Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Zhuodong Tang"'
Autor:
Ruixin Yang, Yanming Cai, Yongbing Qi, Zhuodong Tang, Jun-Jie Zhu, Jinxiang Li, Wenlei Zhu, Zixuan Chen
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract C–C coupling is of utmost importance in the electrocatalytic reduction of CO2, as it governs the selectivity of diverse product formation. Nevertheless, the difficulties to directly observe C–C coupling pathways at a specific nanocavity
Externí odkaz:
https://doaj.org/article/83085d94c2474c26974e73b3fa2ea420
Publikováno v:
JACS Au, Vol 4, Iss 3, Pp 1155-1165 (2024)
Externí odkaz:
https://doaj.org/article/ce58786f08c14e59bc2e72fc8bd195b9
Autor:
Di Gao, Zhuodong Tang, Xueqin Chen, Rong Wu, Ye Tian, Qianhao Min, Jian-Rong Zhang, Zixuan Chen, Jun-Jie Zhu
Publikováno v:
Nano Letters. 23:4201-4208
Publikováno v:
ACS Nano. 16:20842-20850
Probing of the single-cell level extracellular electron transfer highlights the maximum output current for microbial fuel cells (MFCs) at hundreds of femtoampere per cell, which is difficult to achieve by existing devices. Past studies focus on the e
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Journal of the American Chemical Society. 141:16071-16078
Measuring binding between molecules is critical for understanding basic biochemical processes, developing molecular diagnosis, and screening drugs. Here we study molecular binding at the single molecule level by attaching nanoparticles to the molecul
Publikováno v:
Lecture Notes in Operations Research ISBN: 9783030902742
Lecture Notes in Operations Research
Lecture Notes in Operations Research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25ebbcc334607e1b5425da4ded13ad2b
https://doi.org/10.1007/978-3-030-90275-9_16
https://doi.org/10.1007/978-3-030-90275-9_16
Publikováno v:
SSRN Electronic Journal.
We show the equivalence of discrete choice models and a forest of binary decision trees. This suggests that standard machine learning techniques based on random forests can serve to estimate discrete choice models with an interpretable output: the un
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America; 6/8/2021, Vol. 118 Issue 23, p1-8, 8p