Department of Chemistry , Brown University , Providence , Rhode Island 02912 , United States.
Science Institute and Faculty of Physical Sciences , University of Iceland , 107 Reykjavík , Iceland.
J Chem Theory Comput. 2018 May 8;14(5):2797-2807. doi: 10.1021/acs.jctc.8b00039. Epub 2018 Apr 10.
Solving and predicting atomic structures from first-principles methodologies is limited by the computational cost of exploring the search space, even when relatively inexpensive density functionals are used. Here, we present an efficient approach where the search is performed using density functional tight-binding, with an automatic adaptive parametrization scheme for the repulsive pair potentials. We successfully apply the method to the genetic algorithm optimization of bulk carbon, titanium dioxide, palladium oxide, and calcium hydroxide, and we assess the stability of the unknown crystal structure of palladium hydroxide.
从第一性原理方法求解和预测原子结构受到搜索空间计算成本的限制，即使使用相对廉价的密度泛函也是如此。在这里，我们提出了一种有效的方法，其中搜索使用密度泛函紧束缚进行，对于排斥对势使用自动自适应参数化方案。我们成功地将该方法应用于体相碳、二氧化钛、氧化钯和氢氧化钙的遗传算法优化，并评估了氢氧化钯未知晶体结构的稳定性。
