Surface diffusion and effective pore diffusion in reversed-phase liquid chromatography studied by molecular dynamics simulations

该项目的目标是建立一个一致的，在反相液相色谱（RPLC），最流行的液相色谱分离技术的表面扩散和有效的孔扩散的分子水平的图片。在一个模型RPLC系统中，使用分子动力学（MD）模拟在固定相中和附近的扩散时空分辨。随后使用分级扩散模型将孔级扩散追踪到宏观固定床水平，以允许与色谱数据进行关键比较。小的芳烃，如异丙醇和苯甲醇被用作代表性的分析物，这可以区分其极性，从而浓度，分子取向，并在RPLC固定相和附近的流动性。它们还在不同程度上分配到色谱界面的疏水烷基链中。这种分配到烷基链中（即，进入键合的固定相），连同分析物吸附到链上，形成有效孔扩散、分析物保留和选择性以及由于浓度过载引起的非线性效应的分子基础。这些方面的阐述，而分析物（大小，极性）和移动的相的性质（水-乙腈混合物的组成）进行调整。另外研究的方面是固定相的极性（C18与C8链作为表面改性）和孔几何形状（平面与圆柱形）。MD模拟提供了关于局部浓度、停留时间、扩散迁移率的关键数据，以及关于孔隙水平上的微分分配和吸附的数据。他们可以合理化的宏观，从而实验上可访问的传输动力学和分离效果，如保留和选择性以及吸附等温线的形状，甚至允许预测这些特性的（非）线性RPLC。基于MD模拟的有效孔扩散系数（单中孔水平）与来自分级结构色谱床的中孔和大孔空间的可用物理重建相结合。它允许我们分析（通过基于随机游走方法的质量传输模拟）互连中孔空间中的有效扩散，以及随后在大孔-中孔色谱床的宏观水平上的有效扩散（例如，中孔颗粒的填料或整料）。这种分级扩散方法保证了相关的分子细节（固定相和分析物性质）和所产生的现象（例如，在MD模拟中，在孔水平上适当地解释了在固定相中和固定相附近的扩散;在非线性条件下的吸附和分配），并且可以在形态上追踪到宏观场水平，其中所得数据可以挑战色谱实验（反之亦然）。

The project goal is to establish a consistent, molecular-level picture of surface diffusion and effective pore diffusion in reversed-phase liquid chromatography (RPLC), the most popular liquid chromatographic separation technique. Diffusion in and near the stationary phase is spatiotemporally resolved using molecular dynamics (MD) simulations in a model RPLC system. Pore-level diffusion is subsequently traced up to the macroscopic fixed-bed level using a hierarchical diffusion model, to allow for critical comparisons with chromatographic data. Small aromatic hydrocarbons like ethylbenzene and benzyl alcohol are used as representative analytes, which can be distinguished regarding their polarity and thus concentration, molecular orientation, and mobility in and near the RPLC stationary phase. They also partition to a varying degree into the hydrophobic alkyl chains of the chromatographic interface. This partitioning into the alkyl chains (i.e., into the bonded stationary phase), together with analyte adsorption onto the chains, forms the molecular basis for effective pore diffusion, analyte retention, and selectivity, as well as for nonlinear effects due to concentration overloading. These aspects are elaborated, while analyte (size, polarity) and mobile phase properties (composition of the water-acetonitrile mixture) are adjusted. Additionally investigated aspects are the polarity of the stationary phase (C18 vs. C8 chains as surface modification) and the pore geometry (planar vs. cylindrical). The MD simulations provide key data about local concentrations, residence times, diffusive mobilities, as well as data on a differential partitioning and adsorption on the pore level. They can rationalize the macroscopic, thus experimentally accessible transport dynamics and separation effects like retention and selectivity as well as the shape of adsorption isotherms, or even allow to predict these characteristics of (non)linear RPLC. The MD simulation-based effective pore diffusion coefficient (single-mesopore level) is combined with available physical reconstructions of mesopore and macropore spaces from hierarchically structured chromatographic beds. It allows us to analyze (through mass transport simulations based on a random-walk approach) effective diffusion in the interconnected mesopore space and, subsequently, effective diffusion at the macroscopic level of a macroporous-mesoporous chromatographic bed (e.g., a packing of mesoporous particles or a monolith). This hierarchical diffusion approach guarantees that relevant molecular details (stationary phase and analyte properties) and resulting phenomena (e.g., diffusion in and near the stationary phase; adsorption and partitioning under nonlinear conditions) are properly accounted for on the pore level, in the MD simulations, and can be morphologically traced up to the macroscopic field level, where the resulting data can challenge chromatographic experiments (and vice versa).