  This study focuses on amorphous boron nitride ($\rm \alpha$-BN) as a novel
diffusion barrier for advanced semiconductor technology, particularly
addressing the critical challenge of copper diffusion in back-end-of-logic
(BEOL) interconnects. Owing to its ultralow dielectric constant and robust
barrier properties, $\rm \alpha$-BN is examined as an alternative to
conventional low-k dielectrics. The investigation primarily employs theoretical
modeling, using a Gaussian Approximation Potential, to simulate and understand
the atomic-level interactions and barrier mechanisms of $\rm \alpha$-BN. This
machine learning-based approach allows for realistic simulations of its
amorphous structure, enabling the exploration of the impact of different film
morphologies on barrier efficacy. Complementing the theoretical study,
experimental analyses are conducted on Plasma-Enhanced Chemical Vapor
Deposition (PECVD) grown $\rm \alpha$-BN films, evaluating their effectiveness
in preventing copper diffusion in silicon-based substrates. The results from
both the theoretical and experimental investigations highlight the potential of
$\rm \alpha$-BN as a highly effective diffusion barrier, suitable for
integration in nanoelectronics. This research not only proposes $\rm \alpha$-BN
as a promising candidate for BEOL interconnects but also demonstrates the
synergy of advanced computational models and experimental methods in material
innovation for semiconductor applications.
