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Machine learning approaches for permittivity prediction and rational design of microwave dielectric ceramics

  • Published:2021-11 Issue:6 Volume:7 Page:1284-1293
  • ISSN:2352-8478
  • Container-title:Journal of Materiomics
  • language:en
  • Short-container-title:Journal of Materiomics

Author:

Qin Jincheng,Liu Zhifu,Ma Mingsheng,Li Yongxiang

Funder

Shanghai Rising-Star Program

Special Project for Research and Development in Key areas of Guangdong Province

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Metals and Alloys,Surfaces, Coatings and Films,Electronic, Optical and Magnetic Materials

Reference57 articles.

1. Low-loss dielectric ceramic materials and their properties;Sebastian;Int Mater Rev,2015

2. Microwave-millimeterwave dielectric materials;Ohsato;Key Eng Mater,2004

3. Microwave dielectric ceramics for resonators and filters in mobile phone networks;Reaney;J Am Ceram Soc,2006

4. High permittivity and low loss microwave dielectrics suitable for 5G resonators and low temperature co-fired ceramic architecture;Zhou;J Mater Chem C,2017

5. Forsterite ceramics for millimeterwave dielectrics;Ohsato;J Electroceram,2006

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