Kulakova Lina, Arampatzis Georgios, Angelikopoulos Panagiotis, Hadjidoukas Panagiotis, Papadimitriou Costas, Koumoutsakos Petros
Computational Science and Engineering Laboratory, Clausiusstrasse 33, ETH Zürich, CH-8092, Switzerland.
D.E.Shaw Research LLC, New York, NY 10036, USA.
Sci Rep. 2017 Nov 29;7(1):16576. doi: 10.1038/s41598-017-16314-4.
The Lennard-Jones (LJ) potential is a cornerstone of Molecular Dynamics (MD) simulations and among the most widely used computational kernels in science. The LJ potential models atomistic attraction and repulsion with century old prescribed parameters (q = 6, p = 12, respectively), originally related by a factor of two for simplicity of calculations. We propose the inference of the repulsion exponent through Hierarchical Bayesian uncertainty quantification We use experimental data of the radial distribution function and dimer interaction energies from quantum mechanics simulations. We find that the repulsion exponent p ≈ 6.5 provides an excellent fit for the experimental data of liquid argon, for a range of thermodynamic conditions, as well as for saturated argon vapour. Calibration using the quantum simulation data did not provide a good fit in these cases. However, values p ≈ 12.7 obtained by dimer quantum simulations are preferred for the argon gas while lower values are promoted by experimental data. These results show that the proposed LJ 6-p potential applies to a wider range of thermodynamic conditions, than the classical LJ 6-12 potential. We suggest that calibration of the repulsive exponent in the LJ potential widens the range of applicability and accuracy of MD simulations.
伦纳德 - 琼斯（LJ）势是分子动力学（MD）模拟的基石，也是科学领域中使用最广泛的计算内核之一。LJ势用具有百年历史的规定参数（分别为q = 6，p = 12）对原子间的吸引和排斥进行建模，最初为简化计算将它们设定为相差两倍的关系。我们通过分层贝叶斯不确定性量化来推断排斥指数。我们使用了来自量子力学模拟的径向分布函数和二聚体相互作用能的实验数据。我们发现，对于一系列热力学条件下的液态氩以及饱和氩蒸气，排斥指数p ≈ 6.5能很好地拟合实验数据。在这些情况下，使用量子模拟数据进行校准并不能很好地拟合。然而，对于氩气，通过二聚体量子模拟得到的p ≈ 12.7的值更合适，而实验数据则支持较低的值。这些结果表明，与经典的LJ 6 - 12势相比，所提出的LJ 6 - p势适用于更广泛的热力学条件。我们认为，对LJ势中排斥指数的校准拓宽了MD模拟的适用范围和准确性。
