Coupling of phase transition, anharmonicity, and thermal transport in CaSnF$_6$

This project is a scientific research artifact rather than a software product. Its defensibility is low (2/10) because it represents a specific application of existing methodologies (NEP and MD) to a specific material (CaSnF6). While the 5 forks indicate some initial interest within the academic community, the lack of stars and the niche focus on a single material make it a reference implementation for a paper rather than a reusable tool. Frontier labs like Google (DeepMind) or Microsoft Research are building general-purpose foundation models for materials (e.g., GNoME, MatterSim), which represent a high-level strategic risk to manual, material-specific studies. However, the specific domain expertise in thermal transport and anharmonicity provides a temporary niche. The displacement horizon is set to 1-2 years as automated high-throughput screening and more generalized machine-learning force fields (MLFF) likely render individual material studies like this less novel over time. It is a 'novel combination' because it applies cutting-edge neuroevolution potentials to a complex thermal transport problem, but it does not represent a new software category or a technical moat that others couldn't replicate with the same DFT data.