Stanford Synchrotron Light Source, SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA.
Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Nat Commun. 2018 Jun 29;9(1):2553. doi: 10.1038/s41467-018-04917-y.
Hydrothermal synthesis is challenging in metal oxide systems with diverse polymorphism, as reaction products are often sensitive to subtle variations in synthesis parameters. This sensitivity is rooted in the non-equilibrium nature of low-temperature crystallization, where competition between different metastable phases can lead to complex multistage crystallization pathways. Here, we propose an ab initio framework to predict how particle size and solution composition influence polymorph stability during nucleation and growth. We validate this framework using in situ X-ray scattering, by monitoring how the hydrothermal synthesis of MnO proceeds through different crystallization pathways under varying solution potassium ion concentrations ([K] = 0, 0.2, and 0.33 M). We find that our computed size-dependent phase diagrams qualitatively capture which metastable polymorphs appear, the order of their appearance, and their relative lifetimes. Our combined computational and experimental approach offers a rational and systematic paradigm for the aqueous synthesis of target metal oxides.
水热合成在具有多种多晶型的金属氧化物体系中具有挑战性，因为反应产物通常对合成参数的微小变化很敏感。这种敏感性源于低温结晶的非平衡性质，其中不同亚稳相之间的竞争可能导致复杂的多阶段结晶途径。在这里，我们提出了一个从头算框架来预测颗粒大小和溶液组成如何在成核和生长过程中影响多晶型体的稳定性。我们通过原位 X 射线散射来验证这个框架，监测 MnO 的水热合成如何在不同的溶液钾离子浓度（[K]=0、0.2 和 0.33 M）下通过不同的结晶途径进行。我们发现，我们计算的尺寸相关相图定性地捕捉到了哪些亚稳多晶型体出现，它们出现的顺序，以及它们的相对寿命。我们的计算和实验相结合的方法为目标金属氧化物的水相合成提供了一种合理而系统的范例。
