Learning to predict polymorphism through simulation of nucleation and nanoparticle evolution

通过模拟成核和纳米颗粒演化来学习预测多态性

• 批准号: DP0986999
• 负责人: Prof Julian Gale
• 金额: $ 64.82万
• 依托单位: Curtin University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2009
• 资助国家: 澳大利亚
• 起止时间: 2009-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0986999
• 关键词: Learning; predict; polymorphism; through; simulation

Many substances are capable of exhibiting a myriad of different structures despite having the same composition. This behaviour can have a significant impact on the production of new pharmaceuticals, since the sudden appearance of a new form can lead to instant withdrawal of the drug. By understanding how different forms grow, rather than focusing on just the stability of the product, this research will lead to more reliable prediction of how pharmaceutical molecules might assemble. The same technology will potentially have impacts in many areas of nanoscience through improvements in efficiency, including the production of minerals, desalination and undersea gas recovery.

许多物质尽管具有相同的成分，却能够表现出多种不同的结构。这种行为可能会对新药物的生产产生重大影响，因为新形式的突然出现可能会导致药物立即停药。通过了解不同形式的生长方式，而不是仅仅关注产品的稳定性，这项研究将更可靠地预测药物分子如何组装。通过提高效率，同样的技术可能会对纳米科学的许多领域产生影响，包括矿物生产、海水淡化和海底天然气回收。