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结合混合反向蒙特卡罗和分子动力学的优化分子重建程序。

Optimized molecular reconstruction procedure combining hybrid reverse Monte Carlo and molecular dynamics.

作者信息

Bousige Colin, Boţan Alexandru, Ulm Franz-Josef, Pellenq Roland J-M, Coasne Benoît

机构信息

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.

出版信息

J Chem Phys. 2015 Mar 21;142(11):114112. doi: 10.1063/1.4914921.

DOI:10.1063/1.4914921
PMID:25796236
Abstract

We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.

摘要

我们报道了一种高效的原子尺度重构方法,该方法是在模拟退火技术框架下,将混合反向蒙特卡罗算法(HRMC)与分子动力学(MD)相结合。本着实验约束分子弛豫技术的精神[Biswas等人,《物理评论B》69, 195207 (2004)],这种改进的程序在重构技术领域提供了一种优化策略,对非晶多孔材料等非均质和无序固体具有特别的意义。虽然HRMC方法通过使用能量惩罚生成物理结构,但与MD相结合使该方法在获得相似质量结构时比HRMC模拟至少快一个数量级。此外,为了确保该技术的可转移性,我们提供了合理的论据来选择各种输入参数,如能量惩罚相对于结构优化的相对权重ω。通过将该方法应用于无序多孔碳,我们表明吸附性能提供了测试重构样品整体结构的数据,但对缺陷的存在仅具有微弱的敏感性。相比之下,发现诸如声子态密度等振动性能对样品的局部结构非常敏感。

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