基于多目标粒子群优化算法的新型超硬材料的逆向设计

项目名称： 基于多目标粒子群优化算法的新型超硬材料的逆向设计

项目编号： No.11474125

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 数理科学和化学

项目作者： 李全

作者单位： 吉林大学

项目金额： 86万元

中文摘要： 由于超硬材料在基础科研和工业生产中具有重要的应用价值，寻找新型成本低、工作效率高的超硬材料是亟待解决的关键问题。探索新型超硬材料的实验工作获得了可喜的进展，但是合成的困难依然存在。从结构预测角度出发，设计新型超硬材料可以为实验获得理想超硬材料提供帮助。此前，新型超硬材料的结构预测和设计都是在按照单一的目标来开展全局搜索，比如或者寻找热力学最稳定结构，或者寻找最硬的结构。本项目拟选取典型的过渡族-轻元素型化合物（如Cr、Mn、Fe、Mo、Ru、W、Re和Os等元素的硼化物和氮化物），以具体的复合多功能硬质材料需求为导向，发展有效的兼顾材料硬度、体系自由能、抗压缩性、抗剪切性、轻元素含量、源材料成本和金属性等多目标的粒子群优化结构预测算法，逆向设计出所需的相关材料。本项目将编写具有自主知识产权的结构预测程序，并集成到CALYPSO软件包，为设计和合成新型复合多功能超硬材料提供有力工具。

中文关键词： 晶体结构预测；超硬材料；高压物理；多目标粒子群优化算法；逆向设计

英文摘要： The search for new low-cost and high-efficiency superhard materials is of great importance in view of their major roles played for the fundamental science and the industrial applications. Recent experiments have made big progress in synthesizing several new superhard materials, but the difficulties associated with synthesis in general remain. Materials design technique is greatly desirable as a request to assist experiment. In contrast to the traditional ground state structure prediction method where the total energy or hardness was solely used as the fitness function, here, taking the new family of materials formed by heavy transition metals and light elements (e.g., Cr, Mn, Fe, Mo, Ru, W, Re and Os borides/nitrides) as prototypes, this project is trying to apply multiobjective particle swarm optimization algorithm into the superhard prediction and codes the derived formula into the CALYPSO software. We aim to seek a proper balance among hardness, energy, bulk modulus, shear modulus, concentration of the light elements, cost of materials, and band gap (or metallicity) for a given chemical system based on the requirements of industry.

英文关键词： Crystal structure prediction;Superhard materials;High pressure physics;Multiobjective particle-swarm optimization algorithm;Reverse design