Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, USA.
J Chem Phys. 2023 Apr 14;158(14):144112. doi: 10.1063/5.0141616.
Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. Our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.
半经验量子模型,如密度泛函紧束缚(DFTB),是一种在比标准方法更长的时间和长度尺度上获得量子模拟数据的有吸引力的方法。然而,由于缺乏系统的开发方法,这些模型的应用可能需要大量的工作。在这项工作中,我们讨论了使用 Chebyshev Interaction Model for Efficient Simulation(ChIMES)来创建快速参数化的 DFTB 模型,由于包括了可能不准确的多体相互作用,这些模型具有很强的可转移性。我们将我们的建模方法应用于硅多晶型体,并回顾了以前关于氢化钛的工作。我们还回顾了用于有机分子和化合物的通用 DFTB/ChIMES 模型的创建,该模型接近混合功能和耦合簇精度,参数数量比类似的神经网络方法少两个数量级。在所有情况下,DFTB/ChIMES 的准确性与基础量子方法相似,但计算成本却有数量级的提高。我们的发展提供了一种在变化的极端热力学条件下创建计算效率高且高度准确的模拟的方法,在这些条件下,物理和化学性质很难直接探测,并且历史上对理论方法的依赖很大,用于解释和验证实验结果。