首页> 外文期刊>Journal of chemical theory and computation: JCTC >Numerical Optimization of Density Functional Tight Binding Models: Application to Molecules Containing Carbon, Hydrogen, Nitrogen, and Oxygen
【24h】

Numerical Optimization of Density Functional Tight Binding Models: Application to Molecules Containing Carbon, Hydrogen, Nitrogen, and Oxygen

机译:密度函数紧粘结模型的数值优化:含碳,氢,氮和氧的分子应用

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:通过可调参数的数值优化开发了半透明密度泛函紧密绑定(DFTB)理论的新参数化,以最小化AB Initio计算数据的雾化能量和互动力中的误差。从最小基密度泛函理论计算中获得了对Slatter-Koster键积分的径向依赖性和重叠积分的初始猜测。通过简单的分析功能表示该对电位和键合和重叠积分的径向依赖性。这些功能中的可调参数通过模拟的退火和最陡的缩减算法进行了优化,以最小化测量DFTB模型和AB Initio计算数据之间误差的目标函数的值。通过比较不包括在训练数据中的小分子的预测雾化能量和平衡分子几何来评估所得到的C,H,N和O系统的DFTB模型的准确性和可转换性。从DFTB到AB Initio数据。 DFTB模型提供了对含有C,H,N,和O.的碳氢化合物和更复杂的分子的性能的精确预测。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号