Tuning material properties under high pressure: predicting new materials via advanced ab initio methods

在高压下调整材料性能：通过先进的从头算方法预测新材料

• 批准号: RGPIN-2018-04303
• 负责人: Yao, Yansun
• 金额: $ 1.75万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712909
• 关键词: Tuning; material; properties; under; pressure

The discovery of new materials with desirable properties is a driving force for modern technologies. However, experimental exploration of new materials (synthesis-test-repeat cycle) is expensive and extremely time-consuming. With the rapid progress in computing techniques over time, computer simulations now can accurately reproduce materials' behaviors across microscopic and macroscopic dimensions, and begin to be used to aid and direct experimental search for new materials. The ultimate goal of computational material discovery is to replace tedious experimental procedure and achieve materials by design', where new materials with targeted properties are predicted on supercomputers, before being synthesized in a laboratory. In this NSERC Discovery program, we will develop new methods for computational material discovery, and combine them with high performance computation, to predict new materials in three targeted categories, (1) superconducting materials; materials that conduct electricity without resistance when cooled sufficiently, (2) superhard materials; materials that are as hard as or even harder than natural diamond, and (3) high-energy-density materials; materials with a high energy content that could be utilized as energy carriers. Building on our strong expertise in high-pressure science, we will focused on the materials that can potentially be synthesized under extreme pressure. Just like diamonds can be synthesized under high pressure, we will employ pressure to access new states of matter that cannot be formed using other techniques. This program will progress through four steps, (1) development of physical principles that dictate the properties of interest, such as preferred bonding type and electronic structure, (2) prediction of new (virtual) compounds that can best satisfy these principles, (3) determination of stable crystal structures of the virtual compounds, and identification of thermodynamic conditions for their formation and recovery, and (4) experimental confirmation of predicted materials in collaboration with leading experimental groups. Successful achievement of the objectives is expected to have significant impact on material science. New materials, and new knowledge, will be discovered, which will advance the understanding of material behaviors under extreme pressures. The new suite of theoretical methods developed in this program will enable us to direct the experimental search for new materials. Graduate and undergraduate students will be trained in this program with highly desired expertise and skills, particularly in materials science, programming, high performance computation, mathematical analysis and modeling, which are highly sort after in careers in academia, business, and industry in Canada.

具有理想性能的新材料的发现是现代技术的推动力。然而，新材料的实验探索（合成-测试-重复循环）是昂贵且极其耗时的。随着计算技术的快速发展，计算机模拟现在可以准确地再现材料在微观和宏观维度上的行为，并开始用于帮助和指导新材料的实验研究。计算材料发现的最终目标是取代繁琐的实验程序，实现“设计材料”，即在实验室合成之前，在超级计算机上预测具有目标特性的新材料。