To address these limitations, we introduce a novel framework: the Molecular Merged Hypergraph Neural Network (MMHNN). MMHNN innovatively incorporates a predefined set of molecular subgraphs, replacing each with a supernode to construct a compact hypergraph. This architectural change substantially reduces computational overhead while preserving essential molecular interactions.

The American Chemical Society (ACS) Fall 2025 meeting, held from August 17 to 21 in Washington, DC, has proven to be a monumental event in the scientific community. As the largest international academic event in the field of chemistry, it has drawn researchers, academics, and industry leaders from across the globe, all converging to discuss the latest advancements and challenges in chemistry and its multidisciplinary applications.

Text mining has emerged as a powerful strategy for extracting domain knowledge structure from large amounts of text data. To date, most text mining methods are restricted to specific literature information, resulting in incomplete knowledge graphs. Here, we report a method that combines citation analysis with topic modeling to describe the hidden development patterns in the history of science. Leveraging this method, we construct a knowledge graph in the field of Raman spectroscopy. The traditional Latent DirichletAllocation model is chosen as the baseline model for comparison to validate the performance of our model. Our method improves the topic coherence with a minimum growth rate of 100% compared to the traditional text mining method. It outperforms the traditional text mining method on the diversity, and its growth rate ranges from 0 to 126%. The results show the effectiveness of rule-based tokenizer we designed in solving the word tokenizer problem caused by entity naming rules in the field of chemistry. It is versatile in revealing the distribution of topics, establishing the similarity and inheritance relationships, and identifying the important moments in the history of Raman spectroscopy. Our work provides a comprehensive tool for the science of science research and promises to offer new insights into the historical survey and development forecast of a research field.

Researchers demonstrated the first real-world integration of quantum key distribution (QKD) and high-capacity classical communication over field-deployed multi-core fibers. By optimizing wavelength allocation and transmission directions, they suppressed inter-core Raman noise and achieved secure key generation alongside 110.8 Tbps classical data transmission. A validated theoretical model further guides scalable quantum–classical coexistence. This work paves the way for future secure, high-throughput communication networks integrating quantum and classical systems over shared infrastructure.

A weak physical force, like that which allows spiders to walk on a ceiling, could hold the key to a new revolution in optical communications, thanks to a discovery by University of Melbourne researchers and their collaborators at Hanyang University in South Korea.

Researchers at the RIKEN Pioneering Research Institute (PRI) in Japan have discovered a way to max out the amount of hydrogen that can be stored in perovskite crystalline powder. The trick is to introduce the hydrogen into the perovskite lattice structure using mechanochemistry – chemical reactions that occur by physically grinding and mixing compounds together. Because this process requires less energy than traditional non-mechanical methods, the discovery is eco-friendly and good for future sustainability. 

New research from Purdue University reveals how moisture influences atmospheric blocking, a phenomenon that often drives heat waves, droughts, cold outbreaks and floods, helping solve a mystery in climate science and improving future extreme weather predictions.