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Updated: Mar 27, 2026
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Author Spotlight: Advancements in High-Performance Thermoelectric Thin Films Through Radio Frequency Magnetron Sputtering
Published on: May 17, 2024
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Topological thermoelectrics: analytical framework, material aspects and machine learning.
Deep Mondal1, Supriya Ghosal2,3, Sujoy Datta4
1Department of Physics, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Summary
Topological quantum materials enhance thermoelectric devices by optimizing band geometry and carrier transport. This review unifies analytical, materials, and machine learning approaches for designing next-generation topological thermoelectrics.
Area of Science:
- Condensed Matter Physics
- Materials Science
- Quantum Mechanics
Background:
- Topological quantum materials offer novel mechanisms for thermoelectric (TE) energy conversion.
- Reshaping band geometry, carrier scattering, and heat transport are key opportunities in TE design.
- A unified perspective is needed to leverage these properties for advanced TE materials.
Purpose of the Study:
- To provide a comprehensive review of topological quantum materials for thermoelectric applications.
- To unify analytical, materials-based, and machine learning strategies for TE design.
- To outline design principles and computational pathways for next-generation topological thermoelectrics.
Main Methods:
- Development of an analytical framework using the Bernevig-Hughes-Zhang model to analyze anomalous Nernst response.
- Survey of material platforms including topological insulators, semimetals, and altermagnets.
- Review of machine learning strategies for topological thermoelectrics, including descriptor engineering and model development.
Main Results:
- Helical edge channels can function as energy filters, requiring particle-hole asymmetry for significant thermopower.
- Various material platforms hosting topological phenomena are identified for TE applications.
- Machine learning approaches show promise for accelerating the discovery and optimization of topological thermoelectrics.
Conclusions:
- Topological properties can be controllably exploited to enhance thermoelectric performance.
- A combination of analytical, materials, and data-driven approaches is crucial for advancing topological thermoelectrics.
- This review provides a roadmap for designing and discovering novel topological thermoelectric materials and devices.
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