Keke Song

Fuzhou University — China

Engineering · Physical Sciences

19h-index1.2kcitations73works12.52yr avg
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Research Topics

Perovskite Materials and Applications(18), Machine Learning in Materials Science(9), Conducting polymers and applications(8), Catalytic Processes in Materials Science(7), Hydrogen embrittlement and corrosion behaviors in metals(7)

Publications73 total

Atomistic understanding of hydrogen bubble-induced embrittlement in tungsten enabled by machine learning molecular dynamics
npj Computational Materials·2026Open Access
Investigation of the transport behavior of BP and BAs using the Boltzmann transport equation and machine learning methods
Journal of Applied Physics·2026Open Access
Machine-learned interatomic potential for Fe–Co–X (X = Re, W) alloys: Ductility–brittleness behavior at finite temperatures
Materials & Design·2026Open Access
A study on corporate social responsibility of professional football clubs on fans’ consumption intentions in China
Frontiers in Physiology·2025Open Access
Effect of oxygen and nitrogen on hydrogen adsorption and permeation processes
Journal of Pipeline Science and Engineering·2025Open Access
Atomistic understanding of hydrogen bubble-induced embrittlement in tungsten enabled by machine learning molecular dynamics
arXiv (Cornell University)·2025Open Access
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
2025· 2 citedOpen Access
GPUMD 4.0: A high‐performance molecular dynamics package for versatile materials simulations with machine‐learned potentials
Materials Genome Engineering Advances·2025· 38 citedOpen Access
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
ArXiv.org·2025· 2 citedOpen Access
Sub-population evolutionary particle swarm optimization with dynamic fitness-distance balance and elite reverse learning for engineering design problems
Advances in Engineering Software·2025· 15 cited
Machine-learned interatomic potential for Fe–Co–X (X = Re, W) alloys: Ductility–brittleness behavior at finite temperatures
SSRN Electronic Journal·2025Open Access
Unraveling the transport behavior of BP and BAs using the Boltzmann transport equation and machine learning methods
SSRN Electronic Journal·2025Open Access
General-purpose machine-learned potential for 16 elemental metals and their alloys
Nature Communications·2024· 121 citedOpen Access
Mechanistic analysis of the coordination between MbEGS4 and MbEOMT in methyleugenol synthesis by Melaleuca bracteata F. Muell
Industrial Crops and Products·2024
DEMFFA: a multi-strategy modified Fennec Fox algorithm with mixed improved differential evolutionary variation strategies
Journal Of Big Data·2024· 7 citedOpen Access
Solute segregation in polycrystalline aluminum from hybrid Monte Carlo and molecular dynamics simulations with a unified neuroevolution potential
arXiv (Cornell University)·2024· 5 citedOpen Access
Understanding cellulose pyrolysis via ab initio deep learning potential field
Bioresource Technology·2024· 11 cited
Screening and Expression Analysis of POD Gene in POD-H2O2 Pathway on Bud Dormancy of Pear (Pyrus pyrifolia)
Forests·2024· 5 citedOpen Access
Designing hydrogen embrittlement-resistant grain boundary in steel by alloying elements segregation: First-principles calculations
Applied Surface Science·2024· 20 cited
A novel injectable hydrogel prepared from phenylboronic acid modified gelatin and oxidized-dextran for bone tissue engineering
International Journal of Biological Macromolecules·2024· 26 cited
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Frequent Co-authors

Ping Qian(17), Yanjing Su(10), Xiao‐Xu Wang(7), Xiaotong Li(7), Yifei Wang(7), Baokai Ren(7), Zheyong Fan(6), Jiahui Liu(6), Haikuan Dong(6), Chunqian Zhang(6), Penghua Ying(5), Eric Lindgren(5), Paul Erhart(5), Tapio Ala-Nissilä(5), Shunda Chen(5), Ye Su(5), Qing Liu(5), Yanzhou Wang(4), Zezhu Zeng(4), Ke Xu(4)