近日，英国曼彻斯特大学Sarah J. Haigh团队报道了有机液-固界面上金物种的原子分辨率成像。相关论文于2026年4月2日发表在《科学》杂志上。

固液界面处吸附态原子的结构和动力学特性决定了高级催化剂、电化学装置、分子分离技术以及废料流金属提取等领域的性能。然而，由于成像分辨率不足以及溶剂不相容等原因，学界一直很难开展在各种化学环境中原子级分散的金属原位研究。

研究组将液相电子显微镜原子分辨率的样品设计与深度学习分析相结合，以探究金吸附原子团、石墨基底以及溶剂之间的相互作用。他们追踪了超过10⁶个以石墨为基底的金吸附原子、双原子以及更大尺寸团簇在五种溶剂中的分布位点。尽管其初始原子分布由溶剂的极性所决定，但仍需低温快速干燥动力学来优化催化性能。

附：英文原文

Title: Atomic-resolution imaging of gold species at organic liquid-solid interfaces

Author: Sam Sullivan-Allsop, Nick Clark, Wendong Wang, Rongsheng Cai, William Thornley, David G. Hopkinson, James G. McHugh, Ben Davies, Samuel Pattisson, Nicholas F. Dummer, Rui Zhang, Matthew Lindley, Gareth Tainton, Jack Harrison, Hugo De Latour, Joseph Parker, Joshua Swindell, Eli G. Castanon, Amy Carl, David J. Lewis, Natalia Martsinovich, Christopher S. Allen, Mohsen Danaie, Andrew J. Logsdail, Vladimir Fal’ko, Graham J. Hutchings, Alex Summerfield, Roman Gorbachev, Sarah J. Haigh

Issue&Volume: 2026-04-02

Abstract: The structure and dynamics of adsorbed atoms (adatoms) at solid-liquid interfaces determine the performance of advanced catalysts, electrochemical devices, molecular separation technologies, and metal extraction from waste streams. However, in situ investigations of atomically dispersed metals in various chemical environments have been prevented by insufficient imaging resolution and solvent incompatibility. In this study, we combined a specimen design that provides atomic resolution in liquid-phase electron microscopy with deep learning–enabled analysis to explore the interactions between gold adatoms, graphite support, and the solvent collectively. We tracked the locations of >106 graphite-supported gold adatoms, dimers, and larger clusters in five solvents. Although their initial atomic dispersion was determined by the solvent polarity, fast drying kinetics at low temperature was required for optimizing catalytic performance.

DOI: adw2469

Source: https://www.science.org/doi/10.1126/science.adw2469