Accelerating Density Functional Calculation of Adatom Adsorption on Graphene via Machine Learning
Abstract
:1. Introduction
2. Modeling and Dataset
2.1. First Principles Calculations
2.2. Feature Engineering
2.3. Machine Learner Design
3. Results and Discussion
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Interface | (Å) | (Å) | (eV) | (eV) |
---|---|---|---|---|
Graphene/Mg+Zn | 3.13 | 3.40 | 6.340 | −0.487 |
Graphene/Mg+Li | 3.04 | 3.42 | 6.377 | −0.628 |
Graphene/Mg+Ca | 3.27 | 2.82 | 6.379 | −0.977 |
Graphene/Mg+Al | 3.27 | 3.65 | 6.470 | −1.309 |
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Qu, N.; Chen, M.; Liao, M.; Cheng, Y.; Lai, Z.; Zhou, F.; Zhu, J.; Liu, Y.; Zhang, L. Accelerating Density Functional Calculation of Adatom Adsorption on Graphene via Machine Learning. Materials 2023, 16, 2633. https://doi.org/10.3390/ma16072633
Qu N, Chen M, Liao M, Cheng Y, Lai Z, Zhou F, Zhu J, Liu Y, Zhang L. Accelerating Density Functional Calculation of Adatom Adsorption on Graphene via Machine Learning. Materials. 2023; 16(7):2633. https://doi.org/10.3390/ma16072633
Chicago/Turabian StyleQu, Nan, Mo Chen, Mingqing Liao, Yuan Cheng, Zhonghong Lai, Fei Zhou, Jingchuan Zhu, Yong Liu, and Lin Zhang. 2023. "Accelerating Density Functional Calculation of Adatom Adsorption on Graphene via Machine Learning" Materials 16, no. 7: 2633. https://doi.org/10.3390/ma16072633