Neutron diffraction and Raman studies of the incorporation of sulfate in silicate glasses

The oxidation state, coordination and local environment of sulphur in alkali silicate (R2O-SiO2; R= Na, Li) and alkali-alkaline earth silicate (Na2O-MO-SiO2; M= Ca, Ba) glasses have been investigated using neutron diffraction and Raman spectroscopy. With analyses of both the individual total neutron correlation functions, and of suitable doped-undoped differences, the S-O bonds and (O-O)S correlations were clearly isolated from the other overlapping correlations due to Si-O and (O-O)Si distances in the SiO4 tetrahedra, and the modifier-oxygen (R-O and M-O) distances. Clear evidence was obtained that the sulphur is present as SO4 2- groups, confirmed by the observation in the Raman spectra of the symmetric S-O stretch mode of SO4 2- groups. The modifier-oxygen bond length distributions were deconvoluted from the neutron correlation functions by fitting. The Na-O and Li-O bond length distributions were clearly asymmetric, whereas no evidence was obtained for asymmetry of the Ca-O and Ba-O distributions. A consideration of the bonding shows that the oxygen atoms in the SO4 2- groups do not participate in the silicate network, and as such constitute a third type of oxygen, ‘non-network oxygen’, in addition to the bridging and non-bridging oxygens that are bonded to silicon atoms. Thus each individual sulphate group is surrounded by a shell of modifier, and is not connected directly to the silicate network. The addition of SO3 to the glass leads to a conversion of oxygen atoms within the silicate network from non-bridging to bridging, so that there is a repolymerisation of the silicate network. There is evidence that SO3 doping leads to changes in the form of the distribution of Na-O bond lengths, with a reduction in the fitted short bond coordination number, and an increase in the fitted long bond coordination number, and this is consistent with a repolymerisation of the silicate network. In contrast, there is no evidence that SO3 doping leads to a change in the distribution of Li-O bond lengths, with a total Li-O coordination number consistently in excess of four

Viscosity and viscosity anomalies of model silicates and magmas: a numerical investigation

We present results for transport properties (diffusion and viscosity) using computer simulations. Focus is made on a densified binary sodium disilicate 2SiO$_2$-Na$_2$O (NS2) liquid and on multicomponent magmatic liquids (MORB, basalt). In the NS2 liquid, results show that a certain number of anomalies appear when the system is densified: the usual diffusivity maxima/minima is found for the network-forming ions (Si,O) whereas the sodium atom displays three distinct r\'egimes for diffusion. Some of these features can be correlated with the obtained viscosity anomaly under pressure, the latter being be fairly well reproduced from the simulated diffusion constant. In model magmas (MORB liquid), we find a plateau followed by a continuous increase of the viscosity with pressure. Finally, having computed both diffusion and viscosity independently, we can discuss the validity of the Eyring equation for viscosity which relates diffusion and viscosity. It is shown that it can be considered as valid in melts with a high viscosity. On the overall, these results highlight the difficulty of establishing a firm relationship between dynamics, structure and thermodynamics in complex liquids.Comment: 13 pages, 8 figure

Correlation between floppy to rigid transitions and non-Arrhenius conductivity in glasses

Non-Arrhenius behaviour and fast increase of the ionic conductivity is observed for a number of potassium silicate glasses $(1-x)SiO_2-xK_2O$ with potassium oxide concentration larger than a certain value $x=x_c=0.14$. Recovering of Arrhenius behaviour is provided by the annealing that enhances densification. Conductivity furthermore obeys a percolation law with the same critical concentration $x_c$. These various results are the manifestation of the floppy or rigid nature of the network and can be analyzed with constraint theory. They underscore the key role played by network rigidity for the understanding of conduction and saturation effects in glassy electrolytes.Comment: 4 pages, 4 EPS figure

Predicting the dissolution kinetics of silicate glasses using machine learning

Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, thanks to its inherent ability to handle non-linear data. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties

Electronic redistribution around oxygen atoms in silicate melts by ab initio molecular dynamics simulation

The structure around oxygen atoms of four silicate liquids (silica, rhyolite, a model basalt and enstatite) is evaluated by ab initio molecular dynamics simulation. Thanks to the use of maximally localized Wannier orbitals to represent the electronic ground state of the simulated system, one is able to quantify the redistribution of electronic density around oxygen atoms as a function of the cationic environment and melt composition. It is shown that the structure of the melt in the immediate vicinity of the oxygen atoms modulates the distribution of the Wannier orbitals associated with oxygen atoms. In particular the evaluation of the distances between the oxygen-core and the orbital Wannier centers and their evolution with the nature of the cation indicates that the Al-O bond in silicate melts is certainly less covalent than the Si-O bond while for the series Mg-O, Ca-O, Na-O and K-O the covalent character of the M-O bond diminishes rapidly to the benefit of the ionic character. Furthermore it is found that the distribution of the oxygen dipole moment coming from the electronic polarization is only weakly dependent on the melt composition, a finding which could explain why some empirical force fields can exhibit a high degree of transferability with melt composition.Comment: 27 pages, 7 figures. To be published in Journal of Non-Crystalline Solid

Structural models of random packing of spheres extended to bricks: Simulation of the nanoporous calcium silicate hydrates

Structure simulation algorithms of random packing of spheres and bricks have been developed. These algorithms were used to reproduce the nanostructure of the cementitious calcium silicate hydrates. The textural parameters (specific surface area, porosity, pore size, etc.) of a calcium silicate hydrates (C-S-H) sample, the main binding phase of hydrated cements, have been derived from N2-physisorption experiments. At the same time, these parameters have been simulated by using a sphere-based structural model, where the spheres are randomly packed according to several hierarchical levels. The corresponding algorithm has been extended for managing cuboids instead of spheres. The C-S-H sample density is successfully predicted by considering the presence of water in pores defined by the sphere network within 10-nm-size globules and assuming a tobermorite-like skeleton. Simulations with bricks (321.4nm3) yield also textural parameters that are consistent with N2-physisorption data, but with a globule radius (22nm) twice as big as that obtained when using spheres.European Union MRTN-CT-2006-03586