Project Se(L)ect(i)vity (PTDC/EQU-EQU/6193/2020)

Mineral extraction from seawater brines has emerged as a viable solution to reduce Europe's reliance on imported Critical Raw Materials (CRM). However, the economic viability of this approach hinges on the local demand for sodium chloride, the primary product of such extraction processes. This study investigates the potential of residual brines, commonly known as "bitterns," generated during solar sea-salt extraction in traditional saltworks, as an alternative source of minerals. The Mediterranean region, encompassing South-European, North-African, Near East coasts, and parts of the Atlantic regions, is particularly conducive to exploring this prospect due to its extensive solar sea salt industry. Saltworks in the region, adopting various operational strategies based on feed quality or local climate conditions, produce different types of bitterns, each holding a latent resource potential that has remained largely unexplored. Within the framework of the EU-funded SEArcularMINE project, it was conducted an extensive analytical campaign to characterize bitterns collected from a diverse saltworks network. The analysis revealed the presence of sodium, potassium, magnesium, chloride, sulfate, and bromide in concentrations ranging from g/kg, while boron, calcium, lithium, rubidium, and strontium were found in the mg/kg range. Additionally, trace elements (TEs) such as cobalt, cesium, gallium, and germanium were detected at concentrations in the order of μg/kg. Detailed results on the composition of bitterns are presented, emphasizing the distinct characteristics observed at different sites. The estimated potential for mineral recovery from these bitterns is approximately 190 €/m3, considering the production capacity of about 9 Mm3 per year in the Mediterranean area. This finding underscores the significant contribution that mineral recovery from bitterns could make in securing access to CRMs for the European Union.

Properties such as particle orientation{,} flowability{,} packing{,} compaction{,} syringeability{,} suspension stability and dissolution are the most influenced by changes in the crystal habit and polymorphic form of a drug substance. The crystal habit of a drug substance (long-acting β2-adrenergic agonist (LABA)){,} as well as its purity and polymorphic stability{,} was studied after performing slurry tests with 1{,}2-dimethoxyethane : heptane solution at 50 °C. In these slurry tests{,} the product was kept suspended and undissolved{,} with agitation{,} for polymorphic conversion evaluation. Since no significant modifications were observed in the crystal shape and dimensions at 50 °C{,} a new slurry test was performed at a temperature above the melting point of the starting material (80 °C). In the latter test{,} it was possible to obtain crystals with increased dimensions by 480% compared with the starting material. Additionally{,} the desired polymorphic form (form I) was obtained as well as an acceptable purity of approximately 99%. These are promising results{,} not only for downstream purposes{,} but also concerning the bioavailability of the drug substance. This work shows that working at a temperature higher than the melting point of the compound seems to modify the crystal habit of the product.

Reactor hydrodynamics can play a significant role in antisolvent crystallizations. In this work, the impact of suspension height/clearance ratio (H/C) and power per volume (PV) on the particle size distribution (PSD) parameters Dv10, Dv50, and Dv90 of an active pharmaceutical ingredient (API) were evaluated. The API solution was added near the liquid surface of the antisolvent with a buret, at a rate of approximately 5 mL/min, between the impeller and the reactor’s wall. Statistical models were developed, and it was found that PSD parameters seem to be influenced by the H/C and PV. A relationship between the PSD parameters and the nucleation rate was also witnessed. Furthermore, different mathematical methodologies (indicator function and Monte Carlo simulations) were used to obtain a design space comprising the probability of success of having PSD parameters within specification. An operating region comprising the probability of success was estimated, which can aid in minimizing the risk of failure in antisolvent crystallization processes and consequently help reduce the financial losses caused by out-of-specification batches.

The scale-up of crystallization processes is a challenging step in production of active pharmaceutical ingredients (APIs). When moving from lab to industrial scale, the mixing conditions tend to modify due to the different geometry and agitation performance, which is particularly important in anti-solvent crystallizations where the size of the crystals depends on the mixing and incorporation of the anti-solvent in the solution. In this work, the results obtained in anti-solvent lab-scale crystallization experiments were used to develop multivariate statistical models predicting Particle Size Distribution (PSD) parameters (Dv10, Dv50 and Dv90) in function of predictors such as percentage of volume, power per volume and tip speed. Firstly, the collinearity among the predictors was assessed by Variance Inflation Factor (VIF) diagnosis. Subsequently, least squares method was employed to find correlations among the predictors and output variables. The optimization of the models was executed by testing quadratic, logarithmic and square root terms of the predictors and removing the least statistically significant regression coefficient. The quality of the fitting was evaluated in terms of adjusted R2 (R2adj). The modelled Dv10, Dv50 and Dv90 values presented a good fitting to the experimental data, with R2adj higher than 0.79, either when using power per volume or tip speed along the percentage of volume as predictors. Afterwards, the particle size distribution parameters of industrial scale production were predicted using the previously developed models. The deviations between predicted and experimental values were lower than 17%. This demonstrates that multivariate statistical models developed in lab-scale conditions can be successfully used to predict particle size distribution in industrial-size vessels.

Spacer-less RED stacks using membranes with integrated spacer profiles have been investigated during the last years to eliminate the spacer shadow effect. The presence of spacers partially blocks the membrane surface and creates a tortuous and thus longer path for ions in the channel, meaning higher ohmic resistance. Consequently, power outputs are reduced. Profiled membranes may solve this problem as they provide flow channels for the feed streams, while the relief formed on their surfaces keeps the membranes separated. Although the geometry and arrangement of so far used profiles led to lower ohmic resistance, it did not grant an efficient fluid mixing. Recently, so-called chevron profiles, with enhanced mixing, were proposed based on computational fluid dynamics (CFD) simulations. In the present study, the performance of such chevron-profiled membranes, prepared by thermal pressing, was experimentally validated in a reverse electrodialysis (RED) stack. According to the obtained experimental values of non-ohmic resistance and total pressure drop across the RED stack, the chevron-profiled membranes assure efficient fluid mixing at comparatively low hydraulic losses. The net power density obtained with chevron-profiled membranes was the highest obtained for the present stack design. It outperformed the alternative RED stack configurations investigated in this study, such as channels with optimized spacers and channels formed by pillar-profiled membranes. To allow for an even more straightforward and efficient RED stack assembling with chevron-profiled membranes, recommendations for a further simplified design, consisting of diagonal ridges that are assembled perpendicularly, are provided.