Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Dong, Haikuan"'
Autor:
Dong, Haikuan, Shi, Yongbo, Ying, Penghua, Xu, Ke, Liang, Ting, Wang, Yanzhou, Zeng, Zezhu, Wu, Xin, Zhou, Wenjiang, Xiong, Shiyun, Chen, Shunda, Fan, Zheyong
Publikováno v:
J. Appl. Phys. 135, 161101 (2024)
Molecular dynamics (MD) simulations play an important role in understanding and engineering heat transport properties of complex materials. An essential requirement for reliably predicting heat transport properties is the use of accurate and efficien
Externí odkaz:
http://arxiv.org/abs/2401.16249
Autor:
Song, Keke, Zhao, Rui, Liu, Jiahui, Wang, Yanzhou, Lindgren, Eric, Wang, Yong, Chen, Shunda, Xu, Ke, Liang, Ting, Ying, Penghua, Xu, Nan, Zhao, Zhiqiang, Shi, Jiuyang, Wang, Junjie, Lyu, Shuang, Zeng, Zezhu, Liang, Shirong, Dong, Haikuan, Sun, Ligang, Chen, Yue, Zhang, Zhuhua, Guo, Wanlin, Qian, Ping, Sun, Jian, Erhart, Paul, Ala-Nissila, Tapio, Su, Yanjing, Fan, Zheyong
Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicability. Here, we present a feasible approach for constructing a unified g
Externí odkaz:
http://arxiv.org/abs/2311.04732
Publikováno v:
J. Phys.: Condens. Matter, 2024, 36, 245901
We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroevolution potential is trained using reference data from quantum-mechan
Externí odkaz:
http://arxiv.org/abs/2310.15314
Publikováno v:
International Journal of Heat and Mass Transfer, 206, 123943(2023)
Recently a novel two-dimensional (2D) C$_{60}$ based crystal called quasi-hexagonal-phase fullerene (QHPF) has been fabricated and demonstrated to be a promising candidate for 2D electronic devices [Hou et al. Nature 606, 507-510 (2022)]. We construc
Externí odkaz:
http://arxiv.org/abs/2208.03982
Autor:
Wu, Xiguang, Zhou, Wenjiang, Dong, Haikuan, Ying, Penghua, Wang, Yanzhou, Song, Bai, Fan, Zheyong, Xiong, Shiyun
Publikováno v:
Journal of Chemical Physics; 7/7/2024, Vol. 161 Issue 1, p1-9, 9p
Publikováno v:
Physica E: Low-dimensional Systems and Nanostructures 144, 2022, 115410
In a previous paper [Physical Review B \textbf{103}, 035417 (2021)], we showed that the equilibrium molecular dynamics (EMD) method can be used to compute the apparent thermal conductivity of finite systems. It has been shown that the apparent therma
Externí odkaz:
http://arxiv.org/abs/2207.13405
Autor:
Fan, Zheyong, Wang, Yanzhou, Ying, Penghua, Song, Keke, Wang, Junjie, Wang, Yong, Zeng, Zezhu, Xu, Ke, Lindgren, Eric, Rahm, J. Magnus, Gabourie, Alexander J., Liu, Jiahui, Dong, Haikuan, Wu, Jianyang, Chen, Yue, Zhong, Zheng, Sun, Jian, Erhart, Paul, Su, Yanjing, Ala-Nissila, Tapio
Publikováno v:
Journal of Chemical Physics 157, 114801 (2022)
We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package GPUMD. We in
Externí odkaz:
http://arxiv.org/abs/2205.10046
Publikováno v:
Journal of Applied Physics 130, 235102 (2021)
We study the interfacial thermal conductance of grain boundaries (GBs) between monolayer graphene and hexagonal boron nitride (h-BN) sheets using a combined atomistic approach. First, realistic samples containing graphene/h-BN GBs with different tilt
Externí odkaz:
http://arxiv.org/abs/2111.14289
Publikováno v:
In International Journal of Heat and Mass Transfer 1 June 2024 224
Autor:
Fan, Zheyong, Zeng, Zezhu, Zhang, Cunzhi, Wang, Yanzhou, Dong, Haikuan, Chen, Yue, Ala-Nissila, Tapio
Publikováno v:
Phys. Rev. B 104, 104309 (2021)
We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy for performing large-scale molecular dynamics (MD) simulations. A descriptor of the
Externí odkaz:
http://arxiv.org/abs/2107.08119