二氧化硅材料粗糙表面的详细表征
Detailed Characterization of Rough Surfaces for Silica Materials
摘要：
我们提出了一种新的方法来获得纳米级的粗糙表面的低温吸附实验的形态。我们的方法是基于最现实的粗糙表面的随机相关过程和随机表面密度泛函理论（RS-DFT）作为理论吸附模型制定的模型之一。我们考虑在法线方向上的粗糙度，侧表面结构的相关长度和比表面积作为调整参数的RS-DFT拟合的实验数据在低压范围内，其中表面的几何形状的影响是最关键的。与已发表的方法相比，所提出的方法的主要优点之一是粗糙表面的最佳拟合详细几何形状，这为进一步的原子建模提供了完整的信息。所获得的几何形状正确地反映了二氧化硅材料的纳米粗糙度如何取决于合成条件。我们证明，在许多实验中观察到的表面分形维数是自然的相关随机表面模型。我们研究了在不同条件下合成的常用二氧化硅材料的表面几何形状。所得粗糙度参数和分形维数与实验数据吻合较好。最佳拟合比表面积的分析揭示了粗糙表面上的吸附机理，并为寻找最佳存储材料提供了新的策略。
英文摘要：
We propose a new approach to obtain the nanoscale morphology of rough surfaces from low-temperature adsorption experiments. Our method is based on one of the most realistic models of rough surfaces formulated in terms of random correlated processes and random surface density functional theory (RS-DFT) as a theoretical adsorption model. We consider the roughness in the normal direction, the correlation length of the lateral surface structure and the specific surface area as tuning parameters of RS-DFT to fit the experimental data in the low pressure range, where the influence of the surface geometry is the most crucial. One of the major advantages of the proposed approach over published methods is the best-fit detailed geometry of rough surfaces, which provides full information for further atomistic modeling. The obtained geometry correctly reflects how the nanoroughness of silica materials depends on the synthesis conditions. We demonstrate that the surface fractal dimension observed in many experiments is natural for the correlated random surface model. We investigated the surface geometry of popular silica materials synthesized at different conditions. The obtained roughness parameters and fractal dimensions coincide well with the published experimental data. Analysis of the best fit specific surface area reveals the mechanism of adsorption on rough surfaces and provides a new strategy for the search of optimal storage materials.
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