Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Yinpeng Wan"'
Autor:
Kai Guo, Wenchong Cheng, Haiyuan Liu, Wenhao She, Yinpeng Wan, Heng Wang, Hanbin Li, Zidan Li, Xing Zhong, Jinbo Ouyang, Neng Yu
Publikováno v:
Crystals, Vol 12, Iss 11, p 1617 (2022)
Water molecules and cations with mono, binary, and triple valences have been intercalated into V2O5 to significantly improve its electrochemical properties as a cathode material of zinc-ion batteries. Sn as a tetravalent element is supposed to intera
Externí odkaz:
https://doaj.org/article/bfc830aefbda4bbf9d3c62c23ae16051
Autor:
Kai Guo, Wenchong Cheng, Haoxiong Chen, Hanbin Li, Jinxue Chen, Haiyuan Liu, Yunliang Tu, Wenhao She, Zhengkai Huang, Yinpeng Wan, Lixia Zou, Zhuyao Li, Xing Zhong, Yongchuan Wu, Xianfu Wang, Neng Yu
Publikováno v:
Nanomaterials, Vol 12, Iss 14, p 2400 (2022)
Hydrated V2O5 with unique physical and chemical characteristics has been widely used in various function devices, including solar cells, catalysts, electrochromic windows, supercapacitors, and batteries. Recently, it has attracted extensive attention
Externí odkaz:
https://doaj.org/article/6b4ee75bfad64313ba8f25b95dd3c389
Autor:
Neng Yu, Yanpeng Li, Wenhao She, Hanbin Li, Haoxiong Chen, Wenchong Cheng, Jinxue Chen, Haiyuan Liu, Yunliang Tu, Zhengkai Huang, Yinpeng Wan, Lixia Zou, Xing Zhong, null JunmingLuo, Kai Guo
Publikováno v:
ACS applied materialsinterfaces. 14(45)
Aqueous Zn battery has been a promising alternative battery in large-scale energy storage systems due to its cost-effectiveness, sustainability, and intrinsic safety. However, its cycle life is impeded by the dendrite formation, severe corrosion, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3f99b73a5ff651e1b86bda61f7f2ea0
https://pubmed.ncbi.nlm.nih.gov/36326025
https://pubmed.ncbi.nlm.nih.gov/36326025
Publikováno v:
International Journal of Thermofluids, Vol 23, Iss , Pp 100726- (2024)
Multiphysics analysis, involving the coupled phenomena of various physics fields, such as electro-mechanical, thermofluidic, thermoelectric, and thermo-hygric phenomena, plays a critical role in advancing technology and engineering disciplines. Conve
Externí odkaz:
https://doaj.org/article/aa6119b4ff0f4660ab89356c23c26542
Publikováno v:
Separations, Vol 11, Iss 3, p 88 (2024)
Chemical composition is a critical factor for determining the efficacy of any traditional Chinese medicine (TCM) and can be used as an indicator of commercial quality. To develop a new strategy for discovering potential quality markers (Q-markers) of
Externí odkaz:
https://doaj.org/article/cbc58d6ad3f34f049fce371b6664c91a
Publikováno v:
Molecules, Vol 28, Iss 18, p 6448 (2023)
The quality of Schisandra chinensis (Turcz.) Baill. (S. chinensis) is principally attributed to lignan compounds. In this paper, a simple and rapid strategy for simultaneous extraction and determination of 10 lignans from S. chinensis was established
Externí odkaz:
https://doaj.org/article/be341ab4de7140189f6e2aa630d6eb36
Autor:
Zhiyuan Liu, Jihong Yuan, Ping Wen, Xiaofei Guo, Kelei Li, Yinpeng Wang, Ruirui Liu, Yanjun Guo, Duo Li
Publikováno v:
Foods, Vol 12, Iss 9, p 1894 (2023)
Humans have consumed lard for thousands of years, but in recent decades, it has become much less popular because it is regarded as saturated fat. Animal studies showed that lard plus soybean oil (blend oil) was more advantageous for liver health than
Externí odkaz:
https://doaj.org/article/1b2d536b76d549bab628d78eccd25379
Publikováno v:
Case Studies in Thermal Engineering, Vol 33, Iss , Pp 101927- (2022)
Existing algorithms with iterations as the principle for 3D inverse heat conduction problems (IHCPs) are usually time-consuming and resource-demanding. With the recent advancements in deep learning techniques, it is possible to apply the neural netwo
Externí odkaz:
https://doaj.org/article/94c8f05c73c740f1bda86ecf86f1b211
Autor:
Yongzhong Li, Yinpeng Wang, Shutong Qi, Qiang Ren, Lei Kang, Sawyer D. Campbell, Pingjuan L. Werner, Douglas H. Werner
Publikováno v:
IEEE Access, Vol 8, Pp 139983-139993 (2020)
Existing numerical electromagnetic (EM) solvers are usually computationally expensive, time consuming, and memory demanding. Recent advances in deep learning (DL) techniques have demonstrated superior efficiency and provide an alternative pathway for
Externí odkaz:
https://doaj.org/article/24dbc9196d7e48e7b57d23170be9097f