Approach and algorithm for generating appropriate doped structures for high-throughput materials screening

As the extensive use of first-principles Density Functional Theory (DFT) simulations, using DFT for high-throughput screening to predict the desirable doped structures that are physically stable with optimal properties becomes common. Usually, the challenge of running doping calculation is how to obtain inequivalent doped structures as input for DFT simulations to find the desirable doped structure(s). The current practice of substitutional doping is mainly based on experience to use one or more dopant atoms to replace target atoms to be substituted. Using this manual approach to produce all inequivalent doped structures based on expertise is tedious, and the results are usually incomplete. To address this need, we propose a "doping-filtering" collaboratively working approach and develop associated high-throughput computational algorithms to obtain inequivalent doped structures for substitutional doping-based high-throughput screening effectively. A computational time benchmark matrix table of using this approach to obtain inequivalent doped structures for different doping concentrations is also given. The algorithm is integrated into a high-throughput computational material infrastructure named MatCloud. It has been demonstrated in the study case of doping Ni, Co, Ti and Sc into Zr2Fe that the approach and algorithm are effective in reducing the computational time in obtaining inequivalent doped structures.