SeeBand: A highly efficient, interactive tool for analyzing electronic transport data

TL;DR

SeeBand is an interactive, efficient tool that links electronic band structure with transport properties, enabling real-time analysis and high-throughput material research based on Boltzmann transport theory.

Contribution

It introduces a novel fitting tool that directly extracts electronic band structure parameters from temperature-dependent transport data, surpassing previous doping-based methods.

Findings

Real-time comparison of band structure and transport data.

Rapid processing of large datasets for material analysis.

Identification of new dependencies guiding material design.

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 $\rho$ and Hall coefficient $R_\text{H}$ 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.