CRYSTALGROWER - A NEW APPROACH TO UNDERSTANDING AND PREDICTING CRYSTAL GROWTH

今年，我们在《自然》杂志上发表了一种新的方法，包含在新的软件CrystalGrower中，以了解和预测晶体生长的过程。CrystalGrower策略提供了可以说是第一个完全通用的方法，用于基于少量参数和溶液饱和状态的规范来模拟三维微晶的生长。通过采取重要的一步，绕过需要了解的解决方案形态，这对材料，如沸石，可以是非常复杂的，并结合使用一个独特的选择瓷砖分解固体成生长单位，这导致了一个最重要的最近的进展，在模拟晶体生长的领域。不出所料，自《自然》杂志发表论文以来，CrystalGrower项目吸引了世界各地研究人员的极大兴趣，该论文证明了其适用于从沸石和矿物到有机分子晶体的一切。这种兴趣不仅来自学术团体，也来自希望使用CrystalGrower方法的领先工业研究实验室。虽然CrystalGrower方法已经非常强大，但还需要许多进一步的发展。例如，在生长和多晶体过程中处理竞争多晶型物的能力。下一阶段的一个关键挑战也是试图从将有限数量的参数拟合到实验数据（如原子力显微镜的信息）的方法转变为直接从原子计算中确定这些参数。这将使CrystalGrower成为一个真正的预测工具，并将彻底改变晶体生长的模拟。理解和预测晶体生长的过程是控制现代材料功能的基础。通过理解分子尺度上的晶体生长，我们有可能控制晶体习性、晶体尺寸、缺陷的消除或合并以及共生结构的发展。尽管研究了一百多年，但直到最近才通过扫描探针显微镜揭示了这些过程的分子复杂性。为了给这些大量的新信息带来一些秩序和理解，需要制定和测试新的规则。到目前为止，由于不同晶体系统的复杂性和多样性，这依赖于开发通常仅限于一个系统的模型。这样的工作非常缓慢，并且无法实现广泛的理解，以创建跨晶体类型和晶体结构的统一模型。我们最近在《自然》杂志上描述了一种新的方法来理解和预测晶体的生长，包括缺陷结构的结合，通过使用统一的动力学3-D分区模型同时分子尺度模拟晶体习性和表面拓扑结构。这种方法采用曼彻斯特开发的定制计算机软件CrystalGrower，利用所有已知的实验数据，以比迄今为止更高的精度确定与结晶过程中关键步骤相关的重要自由能。此外，这些方法适用于从分子到离子到骨架晶体等的所有类型的晶体系统。

This year we published in Nature a new methodology, encompassed in the new software CrystalGrower, to understand and predict the course of crystal growth. The CrystalGrower strategy provides arguably the first completely general method for simulating the growth of three-dimensional crystallites based on a small number of parameters and the specification of the saturation state of the solution. By taking the important step of circumventing the need to understand the solution speciation, which for materials such as zeolites can be extremely complex, and combining this with the use of a unique choice of tilings to decompose the solid into growth units, this has led to one of the most significant recent advances in the field of modelling crystal growth. Unsurprisingly, the CrystalGrower project has attracted major interest from researchers around the world since the publication of the Nature paper that demonstrates its' applicability to everything from zeolites and minerals, through to organic molecular crystals. Not only is this interest coming from academic groups, but also from leading industrial research laboratories who would like to use the CrystalGrower approach. Although the CrystalGrower method is already very powerful, there are many further developments that are needed. For example, the ability to handle competing polymorphs during growth and multiple crystals. A key challenge for the next phase is also to try to move from the approach of fitting the limited number of parameters involved to experimental data, such as information from atomic force microscopy, to determining these parameters directly from atomistic calculations. This would make CrystalGrower a truly predictive tool and would revolutionize the simulation of crystal growth. Understanding and predicting the course of crystal growth is fundamental to the control of functionality in modern materials. By understanding crystal growth at the molecular scale we have the possibility to control crystal habit, crystal size, the elimination or incorporation of defects and the development of intergrowth structures. Despite investigations for over one hundred years it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopies. In order to bring some order and understanding to this vast amount of new information requires new rules to be developed and tested. To date, because of the complexity and variety of different crystal systems, this has relied on developing models that are usually constrained to one system only. Such work is painstakingly slow and will not be able to achieve the wide scope of understanding in order to create a unified model across crystal types and crystal structures. We have recently described in Nature a new approach to understand and predict the growth of crystals, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic 3-D partition model. This approach, adopting bespoke computer software CrystalGrower, developed in Manchester, utilises all the known experimental data in order to pin down, with much greater accuracy than hitherto possible, the important free energies associated with the key steps in the crystallisation process. Moreover, these processes are applicable to all types of crystal systems from molecular to ionic to framework crystals etc.