Ab initio guided atomistic modelling of nanomaterials on exascale high-performance computing platforms

IF 2.5 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY
J. J. Gutiérrez Moreno
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引用次数: 0

Abstract

The continuous development of increasingly powerful supercomputers makes theory-guided discoveries in materials and molecular sciences more achievable than ever before. On this ground, the incoming arrival of exascale supercomputers (running over 10^18 floating point operations per second) is a key milestone that will tremendously increase the capabilities of high-performance computing (HPC). The deployment of these massive platforms will enable continuous improvements in the accuracy and scalability of ab initio codes for materials simulation. Moreover, the recent progress in advanced experimental synthesis and characterisation methods with atomic precision has led ab initio-based materials modelling and experimental methods to a convergence in terms of system sizes. This makes it possible to mimic full-scale systems in silico almost without the requirement of experimental inputs. This article provides a perspective on how computational materials science will be further empowered by the recent arrival of exascale HPC, going alongside a mini-review on the state-of-the-art of HPC-aided materials research. Possible challenges related to the efficient use of increasingly larger and heterogeneous platforms are commented on, highlighting the importance of the co-design cycle. Also, some illustrative examples of materials for target applications, which could be investigated in detail in the coming years based on a rational nanoscale design in a bottom-up fashion, are summarised.
在超大规模高性能计算平台上对纳米材料进行原子学建模的 Ab initio 引导
功能日益强大的超级计算机的不断发展,使得材料和分子科学领域的理论指导发现比以往任何时候都更容易实现。在此基础上,即将到来的超大规模超级计算机(每秒运行超过 10^18 次浮点运算)是一个重要的里程碑,将极大地提高高性能计算(HPC)的能力。这些大型平台的部署将使用于材料模拟的原子序数代码的准确性和可扩展性不断提高。此外,最近在原子精度的先进实验合成和表征方法方面取得的进展,已使基于原子序数的材料建模和实验方法在系统尺寸方面趋于一致。这使得在硅学中模拟全尺寸系统几乎成为可能,而无需实验输入。本文从一个视角探讨了计算材料科学将如何通过最近到来的超大规模高性能计算进一步赋能,同时对高性能计算辅助材料研究的最新进展进行了小型回顾。文章评论了与有效利用越来越大的异构平台有关的可能挑战,强调了协同设计周期的重要性。此外,还总结了一些目标应用材料的示例,在未来几年中,可以自下而上的方式,基于合理的纳米级设计,对这些材料进行详细研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nano Futures
Nano Futures Chemistry-General Chemistry
CiteScore
4.30
自引率
0.00%
发文量
35
期刊介绍: Nano Futures mission is to reflect the diverse and multidisciplinary field of nanoscience and nanotechnology that now brings together researchers from across physics, chemistry, biomedicine, materials science, engineering and industry.
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