Drug solubility is one of the most significant physicochemical properties as it is related to drug design, formulation, quantification, recrystallization, and other processes, so understanding it is crucial for the pharmaceutical industry. In this context, this research presents the thermodynamic analysis of the solubility of sulfadiazine (SD) in cosolvent mixtures {acetonitrile + 1-propanol} at 9 temperatures (278.15 K–318.15 K), which is a widely used drug in veterinary therapy, and two solvents of high relevance in the pharmaceutical industry, respectively. The solubility of SD, in cosolvent mixtures {acetonitrile + 1-propanol} is an endothermic process where the maximum solubility was reached in pure acetonitrile at 318.15 K and the minimum in 1-propanol at 278.15 K. Although the solubility parameters of acetonitrile and propanol were similar, the addition of acetonitrile to the cosolvent mixture leads to a positive cosolvent effect on the solubility of DS. As for the thermodynamic functions of the solution, the process is strongly influenced by enthalpy, and according to the enthalpy–entropy compensation analysis, the process is enthalpy-driven in intermediate to rich mixtures in 1-propanol and entropy-driven in mixtures rich in acetonitrile.

The current challenges of the pharmaceutical industry regarding the environmental impact caused by its waste have led to the design and development of more efficient industrial processes. In this context, solubility studies are at the core of different processes, such as formulation, preformulation, synthesis, purification, recrystallization, quantification, and quality control. This research evaluates the solubility of sulfamerazine (SMR) in acetonitrile + 1-propanol cosolvent mixtures at nine temperature levels with UV/vis spectrophotometry using the vial-shake method. According to the analysis of the solid phase in equilibrium using differential scanning calorimetry, there were no polymorphic changes. The minimal solubility of SMR was reached in 1-propanol at 278.15 K, and the maximal solubility in acetonitrile at 313.15 K. In all cases, the process was endothermic and dependent on the cosolvent composition, and the solution enthalpy drove the solution process. The solubility data were well correlated with the van’t Hoff, Yalkowsky–Roseman–van’t Hoff, Apelblat, Buchowski–Ksiazczak λh, Yaws, NRTL, Wilson, and modified Wilson models, with the YR model being one of the most attractive because it presented an excellent prediction percentage from four sets of experimental data. The solution process of SMR in acetonitrile + 1-propanol cosolvent mixtures depends on the affinity of SMR for acetonitrile and temperature increase.

Parabens are substances used in the food, pharmaceutical and cosmetic industries. Recent studies have indicated that these substances have toxic potential, cause endocrine disruption and can easily bioaccumulate; therefore, their physicochemical properties are of industrial, biological and environmental interest. Due to their potential use in the development of more efficient and cleaner processes, the design of environmental recovery strategies and more reasonable designs for solubility in cosolvent mixtures, studies of thermodynamic analysis and mathematical modeling are of great interest. This research studies the solubility of propylparaben in acetonitrile + water cosolvent mixtures at nine temperatures by UV/Vis spectrophotometry, analyzing the solid phase by differential scanning calorimetry to evaluate possible polymorphic changes. The solubility of propylparaben is an endothermic process, where phase separation occurs at intermediate mixtures, reaching its minimum solubility in pure water at 278.15 K and the maximum solubility in pure acetonitrile at 315.15 K. The experimental data are well-correlated with the va not Hoff, Apelblat and Buchowski–Ksiazaczak models. The results revealed that possible microheterogeneity of the MeCN + W mixture can generate phase separation in intermediate mixtures, possibly due to the formation of solvates or hydrates.

Cyclic liquefaction is a phenomenon in which soil deposits formed by loose and saturated sands, lose their shear resistance due to dynamic loads, as earthquakes, sometimes causing the collapse of structures. This phenomenon is a hazard in different cities of the world, as is the case of Santiago de Cali (Colombia), a city that has large alluvial deposits due to its seven rivers. Currently, the liquefaction potential is evaluated by field tests that can be expensive and difficult to perform in densely urbanized areas. Due to this drawbacks, this paper proposes a simple and versatile methodology to evaluate the liquefaction potential in large areas based on the vulnerability index ($K_g$ ) proposed by Nakamura in 1997 (hereinafter Nakamura Methodology). This methodology consists of calculating the vulnerability index using the fundamental frequency ($F_g$ ) and amplification factor ($A_g$ ) determined using HVSR method. The $K_g$ index quantifies the probable damage in the soil produced by earthquakes, and for sand deposits, $K_g$ can be correlated with liquefaction potential. For this research, the liquefaction potential was evaluated using Nakamura methodology in 34 points of Santiago de Cali, within an approximate area of 12 km². The results were compared with those of SPT and CPT tests performed in the same area. The methodology showed a match of up to 82% compared to conventional methods. In conclusion, Nakamura methodology is a viable alternative for liquefaction hazard mapping of large areas and could be very useful in places where there are limited funds or the conditions for more robust testing are not available.