期刊
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 11, 期 8, 页码 3955-3960出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.5b00212
关键词
-
资金
- French ANR [ANR-12-BS04-0001-02]
- Swiss National Science Foundation
- Agence Nationale de la Recherche (ANR) [ANR-12-BS04-0001] Funding Source: Agence Nationale de la Recherche (ANR)
The dream of any solid-state theorist is to be able to predict new materials with tailored properties from scratch, i.e., without any input from experiment. Over the past decades, we have steadily approached this goal. Recent developments in the field of high-throughput calculations focused on finding the best material for specific applications. However, a key input for these techniques still had to be obtained experimentally, namely, the crystal structure of the materials. Here, we give a step further and show that one can indeed optimize material properties using as a single starting point the knowledge of the periodic table and the fundamental laws of quantum mechanics. This is done by combining state-of-the-art methods of global structure prediction that allow us to obtain the groundstate crystal structure of arbitrary materials, with an evolutionary algorithm that optimizes the chemical composition for the desired property. As a first showcase demonstration of our method, we perform an unbiased search for superhard materials and for transparent conductors. We stress that our method is completely general and can be used to optimize any property (or combination of properties) that can be calculated in a computer.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据