Machine Learning Aided Design and Optimization of Thermal Metamaterials

Article Properties
  • Language
    English
  • Publication Date
    2024/03/28
  • Indian UGC (journal)
  • Refrences
    471
  • Changliang Zhu Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, P.R. China
  • Emmanuel Anuoluwa Bamidele Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, United States
  • Xiangying Shen Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, P.R. China
  • Guimei Zhu School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, P.R. China
  • Baowen Li Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, P.R. ChinaSchool of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, P.R. ChinaDepartment of Physics, Southern University of Science and Technology, Shenzhen 518055, P.R. ChinaShenzhen International Quantum Academy, Shenzhen 518048, P.R. ChinaPaul M. Rady Department of Mechanical Engineering and Department of Physics, University of Colorado, Boulder 80309, United States ORCID
Cite
Zhu, Changliang, et al. “Machine Learning Aided Design and Optimization of Thermal Metamaterials”. Chemical Reviews, vol. 124, no. 7, 2024, pp. 4258-31, https://doi.org/10.1021/acs.chemrev.3c00708.
Zhu, C., Bamidele, E. A., Shen, X., Zhu, G., & Li, B. (2024). Machine Learning Aided Design and Optimization of Thermal Metamaterials. Chemical Reviews, 124(7), 4258-4331. https://doi.org/10.1021/acs.chemrev.3c00708
Zhu, Changliang, Emmanuel Anuoluwa Bamidele, Xiangying Shen, Guimei Zhu, and Baowen Li. “Machine Learning Aided Design and Optimization of Thermal Metamaterials”. Chemical Reviews 124, no. 7 (2024): 4258-4331. https://doi.org/10.1021/acs.chemrev.3c00708.
Zhu C, Bamidele EA, Shen X, Zhu G, Li B. Machine Learning Aided Design and Optimization of Thermal Metamaterials. Chemical Reviews. 2024;124(7):4258-331.
Refrences
Title Journal Journal Categories Citations Publication Date
10.1016/B978-0-12-821986-7.00013-5 2021
10.1109/WACV.2017.58 2017
10.1007/978-0-387-30440-3_243 2009
10.1007/0-387-27705-6_6 2006
Handbook of Materials Modeling: Methods: Theory and Modeling 2018