标题： 使用机器学习势解码超小孔MOF MIL-120(Al)二氧化碳吸附剂中的局部框架动力学 显示英文标题

标题： Decoding local framework dynamics in the ultra-small pore MOF MIL-120(Al) CO2 sorbent with Machine Learned Potentials

摘要： 具有超小孔径的金属有机框架（MOFs）为有效捕获CO2等客体分子提供了理想的环境。 它们框架的微小局部动态，无论是功能基团在有机连接体上的重新取向，还是无机节点中存在的动态，预计将在它们的吸附行为中起重要作用。 在此，我们将密度泛函理论（DFT）与一个专门训练的机器学习势能结合，系统地研究了桥接羟基的局部动态，这些羟基是原型超小孔径MOF MIL-120(Al)中的{\mu }2-OH基团，最近被报道为一种有吸引力的CO2吸附剂。 我们识别出六种与不同{\mu }2-OH取向相关的MOF构型，其相互转换的能量势垒相对较低（每单元0.07-0.19 eV），表明所有这些状态都可以在室温下实验观察到。 我们证明了我们的MLP能够达到接近DFT级别的保真度，能够再现空MOF的能量势垒和声子谱，并根据{\mu }2-OH取向准确预测CO2的吸附几何结构，其中CO2要么平行于孔轴，要么垂直于孔轴，这反过来决定了吸附热力学。 这项工作确立了对局部结构（如桥接羟基的重新取向/翻转）的可靠描述是获得超小孔径MOF中客体位置和热力学准确描述的关键特征。 显示英文摘要

摘要： Metal-organic frameworks (MOFs) with ultra-small pores offer an optimal environment to effectively capture guest molecules such as CO2. Subtle local dynamics of their frameworks, either throughout reorientation of functional groups grafted to the organic linkers or those present in their inorganic nodes, is expected to play a major role in their sorption behaviors. Here, we combine density-functional theory (DFT) with a purpose-trained machine-learned potential to systematically investigate the local dynamics of the bridging hydroxyl groups, {\mu}2-OH groups present in the prototypical ultra-small pore MOF MIL-120(Al), reported recently as an attractive CO2 sorbent. We identified six MOF configurations associated with distinct {\mu}2-OH orientations with relatively low interconversion energy barriers (0.07-0.19 eV per unit cell) suggesting that all these states can be observed experimentally at room temperature. We demonstrated that our MLP achieves near-DFT-level fidelity, reproducing the energy barriers and phonon spectra of the empty MOF, and accurately predicting CO2 adsorption geometries depending on the {\mu}2-OH orientations with CO2 adopting either parallel or perpendicular alignment to the pore axis, which in turn governs the adsorption energetics. This work establishes that a reliable description of the local structure, such as reorientation/flipping of bridging hydroxyl groups, is a key feature to gain an accurate description of the guest locations and energetics in ultra-small pore MOFs.