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Artificial neural network simulator for supercapacitor performance prediction

Farsi, H ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1016/j.commatsci.2006.08.024
  3. Publisher: 2007
  4. Abstract:
  5. Artificial neural network was used to calculate the performance of a model supercapacitor as signified by the power density, energy density and utilization to the synthetic, intrinsic and operating characteristics. A four-layer neural net having two hidden layers having 6 and 15 nodes was found to be well capable of simulating the capacitor performance with the convergence achieved often a relatively small number of epochs. As for the input parameters, crystal size, surface lattice length, exchange current density of the capacitor active material and the cell current employed while utilization, energy density and power density were the outputs. © 2006 Elsevier B.V. All rights reserved
  6. Keywords:
  7. Capacitors ; Charge density ; Computer simulation ; Crystal structure ; Current density ; Cell current ; Energy density ; Exchange current density ; Ragone plot ; Neural networks
  8. Source: Computational Materials Science ; Volume 39, Issue 3 , 2007 , Pages 678-683 ; 09270256 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0927025606002606