Enhancing hydrogen production using modified ilmenite oxygen carriers
Peer-Reviewed Publication
Updates every hour. Last Updated: 25-Aug-2025 20:11 ET (26-Aug-2025 00:11 GMT/UTC)
Potassium- and calcium-modified ilmenite oxygen carriers, developed by Institute of Science Tokyo, significantly improve hydrogen yields and redox reaction efficiency in chemical looping systems. The chemical modification of ilmenite results in the formation of a calcium titanate phase with iron substitution. This advancement enhances the oxide ion diffusion, accelerates hydrogen production, and also enables a polygeneration system for simultaneous hydrogen production, carbon dioxide capture, and power generation—paving the way to scalable, carbon-neutral energy systems.
Researchers at Soochow University have conducted a comprehensive electrokinetic study on cation-coupled electrochemical CO2 reduction to formic acid or formate. Published in Science Bulletin, the study provides compelling experimental evidence that supports existing computational predictions: the reaction proceeds through sequential electron and proton transfers, rather than a concerted proton-coupled electron transfer pathway.
A research team from Zhengzhou University has systematically sort out the mechanistic frameworks and theoretical underpinnings of triboelectric nanogenerators (TENGs), concurrently introducing four cutting-edge application frontiers: fluid energy harvesting, self-adaptive sensors and systems, high-voltage power sources, and interface probes. Beyond dissecting persistent technological bottlenecks, this review establishes actionable development trajectories to steer next-generation advancements.
Researchers from the McCullagh Group in Oxford University’s Department of Chemistry have published an innovative method in Nature Protocols today (22 August) that provides comprehensive analysis of metabolites found in cells, tissues and biofluids.
The new method delivers a step-change in capability for analysing highly polar and ionic metabolites. The innovation comes from using anion-exchange chromatography coupled to mass spectrometry (AEC-MS) to meet a long-standing need for improving the large-scale analysis of highly polar and ionic metabolites which drive primary metabolic pathways and processes in cells.
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.