Interaction between Mo and intrinsic or extrinsic defects of Mo doped LiNbO$_3$ from first-principles calculations

This project is a static academic research artifact (arXiv paper) rather than a software platform. It provides specific scientific insights into Mo-doped LiNbO3, a niche material used in holographic data storage. With zero stars and six forks (likely from the authors or immediate peers), it lacks any community momentum or software moat. Its value lies entirely in the specific data points regarding site preference and energy levels, which are reproducible by any computational materials scientist with access to DFT software like VASP or Quantum ESPRESSO. Frontier labs (OpenAI, Google) are focusing on general-purpose materials AI (like GNoME), which may eventually automate this type of specific study, but they are unlikely to compete directly in the niche of lithium niobate dopant optimization. The 'moat' is non-existent as it is public domain research; however, the findings remain relevant (low displacement) until a more advanced experimental or higher-fidelity simulation study supersedes them.