| Summary: | The intricate amorphous structure and elusive local environment of rare-earth (RE) doped laser glasses render existing physical or machine-learning models inadequate for guiding the design of next-generation laser glasses, thereby maintaining iterative experimentation as the primary method for development. Here, the microenvironment surrounding RE ions in a multicomponent laser glass is treated as a statistical ensemble derived from its neighboring glassy compounds (NGCs). The NGCs model employs statistical ensemble averaging over the NGCs to provide a rigorous mathematical description of the key local structural and luminescent behaviors of RE-doped laser glasses. Validation through molecular dynamics simulations and experimental data for quaternary germanate glass system demonstrates the model’s excellent predictive capabilities, allowing it to establish the composition–structure relationship and populate the composition–property space. Moreover, the model enables the creation of multi-luminescence property charts, facilitating the de novo design of chemically complex laser glasses for targeted applications by efficiently screening the compositions which simultaneously meet several performance constraints. This work offers a robust framework for studying the luminescent behaviors of glass and paves the way for new explorations in laser glass technology.
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