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Neeway, James J. (ORCID:0000000170468408)

Publications and source records attributed to Neeway, James J. (ORCID:0000000170468408).

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗
DOE OSTI2026

Low Activity Waste Glass Optimization with Property Models from Machine Learning, Part 2: Experimental Validation and Active Learning

The United States Department of Energy is responsible for managing legacy nuclear waste stored in underground tanks at the Hanford Site. To treat the waste, it is planned as the current baseline to separately vitrify low-activity waste (LAW) and high-level waste fractions. Previously, machine learning (ML) based glass property models (e.g., chemical durability, viscosity, electrical conductivity and SO3 solubility) were developed with prediction uncertainties. A waste glass optimization approach was then established to enable the capability of using these ML models in LAW glass formulation. In this study, the previous ML models were first experimentally validated, and the results were incorporated back into the database to update the ML models. The updated models and formulations showed increased waste loading while reducing the failure rate, demonstrating improved predictive accuracy, reduced uncertainties, and the effectiveness of active learning in guiding high-dimensional, nonlinear LAW glass design. This represents the first experimental validation of ML based LAW glass formulation, with practical benefits such as higher waste loading, shorter mission duration, and lower operational risk.

Lu, Xiaonan (ORCID:0000000179708148)↗
DOE OSTI2026

A Kinetic Model of the Long-Term Corrosion of Glass-Ceramic Materials

Multiphase waste forms show promise for increased waste loading and for the ability to dispose of contaminated solid and particulate waste through direct densification. However, achieving predictive capability for long-term durability of multiphase waste forms, and thus assessing their possible deployment, requires expanding the current, limited knowledge base. Here, we describe the development of a corrosion model of a two-phase waste form consisting of crystals of known volume fraction embedded in a glass matrix. This model accounts for the dissolution of both the crystalline and glass phases as well as the hydration of the glass phase through an ion exchange reaction. Because of the large difference in solubility between the two phases, the reactive surface of the crystalline phase is a function of the extent of dissolution of the glass phase in this model. Model parameterization was performed using corrosion data, such as from single-pass flow-through tests, for the individual phases. The parameterized corrosion model was evaluated against static dissolution test data for a glass-ceramic multiphase waste form. This evaluation demonstrated the model’s ability to reproduce the time-dependent release of key tracers of glass and crystalline phase dissolution. Hence, the development of a kinetic model provides a pathway for long-term durability predictions and thus the use of multiphase waste forms in nuclear cleanup missions.

Kerisit, Sebastien N.↗
DOE OSTI2025

The effectiveness of TRIS and ammonium buffers in glass dissolution studies: a comparative analysis

Abstract Selecting appropriate buffers is crucial for evaluating the chemical durability of glass under controlled conditions such as in the EPA 1313 test designed to measure elemental release as a function of pH. The efficacy of two alkali-metal free buffers, TRIS (NH 2 C(CH 2 OH) 3 ) and ammonium chloride—ammonia (NH 3 /NH 4 Cl), was investigated during EPA 1313 testing of a simulated Hanford low-activity waste borosilicate glass in the alkaline regime (pH 8.5–10.5) at varying temperatures (RT, 40 °C, and 60 °C). While both buffers maintained the desired pH at room temperature, and up to 40 °C, the effectiveness of TRIS decreased at elevated temperatures, particularly at pH 10.5. Although 11 B NMR showed evidence of TRIS-B complexation, its effect on the rate of elemental release was found to be negligible under the test conditions. With ammonium buffer, the release of alkali cations was slightly elevated when compared to the same conditions with TRIS at early time points.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The effect of metals on zeolite crystallization kinetics with relevance to nuclear waste glass corrosion

Abstract Geologic disposal of vitrified radioactive material is planned in several countries, but there are remaining uncertainties related to the long-term stability of glass exposed to groundwater. Specifically, the crystallization of aluminosilicate zeolite minerals can accelerate the rate at which glass corrodes and radioactive material is released into the biosphere. In this study, we identify elemental species that may accelerate or suppress zeolite formation using a protocol to examine their effects on zeolite synthesis over a three-day duration. Our results are consistent with previous works demonstrating glass corrosion acceleration in the presence of calcium. Furthermore, we identify two elements—tin and lithium—as inhibitors of zeolite P2 (gismondine, or GIS type) nucleation and, thus, promising components for promoting the long-term durability of glass waste forms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Forty years of durability assessment of nuclear waste glass by standard methods

Abstract Standard methods to assess the durability of vitrified radioactive waste were first developed in the 1980’s and, over the last 40 years, have evolved to yield a range of responses depending on experimental conditions and glass composition. Mechanistic understanding of glass dissolution has progressed in parallel, enhancing our interpretation of the data acquired. With the implementation of subsurface disposal for vitrified radioactive waste drawing closer, it is timely to review the available standard methodologies and reflect upon their relative advantages, limitations, and how the data obtained can be interpreted to support the post-closure safety case for radioactive waste disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Applying laboratory methods for durability assessment of vitrified material to archaeological samples

Abstract Laboratory testing used to assess the long-term chemical durability of nuclear waste forms may not be applicable to disposal because the accelerated conditions may not represent disposal conditions. To address this, we examine the corrosion of vitrified archeological materials excavated from the near surface of a ~1500-year old Iron Age Swedish hillfort, Broborg, as an analog for the disposal of vitrified nuclear waste. We compare characterized site samples with corrosion characteristics generated by standard laboratory durability test methods including the product consistency test (PCT), the vapor hydration test (VHT), and the EPA Method 1313 test. Results show that the surficial layer of the Broborg samples resulting from VHT displays some similarities to the morphology of the surficial layer formed over longer timescales in the environment. This work provides improved understanding of long-term glass corrosion behavior in terms of the thickness, morphology, and chemistry of the surficial features that are formed.

36 MATERIALS SCIENCE↗