纳米复合材料与绿色催化研究室

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Domain-trained language model for inverse design and synthesis of high-performance hydrogen storage MOFs.Angew. Chem. Int. Ed.,2026,
Reaction mechanisms and rational design of MOF catalysts: insights from microscopic simulations.Coord. Chem. Rev.,2026,
LLM-assisted intelligent discovery of metal-organic frameworks for solid-state electrolytes.Mater. Today,2026,
Recent advances in MOF membranes for oil-water separation: from surface and pore engineering to multifunctional applications.Coord. Chem. Rev.,2026,
Unveiling surface electronic descriptors and structure-activity relationships of frustrated lewis pairs within topologically engineered M6O4(OH)4-based MOFs for hydrogenolysis.ACS Catal.,2025,
Conversational large-language-model AI agent for accelerated synthesis of metal-organic frameworks catalysts in olefin hydrogenation.ACS Nano,2025,
“Back-to-back” radial layered skeleton converging heat flow to assist in thermal conduction of aramid nanofibers/graphene phase change composite materials.Adv. Funct. Mater.,2025,
Recent advances in hydrotreating and hydrocracking catalysts for the preparation of light aromatics: Influencing factors, catalytic mechanisms and performance relationship descriptors.Coord. Chem. Rev.,2025,
Ce-doping rather than CeO2 modification and their synergistic effect: promotion from Ce species in the electrocatalytic oxidation of 5-Hydroxymethylfurfural over NiFe-LDH.Adv. Energy Mater.,2024,
Phase change thermal storage materials for interdisciplinary applications.Chem. Rev.,2024,

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