Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Shengxiang Ma"'
Autor:
Fang Liu, Geng Sun, Hao Bin Wu, Gen Chen, Duo Xu, Runwei Mo, Li Shen, Xianyang Li, Shengxiang Ma, Ran Tao, Xinru Li, Xinyi Tan, Bin Xu, Ge Wang, Bruce S. Dunn, Philippe Sautet, Yunfeng Lu
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
The sluggish electrochemical kinetics of sulfur species remains a major hurdle for the broad adoption of lithium-sulfur batteries. Here, the authors construct an energy diagram of sulfur species to unveil their reaction pathways and propose a general
Externí odkaz:
https://doaj.org/article/342588b7e0b741a99ee15ce26f56c98d
Publikováno v:
2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::622dfe7dea09a64a042fa2f563bc24c6
https://doi.org/10.1109/itaic54216.2022.9836732
https://doi.org/10.1109/itaic54216.2022.9836732
Autor:
Xianyang Li, Bin Xu, Philippe Sautet, Fang Liu, Xinru Li, Li Shen, Shengxiang Ma, Yunfeng Lu, Runwei Mo, Xinyi Tan, Bruce Dunn, Gen Chen, Hao Bin Wu, Ge Wang, Geng Sun, Duo Xu, Ran Tao
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
Nature communications, vol 11, iss 1
Nature Communications
Nature communications, vol 11, iss 1
Nature Communications
The sluggish electrochemical kinetics of sulfur species has impeded the wide adoption of lithium-sulfur battery, which is one of the most promising candidates for next-generation energy storage system. Here, we present the electronic and geometric st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82e3e1290bb92b7fe40b6a815e99e08b
https://doaj.org/article/342588b7e0b741a99ee15ce26f56c98d
https://doaj.org/article/342588b7e0b741a99ee15ce26f56c98d
Publikováno v:
ACS Applied Materials & Interfaces. 12:39127-39134
Silicon is one of the most promising anode materials for lithium-ion batteries due to its high theoretical capacity and low cost. However, significant capacity fading caused by severe structural degradation during cycling limits its practical implica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4a54fed050e8517a4dda0a9d0e4b33d
https://doi.org/10.1021/acsami.0c09938
https://doi.org/10.1021/acsami.0c09938
Publikováno v:
Nanoscale Horizons. 4:705-711
The low Li+ transference number (tLi+), or the relatively small proportion of Li+ conductivity with respect to total ionic conductivity, has been identified as a key drawback of binary electrolytes. The lack of approaches to restrain anion mobility r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab883cb4370db18e7dae7b8694fd2e8a
https://doi.org/10.1039/c8nh00342d
https://doi.org/10.1039/c8nh00342d
Publikováno v:
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).
In order to improve the accuracy of the gangue powder concrete compressive strength prediction model, the factor analysis method is combined with the BP neural network method to propose an improved BP neural network gangue powder concrete compressive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2988d795d6b13a0a075c3cf3f2d94534
https://doi.org/10.1109/itaic49862.2020.9339112
https://doi.org/10.1109/itaic49862.2020.9339112
Publikováno v:
2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA).
In order to improve the feasibility and accuracy of the concrete comprehensive performance prediction model, the factor analysis method and the BP neural network method are combined to propose an improved BP neural network concrete comprehensive perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16be41b2c6907f7da186e53d802b53f6
https://doi.org/10.1109/iciba50161.2020.9277249
https://doi.org/10.1109/iciba50161.2020.9277249
Publikováno v:
2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA).
In order to improve the accuracy of the blasting vibration frequency prediction model, a factor analysis method is combined with the BP neural network method to propose an improved BP neural network blasting vibration frequency prediction model. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::469d7ea0853193df8499c07cc20237ca
https://doi.org/10.1109/iciba50161.2020.9276997
https://doi.org/10.1109/iciba50161.2020.9276997
Autor:
Dong Zhang, Qian Liu, Li Shen, Hao Bin Wu, Chen Zhang, Fang Liu, Huijuan Yue, Jesse Baucom, Shengxiang Ma, Yunfeng Lu, Wenyue Shi
Publikováno v:
ACS applied materialsinterfaces. 12(39)
A new family of solid-like electrolytes was developed by infiltrating MIL-100(Al), an electrochemically stable metal-organic-framework (MOF) material, with liquid electrolytes that contain cations from the 3rd period (Na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9bb2989403ca5c2c6a1615d7adbf32d
https://pubmed.ncbi.nlm.nih.gov/32896128
https://pubmed.ncbi.nlm.nih.gov/32896128
Autor:
Dejia, Kong, Li, Shen, Runwei, Mo, Jiaxu, Liu, Ran, Tao, Wenyue, Shi, Shengxiang, Ma, Chen, Zhang, Yunfeng, Lu
Publikováno v:
Nanoscale. 12(26)
Particular recent interest has been given to the Li
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::9077ec792deaa8cb62fdc2eafb4cb764
https://pubmed.ncbi.nlm.nih.gov/32588865
https://pubmed.ncbi.nlm.nih.gov/32588865