To main content

Effectiveness of Neural Networks for Research on Novel Thermoelectric Materials. A Proof of Concept.

Effectiveness of Neural Networks for Research on Novel Thermoelectric Materials. A Proof of Concept.

Category
Part of a book/report
Abstract
This paper describes the application of neural network approaches to the discovery of new materials exhibiting thermoelectric properties. Thermoelectricity is the ability of a material to convert energy from heat to electricity. At present, only few materials are known to have this property to a degree which is interesting for use in industrial applications like, for example, large-scale energy harvesting [3, 8]. We employ a standard neural network architecture with supervised learning on a training dataset representing materials and later predict the properties on a disjoint test set. At this proof of concept stage, both sets are synthetically generated with plausible values of the features. A substantial increase in performance is seen when utilising available physical knowledge in the machine learning model. The results show that this approach is feasible and ready for future tests with experimental laboratory data.
Language
English
Affiliation
  • SINTEF Digital / Mathematics and Cybernetics
  • University of Oslo
  • SINTEF Industry / Sustainable Energy Technology
Year
2019
Published in
Communications in Computer and Information Science
ISSN
1865-0929
Publisher
Springer
Book
Nordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019
Booklet
1056
ISBN
978-3-030-35664-4
Page(s)
69 - 77