Influence of Geometrical Factors on Performance of Thermoelectric Material Using Numerical Methods

DEREBAŞI N. , Eltez M., Guldiken F., Sever A., Kallis K., Kilic H.

JOURNAL OF ELECTRONIC MATERIALS, vol.44, no.6, pp.2068-2073, 2015 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 44 Issue: 6
  • Publication Date: 2015
  • Doi Number: 10.1007/s11664-015-3657-0
  • Page Numbers: pp.2068-2073


Prediction of the performance of thermoelectric cooling material (figure of merit, ZT) was carried out by simulated results obtained from the finite element method (FEM) as a training dataset with an artificial neural network. A total of 87 input vectors for the ZT obtained from the four thermoelectric cooling (TEC) modules modeled using the FEM analysis were available in the training set to a back-propagation artificial neural network. An average correlation and maximum prediction error were found to be 100% and 0.01%, respectively, for the ZT after training. The standard deviation of the values was 0.05%. A set of test data, different from the training dataset was used to investigate the network performance. The average correlation and maximum prediction error were found to be 99.92% and 0.07%, respectively, for the tested TEC module. A thermoelectric module produced based on the numerical results was shown to be a promising device for use in cooling systems.