A variational approach to assess reaction coordinates for two-step crystallization.
A variational approach to assess reaction coordinates for two-step crystallization.
复制标题
评估两步结晶反应坐标的变分方法。
DOI:
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发表时间:
2022
影响因子:
4.4
通讯作者:
M. Salvalaglio
中科院分区:
文献类型:
--
作者:
Aaron R. Finney;M. Salvalaglio
Molecule- and particle-based simulations provide the tools to test, in microscopic detail, the validity of classical nucleation theory. In this endeavor, determining nucleation mechanisms and rates for phase separation requires an appropriately defined reaction coordinate to describe the transformation of an out-of-equilibrium parent phase for which myriad options are available to the simulator. In this article, we describe the application of the variational approach to Markov processes to quantify the suitability of reaction coordinates to study crystallization from supersaturated colloid suspensions. Our analysis indicates that collective variables (CVs) that correlate with the number of particles in the condensed phase, the system potential energy, and approximate configurational entropy often feature as the most appropriate order parameters to quantitatively describe the crystallization process. We apply time-lagged independent component analysis to reduce high-dimensional reaction coordinates constructed from these CVs to build Markov State Models (MSMs), which indicate that two barriers separate a supersaturated fluid phase from crystals in the simulated environment. The MSMs provide consistent estimates for crystal nucleation rates, regardless of the dimensionality of the order parameter space adopted; however, the two-step mechanism is only consistently evident from spectral clustering of the MSMs in higher dimensions. As the method is general and easily transferable, the variational approach we adopt could provide a useful framework to study controls for crystal nucleation.
影响因子:
4.4
作者:
Blow, Katarina E.;Quigley, David;Sosso, Gabriele C.
通讯作者:
Sosso, Gabriele C.
影响因子:
4.4
作者:
Prinz, Jan-Hendrik;Wu, Hao;Noe, Frank
通讯作者:
Noe, Frank
DOI:
10.1073/pnas.2008561117
发表时间:
2020-11-10
影响因子:
11.1
作者:
Fang H;Hagan MF;Rogers WB
通讯作者:
Rogers WB