Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, UK.
Nature. 2017 Jun 7;546(7657):280-284. doi: 10.1038/nature22374.
The discovery of new materials is hampered by the lack of efficient approaches to the exploration of both the large number of possible elemental compositions for such materials, and of the candidate structures at each composition. For example, the discovery of inorganic extended solid structures has relied on knowledge of crystal chemistry coupled with time-consuming materials synthesis with systematically varied elemental ratios. Computational methods have been developed to guide synthesis by predicting structures at specific compositions and predicting compositions for known crystal structures, with notable successes. However, the challenge of finding qualitatively new, experimentally realizable compounds, with crystal structures where the unit cell and the atom positions within it differ from known structures, remains for compositionally complex systems. Many valuable properties arise from substitution into known crystal structures, but materials discovery using this approach alone risks both missing best-in-class performance and attempting design with incomplete knowledge. Here we report the experimental discovery of two structure types by computational identification of the region of a complex inorganic phase field that contains them. This is achieved by computing probe structures that capture the chemical and structural diversity of the system and whose energies can be ranked against combinations of currently known materials. Subsequent experimental exploration of the lowest-energy regions of the computed phase diagram affords two materials with previously unreported crystal structures featuring unusual structural motifs. This approach will accelerate the systematic discovery of new materials in complex compositional spaces by efficiently guiding synthesis and enhancing the predictive power of the computational tools through expansion of the knowledge base underpinning them.
新材料的发现受到缺乏有效方法的阻碍,这些方法既可以探索此类材料大量可能的元素组成,也可以探索每种组成的候选结构。例如,无机扩展固体结构的发现依赖于晶体化学知识,再加上具有系统变化的元素比例的耗时材料合成。已经开发出计算方法来通过预测特定组成的结构和预测已知晶体结构的组成来指导合成,这取得了显著的成功。然而,对于组成复杂的系统,发现具有与已知结构不同的单元胞和其中原子位置的定性新颖、实验可实现的化合物仍然是一个挑战。许多有价值的性质来自于已知晶体结构中的取代,但仅使用这种方法进行材料发现既可能错过最佳性能,也可能在不完全了解的情况下进行设计。在这里,我们通过计算识别包含它们的复杂无机相场区域,报告了通过计算识别来发现两种结构类型的实验结果。这是通过计算探针结构来实现的,这些结构可以捕捉系统的化学和结构多样性,并且它们的能量可以与当前已知材料的组合进行排序。随后对计算相图中能量最低区域的实验探索提供了两种具有以前未报道的晶体结构的材料,这些结构具有不寻常的结构特征。这种方法将通过有效地指导合成并通过扩展支持它们的知识库来提高计算工具的预测能力,从而加速在复杂组成空间中进行新材料的系统发现。