Wang Jiaxing, Wang Ya, Huang Yang, Peijnenburg Willie J G M, Chen Jingwen, Li Xuehua
Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology Linggong Road 2 Dalian 116024 China
Institute of Environmental Sciences, Leiden University 2300 RA Leiden The Netherlands.
RSC Adv. 2019 Mar 14;9(15):8426-8434. doi: 10.1039/c8ra10226k. eCollection 2019 Mar 12.
Antibacterial activities and cytotoxicity of metal oxide nanoparticles are determined by their special band structures, which also influence their potential ecological risks. Traditional experimental determination of the band gap is time-consuming, while the accuracy of theoretical computation depends on the selected algorithm, for which higher precision algorithms, being more expensive, can give a more accurate band gap. Therefore, in this study, a quantitative structure-property relationship (QSPR) model, highlighting the influence of crystalline type and material size, was developed to predict the band gap of metal oxide nanoparticles rapidly and accurately. The structural descriptors for metal oxide nanoparticles were generated quantum chemistry computations, among which heat of formation and beta angle of the unit cell were the most important parameters influencing band gaps. The developed model shows great robustness and predictive ability ( = 0.848, RMSE = 0.378 eV, RMSE = 0.478 eV, = 0.814, RMSE = 0.408 eV). The current study can assist in screening the ecological risks of existing metal oxide nanoparticles and may act as a reference for newly designed materials.
金属氧化物纳米颗粒的抗菌活性和细胞毒性由其特殊的能带结构决定，这也影响着它们潜在的生态风险。传统的带隙实验测定耗时，而理论计算的准确性取决于所选算法，对于更高精度的算法，因其成本更高，能给出更准确的带隙。因此，在本研究中，开发了一种突出晶体类型和材料尺寸影响的定量结构-性质关系（QSPR）模型，以快速准确地预测金属氧化物纳米颗粒的带隙。金属氧化物纳米颗粒的结构描述符通过量子化学计算生成，其中生成热和晶胞的β角是影响带隙的最重要参数。所开发的模型显示出很强的稳健性和预测能力（R = 0.848，RMSE = 0.378 eV，RMSE = 0.478 eV，R = 0.814，RMSE = 0.408 eV）。当前的研究有助于筛选现有金属氧化物纳米颗粒的生态风险，并可为新设计的材料提供参考。
