Modeling and Simulation of Defect-Induced Reliability Challenges in Modern Semiconductor Materials

State of the art semiconductor functioning needs permanent miniaturization as well as implementation of fresh materials that have created various reliability issues due to both inherent and extrinsic material flaws. Material defects of various kinds at atomic scale vacancy levels all the way to the grain boundaries influence the movement of carriers within the device as well as the switching characteristics and permanent stability of the device over time. This work is a full exploration of the defect effect on the advanced semiconductor material reliability by the use of modern simulation and modeling techniques. The article examines performance of density functional theory (DFT) and molecular dynamics (MD) and kinetic Monte Carlo (KMC) and technology computer-aided design (TCAD) simulations. In the paper, it is examined how machine learning (ML) prediction techniques and defect failure prevention mechanisms may be combined. Multiscale simulation frameworks are needed in reliability engineering based on findings with silicon (Si), gallium nitride (GaN) and two-dimensional (2D) analysis.

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