School of Physical Sciences, University of Kent , Canterbury, CT2 7NZ, United Kingdom.
J Am Chem Soc. 2014 Mar 12;136(10):4056-65. doi: 10.1021/ja500443m. Epub 2014 Feb 28.
Unique physical, chemical, and mechanical properties can be engineered into functional nanomaterials via structural control. However, as the hierarchical structural complexity of a nanomaterial increases, so do the challenges associated with generating atomistic models, which are sufficiently realistic that they can be interrogated to reliably predict properties and processes. The structural complexity of a functional nanomaterial necessarily emanates during synthesis. Accordingly, to capture such complexity, we have simulated each step in the synthetic protocol. Specifically, atomistic models of mesoporous ceria were generated by simulating the infusion and confined crystallization of ceria in a mesoporous silica scaffold. After removing the scaffold, the chemical reactivity of the templated mesoporous ceria was calculated and predicted to be more reactive compared to mesoporous ceria generated without template; visual "reactivity fingerprints" are presented. The strategy affords a general method for generating atomistic models, with hierarchical structural complexity, which can be used to predict a variety of properties and processes enabling the nanoscale design of functional materials.
通过结构控制，可以将独特的物理、化学和机械性能设计到功能纳米材料中。然而，随着纳米材料的层次结构复杂性的增加，生成足够真实的原子模型以可靠地预测性能和过程的相关挑战也随之增加。功能纳米材料的结构复杂性必然在合成过程中产生。因此，为了捕捉这种复杂性，我们模拟了合成方案中的每一个步骤。具体来说，通过模拟在介孔二氧化硅支架中注入和限制二氧化铈的结晶，生成了介孔氧化铈的原子模型。去除支架后，计算并预测了模板介孔氧化铈的化学活性，与没有模板生成的介孔氧化铈相比，它具有更高的反应性；呈现了直观的“反应性指纹”。该策略提供了一种生成具有层次结构复杂性的原子模型的通用方法，可用于预测各种性能和过程，从而实现功能材料的纳米尺度设计。
