An experimental and theoretical study of the aggregate structure of calix[6]arenes in Langmuir films at the water/air interface

Brine-Oil Interfacial Tension Modeling: Assessment of Machine Learning Techniques Combined with Molecular Dynamics

The physical chemistry mechanisms behind the oil-brine interface phenomena are not yet fully clarified. The knowledge of the relation between brine composition and concentration for a given oil may lead to the ionic tuning of the injected solution on geochemical and enhanced oil recovery processes. Thus, it is worth examining the parameters influencing the interfacial properties. In this context, we have combined machine learning (ML) techniques with classical molecular dynamics simulations (MD) to predict oil/brine interfacial tensions (IFT) effectively and compared this process to a linear regression (LR) method. To diversify our data set, we have introduced a new atomistic crude oil model (medium) with 36 different types of hydrocarbon molecules. The MD simulations were performed for mono- and multicomponent (toluene, heptane, Heptol, light, and medium) oil systems interfaced with sulfate and chloride brines with varying cations (Na⁺, K⁺, Ca²⁺, and Mg²⁺) and salinity concentration. Thus, a consistent IFT data set was built for the ML training and LR fitting at room temperature and pressure conditions, over the feature space considering oil density, oil composition, salinity, and ionic concentrations. On the basis of gradient boosted (GB) algorithms, we have observed that the dominant quantities affecting the IFT are related to the oil attributes and the salinity concentration, and no specific ion dominates the IFT changes. When the obtained LR model was validated against MD and experimental data from the literature, the error varied up to 2% and 9%, respectively, showing a robust and consistent transferability. The combination of MD simulations and ML techniques may provide a fast and cost-effective IFT determination over multiple and complex fluid-fluid and fluid-solid interfaces.

The antibacterial activity of p-tert-butylcalix[6]arene and its effect on a membrane model: molecular dynamics and Langmuir film studies

The antibacterial activity of a calixarene derivative, p-tert-butylcalix[6]arene (Calix6), was assessed and was shown not to inhibit the growth of E. coli, S. aureus and B. subtilis bacteria. With the aim of gaining more insights into the absence of antibacterial activity of Calix6, the interaction of this derivative with DPPG, a bacterial cell membrane lipid, was studied. Langmuir monolayers were used as the model membrane. Pure DPPG and pure Calix6 monolayers, as well as binary DPPG:Calix6 mixtures were studied using surface pressure measurements, compressional modulus, Brewster angle and fluorescence microscopies, ellipsometry, polarization-modulation infrared reflection absorption spectroscopy and molecular dynamics simulations. Thermodynamic properties of the mixed monolayers were additionally calculated using thermodynamic parameters. The analysis of isotherms showed that Calix6 significantly affects the DPPG monolayers, modifying the isotherm profile and increasing the molecular area, in agreement with the molecular dynamics simulations. The presence of Calix6 in the mixed monolayers decreased the interfacial elasticity, indicating that calixarene disrupts the strong intermolecular interactions of DPPG hindering its organization into a compact arrangement. At low molar ratios of Calix6, the DPPG:Calix6 interactions are preferentially attractive, due to the interactions between the hydrophobic tails of DPPG and the tert-butyl groups of Calix6. Increasing the proportion of calixarene generates repulsive interactions. Calix6 significantly affects the hydrophobic tail organization, which was confirmed by PM-IRRAS measurements. Calix6 appears to be expelled from the mixed films at a biologically relevant surface pressure, π = 30 mN m-1, indicating a low interaction with the cell membrane model related to the absence of antibacterial activity.

Electrochemical detection of dopamine by a calixarene-cellulose acetate mixed Langmuir-Blodgett monolayer

The sensing performance of a Langmuir-Blodgett monolayer was significantly improved by controlling the film organization at the air-water interface. Cellulose acetate (CA) and 4-tert-butylcalix [6]arene (calix) were co-spread and formed a Langmuir film, which was efficiently transferred onto a preoxidized gold electrode, Au_ox. The modified gold electrode was applied as a fast, highly sensitive electrochemical sensing platform for the quantitative determination of a model molecule, dopamine (DA). The modified gold electrode, CA-calix/Au_ox, demonstrated better recognition and sensing ability towards dopamine as compared with electrodes modified by a single component. Under the optimized conditions, the reduction peak currents at the CA-calix/Au_ox increased linearly within the concentration range of dopamine from 5 to 100 and 100-7500 nM, and exhibited a very low limit of detection (LOD) of 2.54 nM (S/N = 3). These results suggest a simple, superior and efficient approach for the controllable rearrangement of Langmuir-Blodgett monolayers on a molecular level. The electroanalytical performance was optimized from the perspective of the electrode-electrolyte interface.