Search research articles
Contact Us
Filters
Showing results (31-40 of 37) with videos related to
Page
of 4
Sort By:
You have reached the last page of results.
This site can display upto 37 results.
Nanoscale
|
May 26, 2021
Anomalous thermal conductivity enhancement in low dimensional resonant nanostructures due to imperfections
Hongying Wang, Yajuan Cheng, Zheyong Fan, et al.
Small (Weinheim an Der Bergstrasse, Germany)
|
March 7, 2025
Stress-Driven Grain Boundary Structural Transition in Diamond by Machine Learning Potential
Chenchen Lu, Zhen Li, Xinxin Sang, et al.
The Journal of Chemical Physics
|
February 12, 2025
Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
Penghua Ying, Wenjiang Zhou, Lucas Svensson, et al.
Journal of Chemical Theory and Computation
|
April 20, 2026
qNEP: A Highly Efficient Neuroevolution Potential with Dynamic Charges for Large-Scale Atomistic Simulations
Zheyong Fan, Benrui Tang, Esmée Berger, et al.
Nature Computational Science
|
July 8, 2026
NEP89: universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren, et al.
The Journal of Chemical Physics
|
September 22, 2022
GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
Zheyong Fan, Yanzhou Wang, Penghua Ying, et al.
Nature Communications
|
November 25, 2024
General-purpose machine-learned potential for 16 elemental metals and their alloys
Keke Song, Rui Zhao, Jiahui Liu, et al.
Page
of 4
Search research articles
Search
Showing results (31-40 of 37) with videos related to
Sort By:
Page
of 4
You have reached the last page of results.
This site can display upto 37 results.
Nanoscale
|
May 26, 2021
Anomalous thermal conductivity enhancement in low dimensional resonant nanostructures due to imperfections
Hongying Wang, Yajuan Cheng, Zheyong Fan, et al.
Small (Weinheim an Der Bergstrasse, Germany)
|
March 7, 2025
Stress-Driven Grain Boundary Structural Transition in Diamond by Machine Learning Potential
Chenchen Lu, Zhen Li, Xinxin Sang, et al.
The Journal of Chemical Physics
|
February 12, 2025
Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
Penghua Ying, Wenjiang Zhou, Lucas Svensson, et al.
Journal of Chemical Theory and Computation
|
April 20, 2026
qNEP: A Highly Efficient Neuroevolution Potential with Dynamic Charges for Large-Scale Atomistic Simulations
Zheyong Fan, Benrui Tang, Esmée Berger, et al.
Nature Computational Science
|
July 8, 2026
NEP89: universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren, et al.
The Journal of Chemical Physics
|
September 22, 2022
GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
Zheyong Fan, Yanzhou Wang, Penghua Ying, et al.
Nature Communications
|
November 25, 2024
General-purpose machine-learned potential for 16 elemental metals and their alloys
Keke Song, Rui Zhao, Jiahui Liu, et al.
Page
of 4