2:45 PM - 3:00 PM
[1Ip04] Data-scientific exploration of optimized microscopic structure of carbon nanotube films with high thermoelectric power factor
Carbon nanotubes (CNTs) are potential candidates for flexible thermoelectric (TE) materials because of their flexibility and good thermoelectric property. The TE performance of CNT films highly depends on both semiconductor purity and CNT alignment. In addition, the CNT films seem to have a trade-off relationship between the electrical conductivity and the Seebeck coefficient. We explored the optimal semiconductor purity and structure using a Thermoelectric Random Stick Network (TE-RSN) method and Nondominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ). As a result of optimization up to 2,000 generations, an averaged electrical conductivity increased from 100 S/m to 300 S/m and an averaged Seebeck coefficient increased from 60 µV/K to 120 µV/K compared to the initial generation. Thus, we succeeded in resolving the trade-off relationship between the electrical conductivity and the Seebeck coefficient. In the presentation, we will explain the details.
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