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Exploring the High-Pressure Materials Genome

机译:探索高压材料基因组

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A thorough in?situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab?initio calculations are widely used to guide experiments by predicting the composition, structure, and properties of high-pressure compounds. However, such techniques are usually computationally expensive and not suitable for large-scale combinatorial exploration. On the other hand, data-driven computational approaches using large materials databases are useful for the analysis of energetics and stability of hundreds of thousands of compounds, but their utility for materials discovery is largely limited to idealized conditions of zero temperature and pressure. Here, we present a novel framework combining the two computational approaches, using a simple linear approximation to the enthalpy of a compound in conjunction with ambient-conditions data currently available in high-throughput databases of calculated materials properties. We demonstrate its utility by explaining the occurrence of phases in nature that are not ground states at ambient conditions and by estimating the pressures at which such ambient-metastable phases become thermodynamically accessible, as well as guiding the exploration of ambient-immiscible binary systems via sophisticated structural search methods to discover new high-pressure phases.
机译:彻底的呢?原位的材料在极端条件下的具体化是具有挑战性的,并且诸如晶体结构搜索方法的计算工具与AB组合的晶体结构搜索方法被广泛用于通过预测高压化合物的组成,结构和性质来指导实验。然而,这种技术通常是计算昂贵的并且不适合大规模组合勘探。另一方面,使用大型材料数据库的数据驱动的计算方法对于节能和数十万种化合物的稳定性是有用的,但它们的材料发现的效用主要限于零温度和压力的理想条件。这里,我们提出了一种新颖的框架,其组合了两种计算方法,使用简单的线性近似与化合物的焓与当前在计算的材料特性的高吞吐量数据库中可用的环境条件数据结合使用。我们通过在环境条件下解释不是基于局部状态的性质的阶段的发生以及通过估计这种环境 - 稳定相变得热力学可接近的压力来证明其效用,并通过复杂引导环境不混溶的二元系统的探索结构搜索方法发现新的高压阶段。

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