  Thermoelectric properties in topological insulator Bi2Se3 are explored with
multifaceted strategies, i.e., hybrid functional with strain and artificial
intelligence methodology. The assessment with the experimental band gap values
recognises the limitations of conventional functional and the effectiveness of
screened hybrid functionals. A thorough investigation into the impact of
biaxial and uniaxial strain on thermoelectric parameters uncovers distinctive
behaviours in n-type and p-type Bi2Se3 , providing insights into optimal strain
conditions for improved performance. Furthermore, the studies on the role of
topologically non-trivial surface states (TNSS) in thermoelectric properties
reveal that TNSS significantly dominate electronic transport. Dual scattering
time approximation elucidates the segregation of thermoelectric transport
contributions from bulk and surface states, highlighting the importance of
controlling the relaxation time ratio for enhanced thermoelectric performance.
Additionally, the prediction of thermoelectric properties using Random Forest
and Neural Networks models showcase impressive agreement with density
functional theory predictions across varying temperatures, offering a powerful
tool for understanding complex temperature-dependent trends in thermoelectric
properties. In summary, this interdisciplinary study presents a unique approach
to advancing the understanding and optimization of thermoelectric properties in
Bi2Se3 . It provides a comprehensive framework for tailoring material behaviour
for diverse thermoelectric applications.
