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Full-Text Articles in Engineering
Confning Tio2 Nanotubes In Pecvd‑Enabled Graphene Capsules Toward Ultrafast K‑Ion Storage: In Situ Tem/Xrd Study And Dft Analysis, Jingsheng Cai, Ran Cai, Zhongti Sun, Xiangguo Wang, Nan Wei, Feng Xu, Yuanlong Shao, Peng Gao, Shi Xue Dou, Jingyu Sun
Confning Tio2 Nanotubes In Pecvd‑Enabled Graphene Capsules Toward Ultrafast K‑Ion Storage: In Situ Tem/Xrd Study And Dft Analysis, Jingsheng Cai, Ran Cai, Zhongti Sun, Xiangguo Wang, Nan Wei, Feng Xu, Yuanlong Shao, Peng Gao, Shi Xue Dou, Jingyu Sun
Australian Institute for Innovative Materials - Papers
© 2020, © 2020, The Author(s). Titanium dioxide (TiO2) has gained burgeoning attention for potassium-ion storage because of its large theoretical capacity, wide availability, and environmental benignity. Nevertheless, the inherently poor conductivity gives rise to its sluggish reaction kinetics and inferior rate capability. Here, we report the direct graphene growth over TiO2 nanotubes by virtue of chemical vapor deposition. Such conformal graphene coatings effectively enhance the conductive environment and well accommodate the volume change of TiO2 upon potassiation/depotassiation. When paired with an activated carbon cathode, the graphene-armored TiO2 nanotubes allow the potassium-ion hybrid capacitor full cells to harvest an energy/power …
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
Faculty of Engineering and Information Sciences - Papers: Part B
Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …
Fault-Tolerant Analysis And Design Of Afpmsm With Multi-Disc Type Coreless Open-End Winding, Xiaoguang Wang, Meng Zhao, Lei Tang, Wei Xu, Md Rabiul Islam
Fault-Tolerant Analysis And Design Of Afpmsm With Multi-Disc Type Coreless Open-End Winding, Xiaoguang Wang, Meng Zhao, Lei Tang, Wei Xu, Md Rabiul Islam
Faculty of Engineering and Information Sciences - Papers: Part B
This article presents a multi-disc coreless axial flux permanent magnet synchronous machine (MDC-AFPMSM) with N pole and S pole type series magnetic circuit and open-end winding for high reliability applications, such as small power actuator system. Firstly, the topology and driving modes of MDC-AFPMSM are presented in details. In this article, a multi-objective optimization function is proposed to design the machine with full consideration of various influence factors. The drive performance indexes of four-phase, five-phase and six-phase machines are analyzed and discussed. Furthermore, main parameters of the five-phase MDC-AFPMSM with open-end winding are calculated. In order to reduce the torque …
A Framework Towards Data Analysis On Host-Pathogen Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song
A Framework Towards Data Analysis On Host-Pathogen Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song
Faculty of Engineering and Information Sciences - Papers: Part B
With the rapid development of high-throughput technologies, systems biology is now embracing a great opportunity made possible by the increased accumulation of data available online. Biological data analytics is considered as a critical means to contribute to a better understanding on such data through extraction of the latent features, relationships and the associated mechanisms. Therefore, it is important to evaluate how to involve data analytics from both computational and biological perspectives in practice. This paper has investigated interaction relationships in the proteomics area, which provide insights of the critical molecular processes within infection mechanisms. Specifically, we focused on host–pathogen protein–protein …
Nonlinear Analysis Of Square Concrete-Filled Double Steel Tubular Slender Columns Incorporating Preload Effects, Mizan Ahmed, Qing Quan Liang, Vipulkumar I. Patel, Muhammad N. S Hadi
Nonlinear Analysis Of Square Concrete-Filled Double Steel Tubular Slender Columns Incorporating Preload Effects, Mizan Ahmed, Qing Quan Liang, Vipulkumar I. Patel, Muhammad N. S Hadi
Faculty of Engineering and Information Sciences - Papers: Part B
Thin-walled square and circular hollow steel tubes are designed to support the permanent and construction loads of several upper composite floors before filling the concrete into the tubes to form concrete-filled double steel tubular (CFDST) columns. The influences of preloads acting on the steel tubes on the structural responses of slender square CFDST columns have not been investigated either experimentally or numerically. This paper presents a fiber-based computational model for the determination of the interaction behavior of local and global buckling in axially and eccentrically loaded CFDST thin-walled square slender columns including preload effects. The computational modeling method accounts for …