We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of different size, comprising composite medium. The parameters of interaction potential between the quasi-atoms are optimized to match elastic properties of the composite medium to those of the atomic one. The optimization method coincides conceptually with the online Machine Learning (ML) methods, making it computationally very efficient. Such an approach allows a straightforward application of standard software packages for molecular dynamics (MD), supplemented by the ML-based optimizer. The new method is applied to model systems with a simple, pairwise Lennard-Jones potential, as well with multi-body Tersoff potential, describing covalent bonds. Using LAMMPS software we simulate collision of particles of different size. Comparing simulation results, obtained by the novel method, with full-atomic simulations, we demonstrate its accuracy, validity and overwhelming superiority in computational speed. Furthermore, we compare our method with other hybrid methods, specifically, with the closest one -- AtC (Atomic to Continuum) method. We demonstrate a significant superiority of our approach in computational speed and implementation convenience. Finally, we discuss a possible extension of the method for modeling other phenomena.

翻译：我们提出了一种新颖的混合方法，用于对固体关键区域（接触表面、裂纹区域等）进行同步原子模拟，同时对其他部分进行连续介质建模。连续介质通过不同尺寸的准原子进行处理，构成复合介质。准原子间相互作用势的参数经过优化，以使复合介质的弹性特性与原子介质的特性相匹配。该优化方法在概念上与在线机器学习方法一致，使其在计算上非常高效。这种方法允许直接应用标准分子动力学软件包，并辅以基于机器学习的优化器。新方法应用于具有简单对式Lennard-Jones势的模型系统，以及描述共价键的多体Tersoff势。使用LAMMPS软件，我们模拟了不同尺寸粒子的碰撞。通过将新方法获得的模拟结果与全原子模拟进行比较，我们证明了其准确性、有效性以及在计算速度上的显著优势。此外，我们将我们的方法与其他混合方法，特别是最接近的原子至连续介质方法进行了比较。我们证明了我们的方法在计算速度和实现便利性上的显著优越性。最后，我们讨论了该方法在模拟其他现象方面的可能扩展。