Zobrazeno 1 - 10
of 208
pro vyhledávání: '"Hu CE"'
Autor:
Ren, Jie, Zhao, Chenya, He, Lanshan, Wu, Congcong, Jia, Wenting, Xu, Shengwen, Ye, Daojian, Xu, Weiyang, Huang, Fujin, Zhou, Hang, Zou, Chengwu, Hu, Ce, Yu, Ting, Luo, Xingfang, Yuan, Cailei
Self-doping can not only suppress the photogenerated charge recombination of semiconducting quantum dots by self-introducing trapping states within the bandgap, but also provide high-density catalytic active sites as the consequence of abundant non-s
Externí odkaz:
http://arxiv.org/abs/2304.06422
This work presents data analysis on Pb-Pb collisions at $\sqrt{s_{\rm NN}}$=2.76 TeV with centrality $40\%-50\%$. We present introduction and Monte-Carlo simulation results of the Glauber model, which shed light on the initial geometric configuration
Externí odkaz:
http://arxiv.org/abs/2109.12802
Autor:
Hu, Ce-ran, Xing, Zhi-zhong
With the help of current neutrino oscillation data, we illustrate the three-dimensional (3D) profiles of all the six distinct effective Majorana neutrino masses $|\langle m\rangle^{}_{\alpha \beta}|$ (for $\alpha, \beta = e, \mu, \tau$) with respect
Externí odkaz:
http://arxiv.org/abs/2108.00986
Autor:
Huang, Yuan, Zhou, Hang, Luo, Xingfang, Zhan, Helong, Xu, Weiyang, Ye, Daojian, Wu, Congcong, Hu, Ce, Lei, Wen, Yuan, Cailei
Publikováno v:
In Chemical Engineering Journal 15 April 2024 486
Machine learning methods have nowadays become easy-to-use tools for constructing high-dimensional interatomic potentials with ab initio accuracy. Although machine learned interatomic potentials are generally orders of magnitude faster than first-prin
Externí odkaz:
http://arxiv.org/abs/2006.16482
Publikováno v:
J. Phys. Chem. B 2020
Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models targeting tensorial properties, which are rotationally covariant. Here, we p
Externí odkaz:
http://arxiv.org/abs/2004.13605
Akademický článek
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Autor:
Lv, Quanshan, Yan, Faguang, Mori, Nobuya, Zhu, Wenkai, Hu, Ce, Kudrynskyi, Zakhar R., Kovalyuk, Zakhar D., Patanè, Amalia, Wang, Kaiyou
Atomically thin layers of van der Waals (vdW) crystals offer an ideal material platform to realize tunnel field effect transistors (TFETs) that exploit the tunneling of charge carriers across the forbidden gap of a vdW heterojunction. This type of de
Externí odkaz:
http://arxiv.org/abs/2001.10273
Publikováno v:
J. Phys. Chem. Lett.2019,10,17,4962-4967
We propose a simple, but efficient and accurate machine learning (ML) model for developing high-dimensional potential energy surface. This so-called embedded atom neural network (EANN) approach is inspired by the well-known empirical embedded atom me
Externí odkaz:
http://arxiv.org/abs/1907.06159
Atomically thin two dimensional (2D) materials are promising candidates for miniaturized high-performance optoelectronic devices. Here, we report on multilayer MoTe2 photodetectors contacted with asymmetric electrodes based on n- and p-type graphene
Externí odkaz:
http://arxiv.org/abs/1903.08833