FLAME：原子建模环境库
FLAME: a library of atomistic modeling environments
摘要：
FLAME是一个用于探索复杂凝聚态系统的势能面（PES）的原子模拟软件包。方法的范围包括分子动力学模拟，以采样自由能景观，鞍点搜索，以确定过渡态，和梯度松弛，以找到动态稳定的几何形状。除了这些常见的任务，FLAME实现了一个结构预测算法的基础上的最小跳跃方法（MHM），以确定任何系统的基态结构，仅给出的化学成分，和一个框架，训练神经网络的潜力，从$\textit{ab initio}$计算再现PES。FLAME中神经网络势与MHM的组合允许高效和可靠地识别分子和晶体的基态以及亚稳结构，以及纳米结构，包括表面、界面和二维材料。在这篇手稿中，我们提供了在FLAME代码中实现的方法及其功能的详细描述，以及几个说明性的例子。
英文摘要：
FLAME is a software package to perform a wide range of atomistic simulations for exploring the potential energy surfaces (PES) of complex condensed matter systems. The range of methods include molecular dynamics simulations to sample free energy landscapes, saddle point searches to identify transition states, and gradient relaxations to find dynamically stable geometries. In addition to such common tasks, FLAME implements a structure prediction algorithm based on the minima hopping method (MHM) to identify the ground state structure of any system given solely the chemical composition, and a framework to train a neural network potential to reproduce the PES from $\textit{ab initio}$ calculations. The combination of neural network potentials with the MHM in FLAME allows a highly efficient and reliable identification of the ground state as well as metastable structures of molecules and crystals, as well as of nano structures, including surfaces, interfaces, and two-dimensional materials. In this manuscript, we provide detailed descriptions of the methods implemented in the FLAME code and its capabilities, together with several illustrative examples.
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