Michael Parzer
;
Alexander Riss
;
Fabian Garmroudi
;
Johannes de Boor
;
Takao Mori
(National Institute for Materials Science)
;
Ernst Bauer
説明:
(abstract)Linking the fundamental physics of band structure and scattering theory with macroscopic features such as measurable bulk thermoelectric transport properties is indispensable to a thorough understanding of transport phenomena and ensures more targeted and efficient experimental research. Here, we introduce SeeBand, a highly efficient and interactive fitting tool based on Boltzmann transport theory. A fully integrated user interface and visualization tool enable real-time comparison and connection between the electronic band structure (EBS) and microscopic transport properties. It allows simultaneous analysis of data for the Seebeck coefficient S, resistivity ρ and Hall coefficient RH to identify suitable EBS models and extract the underlying
microscopic material parameters and additional information from the model. Crucially, the EBS can be obtained by directly fitting the temperature-dependent properties of a single sample, which goes beyond previous approaches that look into doping dependencies. Finally, the combination of neural-network-assisted initial guesses and an efficient subsequent fitting routine allows for a rapid processing of big datasets, facilitating high-throughput analyses to identify underlying, yet undiscovered dependencies, thereby guiding material design.
権利情報:
キーワード: thermoelectric
刊行年月日: 2025-06-07
出版者: Springer Science and Business Media LLC
掲載誌:
研究助成金:
原稿種別: 出版者版 (Version of record)
MDR DOI:
公開URL: https://doi.org/10.1038/s41524-025-01645-y
関連資料:
その他の識別子:
連絡先:
更新時刻: 2025-11-10 16:30:45 +0900
MDRでの公開時刻: 2025-11-10 16:25:05 +0900
| ファイル名 | サイズ | |||
|---|---|---|---|---|
| ファイル名 |
npj Computational Materials---SeeBand A highly efficient, interactive tool for analyzing electronic transport data.pdf
(サムネイル)
application/pdf |
サイズ | 1.42MB | 詳細 |