TID bias dependence

This repository provides a lightweight, phenomenological modeling layer for interpreting radiation-induced failure modes in electronic materials and devices, including Single-Event Effects (SEE), Total Ionizing Dose (TID), and Displacement Damage Dose (DDD). The core concept introduced is an anchoring yield, a bounded parameter that represents the fraction of radiation-induced excitations that become persistent material or electronic state changes (e.g., trapped charge, stable defects, metastable configurations), as opposed to relaxing transiently without lasting impact. This persistence-focused layer operates on top of standard radiation physics inputs (dose rate, flux, LET, NIEL proxies) and does not modify established transport, QED, or materials models. The framework is motivated by the observation—well known in radiation-hardness testing—that energy deposition alone does not predict damage: most deposited energy does not result in long-term degradation, while failure often exhibits sharp thresholds, bias dependence, temperature sensitivity, and particle-type selectivity. The anchoring-yield formalism provides a unified way to parameterize these effects across SEE, TID, and DDD regimes using a common persistence gate. The software is intended as: A review-safe modeling aid for accelerator-based materials and electronics testing A conceptual bridge between radiation inputs and observed failure thresholds A fittable layer that can be calibrated directly against experimental data While the interpretation is inspired by the General Relativity–Clock Scalar (GR-CS) framework—specifically the distinction between transient (null-like) excitations and persistent, time-anchored states—the implementation is deliberately phenomenological and can be evaluated, fitted, and used independently of that interpretation. This package is released under the MIT License to enable unrestricted academic, governmental, and industrial use, including internal evaluation, modification, and integration into existing radiation-effects workflows.