我国目前暂没有自主知识产权的高通量材料集成计算方法和技术，已成为制约我国开展材料基因组计划的瓶颈。将组合化学和材料信息学的思路和方法引入材料计算模拟, 通过材料计算以有理论依据，可预测的方式寻找材料组成"基因"，设计出新化合物，是新材料设计从"炒菜式"向"材料集成设计"转变的一条有效途径。该项目旨在探讨如何将组合化学中"构建单元"和"高通量筛选"理念用于材料计算模拟，及如何将数据，代码，和材料计算软件有效集成并建立材料计算模拟服务平台及材料信息库的方法和技术。基于上述方法和技术，以石墨烯为目标材料开展应用研究, 研究实现高通量材料集成计算的方法，技术和服务平台，以支持中国版材料基因组计划。

The traditional "try-and-error" approach for new material design is time-consuming hence ineffective. The computational combinatorial chemistry and informatics techniques can be appropriately employed to identify the inorganic material "gene" in a theoretical and predictable way. This can be an effective method to transit new material design from "try-and-error" approach to "integrated material design". However, this methodology requires a comprehensive e-infrastructure to facilitate the material development. The existed e-infrastructures or material computational platforms /tools are either closely tied to material simulation code that imposes some usage restrictions or are not entirely for open access, which has restricted the material innovation in some sense. In this project, we aim to investigate how the idea of "building block" and "high-throughput screening" from combinatorial chemistry can be used in computational material science to build a material computational platform and associated database, namely, MatCloud, where data, various scripts and open-source material simulation code (i.e. ABINIT) can be integrated. Based on the MatCloud, we will use CX chemical system that is formed by graphene adsorbing halogen element (X = F, Cl, Br) as an exemplar material to investigate the pattern of how key properties of CX can vary with different doping concentrations and carrier transportation characteristics, etc. A prediction model will then be developed by using appropriate data mining techniques based on the computational data and some experimental data. The model will be used to predict certain key features of C-X system. We believe the innovative methods and techniques for computational material science and material informatics developed in this project can open new dimensions for "integrated material design" and Material Genome Initiative.