Data-driven analysis of electron relaxation times in PbTe-type thermoelectric materials
Data mining from published papers can generate large experimental datasets that have been overlooked in computational materials informatics. We developed an open web system Starrydata2 to accelerate a comprehensive digitization of data of materials from as-reported plot images in published papers, w...
Main Authors: | , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2019-12-01
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Series: | Science and Technology of Advanced Materials |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/14686996.2019.1603885 |
Summary: | Data mining from published papers can generate large experimental datasets that have been overlooked in computational materials informatics. We developed an open web system Starrydata2 to accelerate a comprehensive digitization of data of materials from as-reported plot images in published papers, without sample selection based on performance. By plotting results obtained from our dataset on experimental thermoelectric properties of 434 samples of rock-salt-type (PbTe-type) thermoelectric materials, we revealed differences in electronic structure of parent compounds PbTe, PbSe, PbS, and SnTe from just experimental data. We observed that the calculated Seebeck coefficients were fairly consistent with experimental data for n-type PbTe but not for p-type PbTe, indicating possible modifications in its valence-band electronic structure. We evaluated the electron relaxation time τel from 207 reported samples of n-type PbTe by combining calculations and experimental data. We found that τel is not a constant but varies by at least two orders of magnitude. Achieving long τel was suggested to be critical in increasing the thermoelectric figure of merit ZT. |
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ISSN: | 1468-6996 1878-5514 |