South China University of Technology

About: South China University of Technology is a education organization based out in Guangzhou, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 62343 authors who have published 69468 publications receiving 1251592 citations. The organization is also known as: SCUT & Huánán Lǐgōng Dàxué.

One-step synthesis of Ni3S2 nanorod@Ni(OH)2nanosheet core–shell nanostructures on a three-dimensional graphene network for high-performance supercapacitors

Abstract: A three-dimensional graphene network (3DGN) grown on nickel foam is an excellent template for the synthesis of graphene-based composite electrodes for use in supercapacitors. Ni(OH)2nanosheets coated onto single-crystal Ni3S2nanorods grown on the surface of the 3DGN (referred to as the Ni3S2@Ni(OH)2/3DGN) are synthesized using a one-step hydrothermal reaction. SEM, TEM, XRD and Raman spectroscopy are used to investigate the morphological and structural evolution of the Ni3S2@Ni(OH)2/3DGN. Detailed electrochemical characterization shows that the Ni3S2@Ni(OH)2/3DGN exhibits high specific capacitance (1277 F g−1 at 2 mV s−1 and 1037.5 F g−1 at 5.1 A g−1) and areal capacitance (4.7 F cm−2 at 2 mV s−1 and 3.85 F cm−2 at 19.1 mA cm−2) with good cycling performance (99.1% capacitance retention after 2000 cycles).

Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems

Abstract: With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer.

Abstract: Purpose To develop a radiomics signature to estimate disease-free survival (DFS) in patients with early-stage (stage I-II) non-small cell lung cancer (NSCLC) and assess its incremental value to the traditional staging system and clinical-pathologic risk factors for individual DFS estimation. Materials and Methods Ethical approval by the institutional review board was obtained for this retrospective analysis, and the need to obtain informed consent was waived. This study consisted of 282 consecutive patients with stage IA-IIB NSCLC. A radiomics signature was generated by using the least absolute shrinkage and selection operator, or LASSO, Cox regression model. Association between the radiomics signature and DFS was explored. Further validation of the radiomics signature as an independent biomarker was performed by using multivariate Cox regression. A radiomics nomogram with the radiomics signature incorporated was constructed to demonstrate the incremental value of the radiomics signature to the traditional staging system and other clinical-pathologic risk factors for individualized DFS estimation, which was then assessed with respect to calibration, discrimination, reclassification, and clinical usefulness. Results The radiomics signature was significantly associated with DFS, independent of clinical-pathologic risk factors. Incorporating the radiomics signature into the radiomics-based nomogram resulted in better performance (P < .0001) for the estimation of DFS (C-index: 0.72; 95% confidence interval [CI]: 0.71, 0.73) than with the clinical-pathologic nomogram (C-index: 0.691; 95% CI: 0.68, 0.70), as well as a better calibration and improved accuracy of the classification of survival outcomes (net reclassification improvement: 0.182; 95% CI: 0.02, 0.31; P = .02). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinical-pathologic nomogram. Conclusion The radiomics signature is an independent biomarker for the estimation of DFS in patients with early-stage NSCLC. Combination of the radiomics signature, traditional staging system, and other clinical-pathologic risk factors performed better for individualized DFS estimation in patients with early-stage NSCLC, which might enable a step forward precise medicine. © RSNA, 2016 Online supplemental material is available for this article.

High Performance Fe- and N- Doped Carbon Catalyst with Graphene Structure for Oxygen Reduction

Abstract: High Performance Fe- and N- Doped Carbon Catalyst with Graphene Structure for Oxygen Reduction