Department of Physics, Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland.
Department of Chemistry, Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland.
Nat Commun. 2021 Apr 13;12(1):2197. doi: 10.1038/s41467-021-22545-x.
Precise knowledge of chemical composition and atomic structure of functional nanosized systems, such as metal clusters stabilized by an organic molecular layer, allows for detailed computational work to investigate structure-property relations. Here, we discuss selected recent examples of computational work that has advanced understanding of how these clusters work in catalysis, how they interact with biological systems, and how they can make self-assembled, macroscopic materials. A growing challenge is to develop effective new simulation methods that take into account the cluster-environment interactions. These new hybrid methods are likely to contain components from electronic structure theory combined with machine learning algorithms for accelerated evaluations of atom-atom interactions.
精确了解功能纳米系统（如由有机分子层稳定的金属簇）的化学组成和原子结构，可以进行详细的计算工作，以研究结构与性能之间的关系。在这里，我们讨论了一些最近的计算工作实例，这些实例促进了我们对这些簇在催化中的作用、与生物系统的相互作用以及如何形成自组装宏观材料的理解。一个日益严峻的挑战是开发有效的新模拟方法，以考虑簇-环境相互作用。这些新的混合方法可能包含电子结构理论的组成部分，并结合机器学习算法，以加速原子间相互作用的评估。
