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Gao R.,Institute of Functional Material Chemistry | Cui J.,Institute of Functional Material Chemistry | Su Z.-M.,Institute of Functional Material Chemistry
Journal of Computational Chemistry | Year: 2015

A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R2(0.75), Q2(0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. © 2015 Wiley Periodicals, Inc.

Du D.,Institute of Functional Material Chemistry | Lan Y.,Institute of Functional Material Chemistry | Wang X.,Institute of Functional Material Chemistry | Shao K.,Institute of Functional Material Chemistry | And 2 more authors.
Solid State Sciences | Year: 2010

The reactions between trivacant Keggin polyanions and transition metal ions in the presence of organoamine resulted in the isolation of two new polyoxotungstates, that is, [Hen]2[Cu(en)2(H2O)]2{[Cu(en)2]2[X2W23CuO79]}·4H2O (X = Ge, 1; X = Si, 2; and en = 1,2-ethylenediamine). Single-crystal X-ray diffraction analyses reveal that the polyanions in 1 and 2 are constructed by saturated Keggin anions condensed through sharing common oxygen atoms into Keggin dimers, which are further fused by copper(II) bridging fragments into one-dimensional (1D) ladder-like chains and then extended to a 3D supramolecular framework through hydrogen bond interactions. The IR spectrum and X-ray powder diffraction have been studied in detail for compounds 1 and 2. The UV spectrum, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), the cyclic voltammetry and electrocatalytic activity toward the reduction of nitrite have also been studied for compound 1. © 2009 Elsevier Masson SAS. All rights reserved.

Gao T.,Northeast Normal University | Li H.,Northeast Normal University | Lu Y.-H.,Northeast Normal University | Li H.-B.,Institute of Functional Material Chemistry | And 2 more authors.
Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010 | Year: 2010

Least squares support vector machines (LSSVM) has been carried out in order to obtain a statistically meaningful analysis of the extended set of molecules. The combined HF with LSSVM correction approach (LSSVM/HF) has been applied to evaluate the transition energies of organic molecules. After LSSVM correction, the RMS deviations of the calculated transition energies reduce from 0.91 to 0.26 eV for HF methods. And, this LSSVM/HF is a excellent method to predict transition energies and extend the reliably and efficiently of calculated transition energies. © 2010 IEEE.

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