Long time evolution of complex materials : algorithmic developments and applications to metals, semiconductors and proteins

复杂材料的长期演化：金属、半导体和蛋白质的算法开发和应用

• 批准号: RGPIN-2019-04580
• 负责人: Mousseau, Normand
• 金额: $ 3.64万
• 依托单位: Université de Montréal
• 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=715019
• 关键词: Long; time; evolution; complex; materials

In spite of the continual increase in computer power over many decades, it is still a challenge, today, to reproduce on computer the long-time atomistic dynamics that is responsible for the evolution of materials and complex molecules such as proteins, for example. Yet, many macroscopic properties of interest to us, such as strength and conductivity are determined by specific atomic position. As even a tiny fraction of atoms hops around, these properties can be modified in depth, affecting the use of the objects upon which our civilization relies. Over the past years, I have been developing various algorithms and methods to try to access the right time scale or ensure a sufficient thermodynamical sampling in order to study understand the kinetics of these complex materials : glasses, proteins, defects in metals and semiconductors, etc. The program presented here first aims at expanding this development in order to address a wider range of problems - the question is complex and much remains to be done in order to cross both time and length scales. On the condensed matter and materials science side, I also plan to focus on specific scientific questions with the goal to develop a better understanding of the kinetics of point defects, both self-defects and impurities, near extended defects such as grain boundaries and dislocations. On the biophysics side, my focus will be two-fold: first, finish the development of a simplified all-atom forcefield based on a coarse-grained potential that we have used for many years and, second, apply this potential to study the kinetics of amyloid aggregation and the interaction between potential inhibitors, coming from natural molecules, and amyloid proteins. In parallel with this work, I will continue to collaborate with groups from around the world who are using the computer codes I have developed that implement methods I have created over the years : the activation-relaxation technique (ART nouveau), a very efficient open-ended saddle-point search method, the kinetic activation-relaxation technique (kinetic ART), a unique off-lattice kinetic Monte Carlo algorithm with an on-the-fly cataloguing capability and, soon, the new all-atom forcefield for protein we are developing. These codes are used today by more than 20 groups from around the world and their use continues to increase, providing considerable leverage to the development that will take place over the coming years. Overall, therefore, this research program will advance significantly our understanding of the kinetics of complex materials from the atomic level both with the tools that I will continue to develop and distribute and their applications that I plan to do over the next few years, particularly regarding defect kinetics in metals and semiconductors and protein aggregation.

尽管几十年来计算机的能力不断提高，但在今天，在计算机上再现长期以来导致材料和复杂分子（例如蛋白质）进化的原子动力学仍然是一个挑战。然而，我们感兴趣的许多宏观性质，如强度和电导率是由特定的原子位置决定的。即使是一小部分原子的跳跃，这些特性也会被深刻地改变，影响到我们文明所依赖的物体的使用。在过去的几年里，我一直在开发各种算法和方法，试图获得正确的时间尺度或确保足够的热力学采样，以研究了解这些复杂材料的动力学：玻璃，蛋白质，金属和半导体中的缺陷等。这里提出的方案首先旨在扩展这一发展，以解决更广泛的问题——这个问题很复杂，为了跨越时间和长度的尺度，还有很多工作要做。在凝聚态和材料科学方面，我还计划专注于具体的科学问题，目的是更好地理解点缺陷的动力学，包括自缺陷和杂质，近扩展缺陷，如晶界和位错。在生物物理方面，我的重点将是两方面：首先，完成基于我们已经使用多年的粗粒度电位的简化全原子力场的开发；其次，应用这种电位来研究淀粉样蛋白聚集的动力学以及来自天然分子的潜在抑制剂与淀粉样蛋白之间的相互作用。在这项工作的同时，我将继续与来自世界各地的团体合作，他们正在使用我开发的计算机代码来实现我多年来创建的方法：激活-松弛技术（ART nouveau），一种非常有效的开放式鞍点搜索方法，动力学激活-松弛技术（kinetic ART），一种具有动态编目能力的独特的离晶格动力学蒙特卡罗算法，以及我们正在开发的新的全原子蛋白质力场。目前，世界各地有20多个团体在使用这些代码，而且它们的使用还在不断增加，为未来几年的发展提供了相当大的杠杆作用。因此，总的来说，这个研究项目将大大提高我们对复杂材料动力学的理解，从原子水平上，我将继续开发和分发的工具，以及我计划在未来几年里进行的应用，特别是关于金属、半导体和蛋白质聚集的缺陷动力学。