Zheyong Fan

Zheyong Fan

Aalto-yliopisto

H-index: 32

Europe-Finland

About Zheyong Fan

Zheyong Fan, With an exceptional h-index of 32 and a recent h-index of 27 (since 2020), a distinguished researcher at Aalto-yliopisto, specializes in the field of electron transport, thermal transport, GPU computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Combining the D3 dispersion correction with the neuroevolution machine-learned potential

calorine: A Python package for constructing and sampling neuroevolution potential models

Solute segregation in polycrystalline aluminum from hybrid Monte Carlo and molecular dynamics simulations with a unified neuroevolution potential

Dissimilar thermal transport properties in κ-Ga2O3 and β-Ga2O3 revealed by homogeneous nonequilibrium molecular dynamics simulations using machine-learned potentials

Pushing thermal conductivity to its lower limit in crystals with simple structures

Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

Tensorial properties via the neuroevolution potential framework: Fast simulation of infrared and Raman spectra

Anomalous strain-dependent thermal conductivity in the metal-organic framework HKUST-1

Zheyong Fan Information

University

Position

Varian Medical Systems (Previously at )

Citations(all)

3229

Citations(since 2020)

2443

Cited By

1478

hIndex(all)

32

hIndex(since 2020)

27

i10Index(all)

64

i10Index(since 2020)

52

Email

University Profile Page

Aalto-yliopisto

Google Scholar

View Google Scholar Profile

Zheyong Fan Skills & Research Interests

electron transport

thermal transport

GPU computing

Top articles of Zheyong Fan

Title

Journal

Author(s)

Publication Date

Combining the D3 dispersion correction with the neuroevolution machine-learned potential

Journal of Physics: Condensed Matter

Penghua Ying

Zheyong Fan

2024

calorine: A Python package for constructing and sampling neuroevolution potential models

Journal of Open Source Software

Eric Lindgren

Magnus Rahm

Erik Fransson

Fredrik Eriksson

Nicklas Österbacka

...

2024/3/6

Solute segregation in polycrystalline aluminum from hybrid Monte Carlo and molecular dynamics simulations with a unified neuroevolution potential

arXiv preprint arXiv:2404.13694

Keke Song

Jiahui Liu

Shunda Chen

Zheyong Fan

Yanjing Su

...

2024/4/21

Dissimilar thermal transport properties in κ-Ga2O3 and β-Ga2O3 revealed by homogeneous nonequilibrium molecular dynamics simulations using machine-learned potentials

Journal of Applied Physics

Xiaonan Wang

Jinfeng Yang

Penghua Ying

Zheyong Fan

Jin Zhang

...

2024/2/14

Pushing thermal conductivity to its lower limit in crystals with simple structures

Nature Communications

Zezhu Zeng

Xingchen Shen

Ruihuan Cheng

Olivier Perez

Niuchang Ouyang

...

2024/4/8

Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

arXiv preprint arXiv:2401.11427

Xiguang Wu

Wenjiang Zhou

Haikuang Dong

Penghua Ying

Yanzhou Wang

...

2024/1/21

Tensorial properties via the neuroevolution potential framework: Fast simulation of infrared and Raman spectra

arXiv preprint arXiv:2312.05233

Nan Xu

Petter Rosander

Christian Schäfer

Eric Lindgren

Nicklas Österbacka

...

2023/12/8

Anomalous strain-dependent thermal conductivity in the metal-organic framework HKUST-1

Physical Review B

Hongzhao Fan

Penghua Ying

Zheyong Fan

Yue Chen

Zhigang Li

...

2024/1/19

Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials

Journal of Physics: Condensed Matter

Zheyong Fan

Yang Xiao

Yanzhou Wang

Penghua Ying

Shunda Chen

...

2024/3/21

Thermodynamics of Water and Ice from a Fast and Scalable First-Principles Neuroevolution Potential

Journal of Chemical & Engineering Data

Zekun Chen

Margaret L Berrens

Kam-Tung Chan

Zheyong Fan

Davide Donadio

2024

Transferability of Machine Learning Models for Predicting Raman Spectra

The Journal of Physical Chemistry A

Mandi Fang

Shi Tang

Zheyong Fan

Yao Shi

Nan Xu

...

2024/3/13

Molecular dynamics simulations of heat transport using machine-learned potentials: A mini review and tutorial on GPUMD with neuroevolution potentials

Haikuan Dong

Yongbo Shi

Penghua Ying

Ke Xu

Ting Liang

...

2024/1/29

Vibrational anharmonicity results in decreased thermal conductivity of amorphous at high temperature

Physical Review B

Honggang Zhang

Xiaokun Gu

Zheyong Fan

Hua Bao

2023/7/28

Accurate prediction of heat conductivity of water by a neuroevolution potential

The Journal of Chemical Physics

Ke Xu

Yongchao Hao

Ting Liang

Penghua Ying

Jianbin Xu

...

2023/5/28

Method and apparatus to facilitate administering therapeutic radiation to a heterogeneous body

2023/1/24

TERMA scaling as an effective heterogeneity correction model for convolution‐based external‐beam photon dose calculations

Medical Physics

Linda Laakkonen

Zheyong Fan

Ari Harju

2023/5

A high-performance GPU implementation of the electron-phonon Wannier interpolation and the related transport properties

arXiv preprint arXiv:2306.16493

Zhe Liu

Bo Zhang

Zheyong Fan

Wu Li

2023/6/28

Tuning the through-plane lattice thermal conductivity in van der Waals structures through rotational (dis) ordering

ACS nano

Fredrik Eriksson

Erik Fransson

Christopher Linderälv

Zheyong Fan

Paul Erhart

2023/12/8

Atomistic insights into the mechanical anisotropy and fragility of monolayer fullerene networks using quantum mechanical calculations and machine-learning molecular dynamics …

Extreme Mechanics Letters

Penghua Ying

Haikuan Dong

Ting Liang

Zheyong Fan

Zheng Zhong

...

2023/1/1

Variable thermal transport in black, blue, and violet phosphorene from extensive atomistic simulations with a neuroevolution potential

International Journal of Heat and Mass Transfer

Penghua Ying

Ting Liang

Ke Xu

Jianbin Xu

Zheyong Fan

...

2023/3/1

See List of Professors in Zheyong Fan University(Aalto-yliopisto)

Co-Authors

H-index: 84
Krasheninnikov Arkady

Krasheninnikov Arkady

Aalto-yliopisto

H-index: 61
Tapio Ala-Nissila

Tapio Ala-Nissila

Aalto-yliopisto

H-index: 53
Davide Donadio

Davide Donadio

University of California, Davis

H-index: 49
Jin-Cheng Zheng

Jin-Cheng Zheng

Xiamen University

H-index: 42
Hannu-Pekka Komsa

Hannu-Pekka Komsa

Aalto-yliopisto

H-index: 40
Hua Bao

Hua Bao

Shanghai Jiao Tong University

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