The electrocatalytic reduction of nitric oxide (NO) to ammonia (NH₃) offers a promising strategy for simultaneously addressing industrial pollutant emissions and enabling sustainable chemical synthesis. In this study, porous aromatic frameworks (PAFs) are introduced for the first time into the NORR system, where their intrinsic porous architecture enhances NO adsorption and interfacial mass transport. By incorporating Co²⁺ ions into a tetraphenylporphyrin-derived PAF (PAF-TPP), a Co-N₄ coordinated catalyst (PAF-TPP-Co) is constructed, achieving highly efficient NO-to-NH₃ conversion. The catalyst delivers an ammonia production rate of 914.2 μg·h^-1·mg_cat^-1 and a Faradaic efficiency of 71.3% at -0.6 V vs. RHE. A synergistic “adsorption–transport–catalysis” mechanism is proposed, providing new insight into the design of porous catalytic systems for NORR.

A research team led by Professors Xiufang Chen, Huaying Ren, and Wancheng Yu at the Institute of Novel Semiconductors, Shandong University, has developed and optimized an innovative stepwise growth strategy that decouples buffer layer formation from subsequent graphene growth, addressing these long-standing challenges at their root. Their breakthrough findings are published in Nano Research.

Researchers have developed a framework that can break down complex problems that agentic AI is tasked with solving. This framework, called "calculus of intelligence" or COIN, works by breaking up the AI agent's overall goal into smaller tasks within a mathematical logic system.

One hundred years after the technique was recognized with the Nobel Prize in Chemistry, analytical ultracentrifugation (AUC) is still making waves in the scientific world. Theodor Svedberg developed the approach in the 1920s, using it to characterize tiny gold particles. Now, AUC helps researchers determine specific properties of individual molecules clustered together, such as those used in pharmaceuticals or industrial chemicals.