ServiceNow Research Introduces EnterpriseOps-Gym: A High-Fidelity Benchmark Designed to Evaluate Agentic Planning in Realistic Enterprise Settings

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In conclusion, we built a complete workflow for exploring and analyzing materials structures using pymatgen. We demonstrated how to construct and manipulate crystal structures, analyze symmetry and local environments, and perform common computational materials science tasks, such as supercell generation, surface slab preparation, and diffraction simulation. We also showed how to evaluate thermodynamic stability through a simple phase diagram and handle disordered structures by generating ordered approximations. In addition, we exported structures to standard CIF files, summarized key properties in tabular form, and optionally connected to the Materials Project database to retrieve real materials data. Through these steps, we saw how pymatgen provides an integrated framework that allows us to move from structure generation to analysis and data integration within a single Python environment.

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