Krishnapriyan A, Yang P, Niklasson A M N, Cawkwell M J
Department of Materials Science and Engineering, Stanford University , Stanford, California 94305, United States.
Theoretical Division, Los Alamos National Laboratory , Los Alamos, New Mexico 87545, United States.
J Chem Theory Comput. 2017 Dec 12;13(12):6191-6200. doi: 10.1021/acs.jctc.7b00762. Epub 2017 Nov 7.
New parametrizations for semiempirical density functional tight binding (DFTB) theory have been developed by the numerical optimization of adjustable parameters to minimize errors in the atomization energy and interatomic forces with respect to ab initio calculated data. Initial guesses for the radial dependences of the Slater-Koster bond integrals and overlap integrals were obtained from minimum basis density functional theory calculations. The radial dependences of the pair potentials and the bond and overlap integrals were represented by simple analytic functions. The adjustable parameters in these functions were optimized by simulated annealing and steepest descent algorithms to minimize the value of an objective function that quantifies the error between the DFTB model and ab initio calculated data. The accuracy and transferability of the resulting DFTB models for the C, H, N, and O system were assessed by comparing the predicted atomization energies and equilibrium molecular geometries of small molecules that were not included in the training data from DFTB to ab initio data. The DFTB models provide accurate predictions of the properties of hydrocarbons and more complex molecules containing C, H, N, and O.
通过对可调参数进行数值优化，以最小化相对于从头算数据的原子化能量和原子间力的误差，从而开发了半经验密度泛函紧束缚（DFTB）理论的新参数化方法。斯莱特 - 科斯特键积分和重叠积分的径向依赖性的初始猜测值是从最小基密度泛函理论计算中获得的。对势以及键积分和重叠积分的径向依赖性由简单的解析函数表示。这些函数中的可调参数通过模拟退火和最速下降算法进行优化，以最小化一个目标函数的值，该目标函数量化了DFTB模型与从头算数据之间的误差。通过比较DFTB训练数据中未包含的小分子的预测原子化能量和平衡分子几何结构与从头算数据，评估了所得DFTB模型对C、H、N和O体系的准确性和可转移性。DFTB模型对碳氢化合物以及包含C、H、N和O的更复杂分子的性质提供了准确的预测。
