Beyond Good and Evil: A Comparative Study of Computational Methods and Metrics for Amorphous Materials

Amorphous materials are critical to modern devices, from semiconductor dielectrics and quantum tunnel barriers to optical fibers and protective oxides. Far more disordered than their crystalline counterparts, these materials exhibit rich and complex structural behavior, yet remain classified by a single translational metric: "amorphicity." This approach conflates long-range periodicity with local configurational order, obscuring the process-structure-property relationships that govern device performance. We present a trajectory-aware framework that tracks structural evolution through melt-quench molecular dynamics, reactive and ab initio simulations, machine-learned potentials, and deposition models. By separating periodicity from configurational order, we reveal that systems of comparable "amorphicity" can occupy distinct, process-dependent configurations with markedly different electronic properties. This work aims to establish unified metrics for classifying amorphous materials beyond periodicity, provide quantitative guidance for process optimization, and bridge the gap between simulation and manufacturing for next-generation devices.