  Background: Understanding the nuclear reactions between light charged nuclei
at sub-coulomb energy region holds significant importance in several
astrophysical processes. Determination of the precise reaction cross-section
within the astrophysically important Gamow range is difficult because of
electron screening. Various polynomial fits, R-Matrix and Indirect Trojan horse
method estimate much higher electron screening energies as compared to the
adiabatic limit. Purpose: Obtain the bare astrophysical S-factor of 6
Li(p,{\alpha})3 He using Multi-Layer Perceptron based Artificial Neural Network
based analysis and extract the electron screening energies. Methods:
Experimental S-factor of 6 Li(p,{\alpha})3 He, available in literature, are
reanalyzed using the Multi-LayerPerceptron based Artificial Neural Network
based algorithm to obtain the energy dependent astrophysical S-factor. Bare
astrophysical S-factor is also calculated using the same Feed-forward
Artificial Neural Network from the data range above 60 keV where the electron
screening effect is expected to be negligible. Electron screening potential is
then obtained by taking the ratio of total shielded S-factor with the bare
S-factor. Results and Conclusions: The electron screening potential obtained
from the Present work through the Artificial Neural network based algorithm is
found to be 220 eV. The extracted electron screening potential through the
present analysis indicates that the Artificial Neural Network might be an
alternative tools for estimation the electron screening potential involving
light nuclei.
