Hydrogen diffusivity in sodium aluminosilicate glasses

Welter, T.; Marzok, Ulrich; Deubener, Joachim; Reinsch, Stefan; Müller, Ralf

doi:10.1016/j.jnoncrysol.2019.119502

Cited by 6 publications

(11 citation statements)

References 34 publications

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“…The error bars in part (c) represent the average standard deviation from the GPR models. Also given in the figures are experimental density values for NAS glasses with ∼0 (filled blue circle), 87 ∼0.05 (filled red rectangle), 88 ∼0.1 (filled green triangle), 88,89 and ∼0.2 (filled purple cross) 88 Al 2 O 3 from experiments that have not been included in the original database used for model training and testing.…”

Section: Resultsmentioning

confidence: 99%

Data‐driven prediction of room‐temperature density for multicomponent silicate‐based glasses

Gong

Olivetti

2023

J Am Ceram Soc.

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Density is one of the most commonly measured or estimated material properties, especially for glasses and melts that are of significant interest to many fields, including metallurgy, geology, materials science, and sustainable cements. Here, three types of machine learning models (i.e., random forest [RF], artificial neural network [ANN], and Gaussian process regression [GPR]) have been developed to predict the room‐temperature density of glasses in the compositional space of CaO–MgO–Al2O3–SiO2–TiO2–FeO–Fe2O3–Na2O–K2O–MnO (CMASTFNKM), based on ∼2100 data points mined from ∼140 literature studies. The results show that the RF, ANN, and GPR models give accurate predictions of glass density with R2 values, root mean square error (RMSE), and mean absolute percentage error (MAPE) of ∼0.95–0.97, ∼0.03–0.04 g/cm3 and ∼0.63%–0.83%, respectively, for the 15% testing set, which are more accurate compared with empirical density models based on ionic packing ratio (with R2 values, RMSE, and MAPE of ∼0.28–0.91, ∼0.05–0.15 g/cm3, and ∼1.40%–4.61%, respectively). Furthermore, glass density is shown to be a reliable reactivity indicator for a range of CaO–Al2O3–SiO2 (CAS) and volcanic glasses due to its strong correlation (R2 values above ∼0.90) with the average metal–oxygen dissociation energy (a structural descriptor) of these glasses. Analysis of the predicted density–composition relationships from these models (for selected compositional subspaces) suggests that the single‐layer ANN and GPR models exhibit a certain level of transferability (i.e., ability to extrapolate to compositional spaces not [or less] covered in the database) and capture some known features, including the mixed alkaline earth (or alkali) effects.

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Section: Resultsmentioning

confidence: 99%

Data‐driven prediction of room‐temperature density for multicomponent silicate‐based glasses

Gong

Olivetti

2023

J Am Ceram Soc.

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“…The surface area of the sieved powder fraction was not studied, as preliminary tests showed that the influence of the grain shape and size distribution within the sieved 100-125 µm fraction on diffusivity and solubility experiments is negligible. In addition, eight sodium aluminosilicate glasses of a previous study were used [8]. The composition of these glasses (reports on the analyses in [8]) ranged from ~50-90 mol% SiO 2 (all with Na 2 O/Al 2 O 3 = 1), including compositions close to the stoichiometric tectosilicates Na 2 O⋅Al 2 O 3 ⋅2SiO 2 (nepheline), Na 2 O⋅Al 2 O 3 ⋅4SiO 2 (jadeite) and Na 2 O⋅Al 2 O 3 ⋅6SiO 2 (albite).…”

Section: Glass Preparationmentioning

confidence: 99%

“…In addition, eight sodium aluminosilicate glasses of a previous study were used [8]. The composition of these glasses (reports on the analyses in [8]) ranged from ~50-90 mol% SiO 2 (all with Na 2 O/Al 2 O 3 = 1), including compositions close to the stoichiometric tectosilicates Na 2 O⋅Al 2 O 3 ⋅2SiO 2 (nepheline), Na 2 O⋅Al 2 O 3 ⋅4SiO 2 (jadeite) and Na 2 O⋅Al 2 O 3 ⋅6SiO 2 (albite). Furthermore, a silica glass from the same study was also examined as a reference material.…”

Section: Glass Preparationmentioning

confidence: 99%

“…In particular, eucryptite, spodumene and cordierite glasses are studied, since these compositions have a relatively high degree of substitution of silicon by aluminium (in eucryptite glass, nominally every second silicon tetrahedron is replaced by an aluminium tetrahedron) and therefore the lowest hydrogen gas permeation can be expected. To extend the spectrum of aluminosilicate glasses with tectosilicate composition, data from earlier measurements [8] for albite (Na 2 O⋅Al 2 O 3 ⋅6SiO 2 ), jadeite (Na 2 O⋅Al 2 O 3 ⋅4SiO 2 ) and nepheline (Na 2 O⋅Al 2 O 3 ⋅2SiO 2 ) glasses are added. To illustrate the outstanding barrier effect of a thin layer of these tectosilicate glasses (glass liner), the effective permeation through a pressurised hydrogen tank with glass lining is calculated.…”

Section: Introductionmentioning

confidence: 99%

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Hydrogen Permeability of Tectosilicate Glasses for Tank Barrier Liners

et al. 2023

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The permeation of hydrogen gas was studied in meta-aluminous (tectosilicate) glass powders of Li2O×Al2O3×SiO2 (LAS), Na2O×Al2O3×SiO2 (NAS) and MgO×Al2O3×SiO2 (MAS) systems by pressure loading and vacuum extraction in the temperatures range 210–310 °C. With this method, both the solubility S and the diffusivity D were determined, while the permeability was given by the product SD. For all glasses, S was found to decrease with temperature, while D increased. Since the activation energy of diffusion of H2 molecules exceeded that of dissolution, permeation increased slightly with temperature. When extrapolated to standard conditions (25 °C), the permeability of tectosilicate glasses was found to be only 10-22–10-24 mol H2 (m s Pa)-1, which is 8–10 magnitudes lower than most polymers. Thin glass liners of these compositions are expected to be the most effective barrier for tanks of pressurised hydrogen.

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“…The underlying principles in the correlations between glass composition, accessible free volume and hydrogen permeation are still unclear. Only recently, a first attempt limited to hydrogen diffusivity was made by drawing a distinction between free volume reductions in modified and in fully polymerized networks (Welter et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Hydrogen Permeation Through Glass

et al. 2020

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Physical storage of gaseous hydrogen under high-pressure in glassy micro-containers such as spheres and capillaries is a promising concept for enhancing safety and the volumetric capacity of mobile hydrogen storage systems. As very low permeation through the container wall is required for storage of compressed hydrogen, development of glasses of minimal hydrogen permeability is needed. For this purpose, one has to understand better the dependence of hydrogen permeability on glass structure. The paper points out that minimizing the accessible free volume is a sound strategy to minimize hydrogen permeability. Based on previously measured and comprehensive literature data, it is shown that permeation is independently controlled by ionic porosity and network modifier content. Thus, ionic porosity in modified and fully polymerized networks can be decreased equally to the lowest hydrogen permeability among the glasses under study. Applying this concept, a drop of up to 30,000 with respect to the permeation of hydrogen molecules through silica glass is attainable.

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Hydrogen diffusivity in sodium aluminosilicate glasses

Cited by 6 publications

References 34 publications

Data‐driven prediction of room‐temperature density for multicomponent silicate‐based glasses

Data‐driven prediction of room‐temperature density for multicomponent silicate‐based glasses

Hydrogen Permeability of Tectosilicate Glasses for Tank Barrier Liners

Hydrogen Permeation Through Glass

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