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Ensuring the long-term chemical durability of glasses is critical for nuclear waste immobilization operations. Durable glasses usually undergo qualification for disposal based on their response to standardized tests such as the product consistency test or the vapor hydration test (VHT). The VHT uses elevated temperature and water vapor to accelerate glass alteration and the formation of secondary phases. Understanding the relationship between glass composition and VHT response is of fundamental and practical interest. However, this relationship is complex, non-linear, and sometimes fairly variable, posing challenges in identifying the distinct effect of individual oxides on VHT response. Here, we leverage a dataset comprising 654 Hanford low-activity waste (LAW) glasses across a wide compositional envelope and employ various machine learning techniques to explore this relationship. We find that Gaussian process regression (GPR), a nonparametric regression method, yields the highest predictive accuracy. By utilizing the trained model, we discern the influence of each oxide on the glasses’ VHT response. Moreover, we discuss the trade-off between underfitting and overfitting for extrapolating the material performance in the context of sparse and heterogeneous datasets.

Radioactive waste immobilization is a means to limit the release of radionuclides from various waste streams into the environment over a timescale of hundreds to many thousands of years. Incorporation of radionuclide-containing wastes into borosilicate glass during vitrification is one potential route to accomplish such immobilization. To facilitate comparisons and assessments of reproducibility across experiments and laboratories, a six-component borosilicate glass (Si, B, Na, Al, Ca, Zr) known as the International Simple Glass (ISG) was developed by international consensus as a compromise between simplicity and similarity to waste glasses. Focusing on a single glass composition with a multi-pronged approach utilizing state-of-the-art, multi-scale experimental and theoretical tools provides a common database that can be used to assess relative importance of mechanisms and models. Here we present physical property data (both published and previously unpublished) on a single batch of ISG, which was cast into individual ingots that were distributed to the collaborators. Properties from the atomic scale to the macroscale, including composition and elemental impurities, phase purity, density, thermal properties, mechanical properties, optical and vibrational properties, and the results of molecular dynamics simulations are presented. In addition, information on the surface composition and morphology after polishing is included. Although the existing literature on the alteration of ISG is not extensively reviewed here, the results of well-controlled static alteration experiments are presented here as a point of reference for other performance investigations.