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Figure 8. (A) Workflow of the ML-assisted extrusion printing of thermoelectric inks, including the four input variables listed in box 1 and
three out properties of interests in box 4, (B) ZT of BiSbTe using the optimum condition identified through this ML model and reported
values. Reproduced from Ref. [61] with permission from the Royal Society of Chemistry. (License under Creative Commons Attribution
3.0 Unported License).

within 1 s flash sintering time (optimized time). The sintering time was comparatively less than the previous
sintering time.

[64]
Hou et al. applied ML to optimize the PF of Al Fe Si by varying the composition of Al/Si . Experimentally
3
2
3
obtained data was used to train the ML model to predict unknown power factors. The commonly used
anisotropic squared-exponential (SE) covariance function in GPR was chosen to describe the covariance
between the feature variables of composition and temperature. Finally, the optimal ratio of 0.9 shows the
increase of PF up to 40% at 510 K compared with the original composition. Headley et al. applied the ML
approach to make a n-type Bi Te Se under laser powder bed fusion (LPBF) processing . The four steps
[63]
2
0.3
2.7
are followed to predict the optimized LPBF-built complex geometries using an iterative augmented strategy,
as shown in Figure 9. Initially, the new 13-line scan parameter (power and scan speed) combinations are
predicted. Then, this parameter value was used as input for melt pool characterization. The width and depth
of melt pool geometrical values were obtained, and these training datasets were used for ML. Again, 93-line
scan parameter combinations were used to predict the melt pool geometry with uncertainties. Then,
optimized parameter combinations were given to the LPBF-built to make Bi Te Se with three geometries:
2
0.3
2.7
the rectangular prism, hollow rectangle, and trapezoid. Integrating ML techniques helps to visualize and
quickly understand changing melt pool dimensions concerning varied laser parameters.
AI for TE materials synthesis
The first and only report during the writing of this article on the application of AI for TE materials synthesis