Developing stable, surfactant-free formulations for food, pharmaceutical, and cosmetic applications remains a challenge due to the high environmental impact and toxicity risks associated with synthetic surfactants. While solid particles offer an eco-friendly alternative for establishing kinetic stability in Pickering emulsions, the performance of natural, unmodified aluminosilicate clays remains highly variable and poorly optimized. This study aimed to solve this limitation by systematically mapping the stabilization performance of raw bentonite and kaolin using targeted mechanical milling and ionic-strength adjustments without relying on chemical surface modifications. The mineral matrices were characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and electron microscopy to link structural amorphization to interfacial performance. Oil-in-water formulations were prepared via high-shear homogenization by systematically adjusting clay content, oil volume fraction, and phase salinity, utilizing a central composite design and response surface methodology to model system stability. The experimental results demonstrated that mechanical processing yielded optimized particle-size distributions capable of organizing rigid interparticle networks at the oil–water interface. Rheological modeling confirmed solid-sphere behavior and thixotropy under optimal concentrations, proving that physical processing and electrolyte control are sufficient to engineer highly stable, green Pickering systems tailored for targeted industrial applications.

The structural and thermodynamic properties of minerals are strongly affected by cation site-ordering processes. We describe methods to determine the main interatomic interactions that drive the ordering process, which are based on parameterizing model Hamiltonians using empirical interatomic potentials and/or ab initio quantum mechanics methods. The methods are illustrated by a number of case study examples, including Al/Si ordering in aluminosilicates, Mg/Ca ordering in garnets, simultaneous Al/Si and Mg/Al ordering in pyroxenes, micas and amphiboles, and Mg/Al non-convergent ordering in spinel using only quantum mechanical methods.

Tube-in-tube experiments involving a time-dependent variation of temperature or a strong thermal gradient were conducted in order to decipher the transport and transfer of Al in a closed medium along with dilute water. Results show that the solubility and the transport of Al are controlled by the alkali availability. Starting from a mixture of kyanite + quartz + muscovite at the hot end of a thermal gradient, Al is transported toward the cold end in the form of a complex with an Al/K stoichiometry close to unity. Since more Al than alkali are released by the dissolution of muscovite, an Al-rich phase (kyanite) forms in the vicinity of the starting minerals undergoing dissolution, although Al is mobile in the system. Then, the variation of the solubility of the Al-K complex with temperature leads to the formation of muscovite (+quartz) at the cold end of the thermal gradient. A quantitative interpretation of the experimental results was carried out using data from the literature on Al speciation in dilute water. Extrapolation of the laboratory data to natural rocks suggests that the diffusion of Al is an efficient transport process under medium-grade, low- to medium-pressure conditions. Therefore, mass-transfer estimates based on mass-balance analyses postulating a fixed Al reference frame should be considered with caution. Also the high fluid to rock ratio calculated from the amount of aluminosilicates occurring in veins of medium-grade metapelites is questionable because such calculations neglect the importance of the transport of Al by diffusion.

This paper reviews recent applications of Monte Carlo methods for the study of cation ordering in minerals. We describe the program Ossia99, designed for the simulation of complex ordering processes and for use on parallel computers. A number of applications for the study of long-range and short-range order are described, including the use of the Monte Carlo methods to compute quantities measured in an NMR experiment. The method of thermodynamic integration for the determination of the free energy is described in some detail, and several applications of the method to determine the thermodynamics of disordered systems are outlined.