Researchers at Fudan University have developed a crosslinked potassium polyacrylate skin membrane that lets microrobots generate electricity by walking on metal or silicon surfaces. The membrane uses atmospheric moisture and oxygen to convert environmental chemical energy into power, achieving 133 mW cm⁻² on zinc. It also senses substrate material and roughness, enabling active energy pursuit. The system powered over 10,000 walking steps and remained stable after 1,000,000 steps.

Researchers found that carefully balancing metallic cobalt and cobalt oxide enables highly selective electrocatalytic hydrogenation of nitrogen-containing compounds. The catalyst converted pyridine to piperidine with a more than 99% yield, while intermittent electrolysis maintained its optimal chemical state, offering a potential route toward sustainable chemical manufacturing without use of scarce precious metals.

A “hidden variable” that can determine the success or failure of a chemical reaction has been found in the immediate vicinity of electrodes.

The valence-electron concentration has been conventionally used to identify and classify magnetic ground states in various intermetallic compounds. In quasicrystal approximants, the predictive power of valence-electron concentration is found to be limited across different alloy families and constituent elements. Now, researchers establish the lattice parameter as an experimentally accessible, unified structural descriptor for magnetic ground state selection in Tsai-type icosahedral compounds. This breakthrough will help identify novel quasicrystals and approximant crystals with emergent magnetic properties. 

The research team from National University of Defense Technology systematically described the memory efficiency issues in the training process of large language models (LLMs) with Transformer architecture for scientific fields. As the scale of models continues to expand, memory requirements have become a key bottleneck restricting their applications in scientific fields such as biology, medicine, chemistry, and meteorology. The article systematically reviewed memory-efficient pre-training technologies at the algorithm level, system level, and software-hardware collaborative optimization, and combined with the AlphaFold 2 case, demonstrated how customized memory optimization methods can reduce storage overhead while maintaining prediction accuracy.

A new study published in Advances in Atmospheric Sciences shows that greening in China generally cools the local climate with more rainfall over southern and northeastern China, while greening in India tends to produce warming and less rainfall. The Co-occurring greening in China and India yields uniform climate feedbacks across over half global lands, producing cooler and wetter southern China, cooler western Eurasia, and warmer northern North America.

A team of astronomers from the Einstein Probe (EP) collaboration has uncovered a previously hidden stage in the aftermath of one of the Universe’s most violent events—the merger of two compact stars. Designated EP250704a/GRB 250704B, the fleeting cosmic explosion was jointly captured by the China-led EP mission, the SVOM, and the Insight-HXMT, enabling astronomers to follow this transient simultaneously in gamma rays and soft X-rays from the very onset of the emission. Led by the EP fast extragalactic transients working group, a study published in Science Bulletin reports that, although the short gamma-ray burst (GRB) produced by the compact star merger lasted only about half a second, the source continued shining in soft X-rays for nearly ten minutes after the gamma-ray flash had faded. The discovery reveals that the merger remnant releases substantial energy well beyond the initial short GRB traditionally used to identify these events, allowing compact star mergers—the same cosmic collisions that also produce gravitational waves—to appear as minute-long fast X-ray transients. These X-ray transients therefore provide an electromagnetic counterpart to gravitational-wave events, offering a new probe for multi-messenger astronomy.

Correlation does not imply causation. Using AI to discover new materials is becoming more common, but data-driven approaches sometimes rely heavily on correlations and make testing AI-based predictions difficult. A new perspective paper published by Tohoku University researchers developed a framework for incorporating physics-based principles into AI to generate more interpretable, testable, and meaningful predictions.

Optica announces it's 2027 election results.