基于第一性原理与BP神经网络的V掺杂TiO2光电性质研究  

Photoelectric Properties of V-doped TiO2 Based on the First-principle and BP Neural Network

作　　者：李昌磊 杨平[1] LI Changlei;YANG Ping(Lab.of Adv.Design,Manufacturing&Reliability for MEMS/NEMS/OEDS,School of Mechanical Engineering,Jiangsu University,Zhenjiang 212000,China)

机构地区：[1]江苏大学机械工程学院,微纳光电子器件及系统先进制造与可靠性国际实验室,镇江212000

出　　处：《人工晶体学报》2020年第4期618-623,共6页Journal of Synthetic Crystals

摘　　要：通过采用密度泛函理论第一性原理计算,主要研究不同浓度下V掺杂TiO2的结构、能带、电导率、反射和吸收率的变化。建立本征TiO2和VxTi1-xO2(x=0.0625,0.125,0.1875)的掺杂模型,掺杂体系具有较高的电导率且具有N型半导体特征。通过BP神经网络对模型的能带结果进行训练,训练的模型数据结果发现掺杂后具有较高的电导率,禁带宽度明显降低。综合以上结果,在x=0.1875时实现最佳电导率和光学性能。Based on the density functional theory,the change of structure,energy band,conductivity,reflectivity and absorptivity of V-TiO2 of different concentration were investigated by first principle calculation.Intrinsic doping model of TiO2 and VxTi1-xO2(x=0.0625,0.125,0.1875)was established and the doping system is higher in conductivity with characteristics of N-type semiconductors.BP neural network was adopted to train the energy band results of the intrinsic doping model,and the data results of training model show that higher conductivity was achieved after doping and the energy gap was significantly reduced.Considering the above results,optimal conductivity and optical performance can be achieved when x=0.1875.

关 键 词：第一性原理 光学性质 BP神经网络 TIO2 

分 类 号：O474[理学—半导体物理]