Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion.
Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion.
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DOI：
10.1063/1.4880555
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
T. C. Moore;C. Iacovella;C. McCabe
中科院分区：
文献类型：
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作者：
T. C. Moore;C. Iacovella;C. McCabe
在这项工作中，提出了一个扩展的标准迭代玻尔兹曼反演（IBI）方法用于获得粗粒度的潜力。结果表明，从多个状态的目标数据的列入产生较少的状态依赖的潜力，因此更适合于模拟系统的热力学状态比标准的IBI方法的范围。包含来自多个状态的目标数据迫使算法对与多个状态点处的径向分布函数匹配的势相空间的区域进行采样，从而产生更能代表潜在相互作用的导出势。结果表明，该算法是能够收敛到真正的潜在的潜在的系统是已知的。它也表明，通过所提出的方法得到的潜力更好地预测正烷烃链的行为比通过标准IBI方法得到的。此外，通过烷烃单层的检查，它表明，在拟合过程中给予每个状态的相对权重可以影响散装系统的属性，允许进一步调整的潜力，以匹配参考原子和/或实验系统的属性。
In this work, an extension is proposed to the standard iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodynamic states than the standard IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the standard IBI method. Additionally, through the examination of alkane monolayers, it is shown that the relative weight given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of reference atomistic and/or experimental systems.