Machine Learning Model Predicting
Thermoelectric Properties of
BiTe-based materials ver.0.2a

This website provides a machine learning model to predict thermoelectric properties of BiTe-based materials (BiSbTe, BiTeSe). The purpose of this website is to demonstrate the excellence of the machine learning model we developed. Therefore, detailed information on the material synthesis process is omitted.
You can also find a thermoelectric power generation simulator on our web simulator.

Please follow the steps below to predict the material properties.

Step 1: Choose Material and Composition

The meaning of the composition (x) depends on type:

Scatter Plot: Experiments using SPS (Expt)
Plot 1: Machine Prediction (Pred 1)
Plot 2: Machine Prediction (Pred 2)
Show Options

Step 2: Check the Thermoelectric Properties

Regression/Interpolation Methods for Thermoelectric Properties

In the plot, the filled region means 95% CI (confidence interval) of the mean. However, because the synthesis is rarely repeated in this example, the CI has no significant meaning.

Thermoelectric Properties

Methods

Contacts

Powered by