior anti-corrosive properties and a horizontal growth pattern.

Inhibition of transcriptional regulation of detoxification genes contributes to insecticide resistance management in Spodoptera exigua.

Synthetic insecticides have been widely used for the prevention and control of disease vectors and agricultural pests. However, frequent uses of insecticides have resulted in the development of insecticide resistance in these insect pests. The resistance adversely affects the efficacy of insecticides, and seriously reduces the lifespan of insecticides.

Assessing Generative Model Coverage of Protein Structures with SHAPES.

Recent advances in generative modeling enable efficient sampling of protein structures, but their tendency to optimize for designability imposes a bias toward idealized structures at the expense of loops and other complex structural motifs critical for function. We introduce SHAPES (Structural and Hierarchical Assessment of Proteins with Embedding Similarity) to evaluate five state-of-the-art generative models of protein structures. Using structural embeddings across multiple structural hierarchies, ranging from local geometries to global protein architectures, we reveal substantial undersampling of the observed protein structure space by these models.

COSIME: Cooperative multi-view integration and Scalable and Interpretable Model Explainer.

Single-omics approaches often provide a limited view of complex biological systems, whereas multiomics integration offers a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and interpreting the intricate relationships between biological features-both within and across different data views-remains a bottleneck. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration and Scalable Interpretable Model Explainer).