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Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework

  • Published:2020-06-07 Issue:21 Volume:127 Page:215104
  • ISSN:0021-8979
  • Container-title:Journal of Applied Physics
  • language:en
  • Short-container-title:Journal of Applied Physics

Author:

Santos D. P.12ORCID,Pelissari P. I. B. G. B.12,de Mello R. F.3,Pandolfelli V. C.1ORCID

Affiliation:

1. Department of Materials Engineering, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil

2. HiTemp Technological Solutions, São Carlos, São Paulo 13560-251, Brazil

3. Department of Computer Science, Institute of Mathematics and Computer Science, University of S ao Paulo, São Carlos, São Paulo 13566-590, Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Design of Automatic Production Algorithm for Ceramic Patterns Based on Machine Learning;2024 International Conference on Electrical Drives, Power Electronics & Engineering (EDPEE);2024-02-27

2. Theory-guided design of high-strength, high-melting point, ductile, low-density, single-phase BCC high entropy alloys;Acta Materialia;2022-09

3. Machine learning for materials design and discovery;Journal of Applied Physics;2021-02-21
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