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Deep learning-based workflow for atomic image denoising and chemical identification
Ke Ma, Shiqiang Feng, Haihui Hu, Yimeng Cai, Dechao Chen, Lili Han*
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Deep learning-based workflow for atomic image denoising and chemical identification
Ke Ma, Shiqiang Feng, Haihui Hu, Yimeng Cai, Dechao Chen, Lili Han*
Submit a Manuscript
Level-shifted embedded cluster method may offer a viable alternative for the simulation of metal oxides
Zi-Jian Zhou, Xin-Ping Wu*
Chin. J. Struct. Chem., 2025, 44(5), 100471. DOI: 10.1016/j.cjsc.2024.100471
May 1, 2025
ABSTRACT
In conclusion, the LSEC method can effectively circumvent the shortcomings of the conventional embedded cluster method while preserving its benefits in the simulation of metal oxides. Consequently, the LSEC method can provide efficient and accurate simulations of metal oxides and is anticipated to serve as a viable alternative for the simulation of metal oxides, in addition to the prevailing periodic DFT methods.
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