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Page 14 of 21 Chen et al. Energy Mater. 2025, 5, 500120 https://dx.doi.org/10.20517/energymater.2024.311
[56]
Figure 6. (A) Workflow and (B) identified ZT of doped elements through the ML approach . (License Number 6015491243882).
The ML approach was used to understand the practical conditions involving coating, printing, and
synthesizing the TE materials, as a result of which the time required to carry out the experiment and recover
the material costs was lowered. BiSbTe is a well-known composition in TE applications exhibiting ZT
greater than 1. However, predicting the suitable printing parameter through ML is an effective way to
optimize the ZT. Song et al. employed a GPR-based ML model to predict the thermoelectric properties as a
[61]
function of ink formulation and printing parameters in 3D printing . Initially, the data was collected
through experiment results to make ML algorithm. Considering the TE particle loadings and X-gum
