Heterogeneous seeded molecular dynamics as a tool to probe the ice nucleating ability of crystalline surfaces.
Heterogeneous seeded molecular dynamics as a tool to probe the ice nucleating ability of crystalline surfaces.
复制标题
异质种子分子动力学作为探测晶体表面冰成核能力的工具。
DOI:
--
复制
发表时间:
2018
影响因子:
4.4
通讯作者:
A. Michaelides
中科院分区:
文献类型:
--
作者:
P. Pedevilla;Martin Fitzner;G. Sosso;A. Michaelides
Ice nucleation plays a significant role in a large number of natural and technological processes, but it is challenging to investigate experimentally because of the small time scales (ns) and short length scales (nm) involved. On the other hand, conventional molecular simulations struggle to cope with the relatively long time scale required for critical ice nuclei to form. One way to tackle this issue is to take advantage of free energy or path sampling techniques. Unfortunately, these are computationally costly. Seeded molecular dynamics is a much less demanding alternative that has been successfully applied already to study the homogeneous freezing of water. However, in the case of heterogeneous ice nucleation, nature's favourite route to form ice, an array of suitable interfaces between the ice seeds and the substrate of interest has to be built, and this is no trivial task. In this paper, we present a Heterogeneous SEEDing (HSEED) approach which harnesses a random structure search framework to tackle the ice-substrate challenge, thus enabling seeded molecular dynamics simulations of heterogeneous ice nucleation on crystalline surfaces. We validate the HSEED framework by investigating the nucleation of ice on (i) model crystalline surfaces, using the coarse-grained mW model, and (ii) cholesterol crystals, employing the fully atomistic TIP4P/ice water model. We show that the HSEED technique yields results in excellent agreement with both metadynamics and forward flux sampling simulations. Because of its computational efficiency, the HSEED method allows one to rapidly assess the ice nucleation ability of whole libraries of crystalline substrates-a long-awaited computational development in, e.g., atmospheric science.
影响因子:
3.3
作者:
Cox, Stephen J.;Kathmann, Shawn M.;Michaelides, Angelos
通讯作者:
Michaelides, Angelos
影响因子:
15
作者:
Fitzner, Martin;Sosso, Gabriele C.;Michaelides, Angelos
通讯作者:
Michaelides, Angelos