Norm descriptors for predicting the hydrophile-lipophile balance (HLB) and critical micelle concentration (CMC) of anionic surfactants

Computational prediction of the critical micelle concentration (CMC) of surfactants using the non-Bornian solvation model

The non-Bornian solvation model was used to predict the Gibbs energy change for the adsorption-desorption processes of ionic (14 anionic and 9 cationic) surfactants and 19 non-ionic surfactants at the interface between oil (O) (=nitrobenzene) and water (W). Except for 10 non-ionic surfactants (polyoxyethylenes) having semi-hydrophobic -OC2H4- groups, both ionic and non-ionic surfactants showed a clear energy minimum in their adsorption-desorption processes, providing reliable values of Gibbs energies, and , for the two adsorption processes from their respective bulk phases to the interface (I). It was then found that the critical micelle concentration (CMC) for surfactants (especially for the ionic ones) is linearly related to the two independent variables, i.e., and .

The Development of Dermal Self-Double-Emulsifying Drug Delivery Systems: Preformulation Studies as the Keys to Success

Self-emulsifying drug delivery systems (SEDDSs) are lipid-based systems that are superior to other lipid-based oral drug delivery systems in terms of providing drug protection against the gastrointestinal (GI) environment, inhibition of drug efflux as mediated by P-glycoprotein, enhanced lymphatic drug uptake, improved control over plasma concentration profiles of drugs, enhanced stability, and drug loading efficiency. Interest in dermal spontaneous emulsions has increased, given that systems have been reported to deliver drugs across mucus membranes, as well as the outermost layer of the skin into the underlying layers. The background and development of a double spontaneous emulsion incorporating four anti-tubercular drugs, clofazimine (CFZ), isoniazid (INH), pyrazinamide (PZY), and rifampicin (RIF), are described here. Our methods involved examination of oil miscibility, the construction of pseudoternary phase diagrams, the determination of self-emulsification performance and the emulsion stability index of primary emulsions (PEs), solubility, and isothermal micro calorimetry compatibility and examination of emulsions via microscopy. Overall, the potential of self-double-emulsifying drug delivery systems (SDEDDSs) as a dermal drug delivery vehicle is now demonstrated. The key to success here is the conduct of preformulation studies to enable the development of dermal SDEDDSs. To our knowledge, this work represents the first successful example of the production of SDEDDSs capable of incorporating four individual drugs.

Dispersants as an oil spill clean-up technique in the marine environment: A review

Oil is a major source of energy in the industrial world. Exploitation of oil and rigging activities, transportation via sea, and many other mechanical failures lead to oil spills into the marine environment. In view of these, the suitability and effectiveness of oil spill response methods have always been a topical discussion worldwide. It has become necessary, now than ever, for existing spill response methods used to remove oil from the environment to be improved upon and more importantly, develop new response materials that are sustainable and environmentally friendly. There exist surfactants in nature that are non-toxic and biodegradable, which can be explored to produce potential dispersants to help remove oil safely from the surface of marine water. This review comprises of the works and resourceful materials produced by various researchers and agencies in the field of oil spill response, placing emphasis on the use of dispersants in the marine environment.

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Smart dispersants have the potential to minimize dispersant wastage.

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Biodegradable dispersants may bring a closure to discussions on toxicity.

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Bio-based formulations have the potential to replace chemical based dispersants.

Machine learning hybrid approach for the prediction of surface tension profiles of hydrocarbon surfactants in aqueous solution

HYPOTHESIS

Predicting the surface tension (SFT)-log(c) profiles of hydrocarbon surfactants in aqueous solution is computationally non-trivial, and empirically challenging due to the diverse and complex architecture and interactions of surfactant molecules. Machine learning (ML), combining a data-based and knowledge-based approach, can provide a powerful means to relate molecular descriptors to SFT profiles.

EXPERIMENTS

A dataset of SFT for 154 model hydrocarbon surfactants at 20-30 °C is fitted to the Szyszkowski equation to extract three characteristic parameters (Γ_max,K_L and critical micelle concentration (CMC)) which are correlated to a series of 2D and 3D molecular descriptors. Key (∼10) descriptors were selected by removing co-correlation, and employing a gradient-boosted regressor model to rank feature importance and carry out recursive feature elimination (RFE). The hyperparameters of each target-variable model were fine-tuned using a randomised cross-validated grid search, to improve predictive ability and reduce overfitting.

FINDINGS

The ML models correlate favourably with test experimental data, with R²= 0.69-0.87, and the merits and limitations of the approach are discussed based on 'unseen' hydrocarbon surfactants. The incorporation of a knowledge-based framework provides an appropriate smoothing of the experimental data which simplifies the data-driven approach and enhances its generality. Open-source codes and a brief tutorial are provided.

First-principles prediction of critical micellar concentrations for ionic and nonionic surfactants

The concentration of surfactant in solution for which micelles start to form, also known as critical micelle concentration is a key property in formulation design. The critical micelle concentration can be determined experimentally with a tensiometer by measuring the surface tension of a concentration series. In analogy with experiments, in-silico predictions can be achieved through interfacial tension calculations. We present a newly developed method, which employs first principles-based interfacial tension calculations rooted in COSMO-RS theory, for the prediction of the critical micelle concentration of a set of nonionic, cationic, anionic, and zwitterionic surfactants in water. Our approach consists of a combination of two prediction strategies for modelling two different phenomena involving the removal of the surfactant hydrophobic tail from contact with water. The two strategies are based on regular micelle formation and thermodynamic phase separation of the surfactant from water and both are required to take into account a wide range of polarity in the hydrophilic headgroup. Our method yields accurate predictions for the critical micellar concentration, within one log unit from experiments, for a wide range of surfactant types and introduces possibilities for first-principles based prediction of formulation properties for more complex compositions.

Preparation of New Sargassum fusiforme Polysaccharide Long-Chain Alkyl Group Nanomicelles and Their Antiviral Properties against ALV-J

Avian leukosis virus subgroup J (ALV-J) is an immunosuppressive virus which has caused heavy losses to the poultry breeding industry. Currently, there is no effective medicine to treat this virus. In our previous experiments, the low-molecular-weight Sargassum fusiforme polysaccharide (SFP) was proven to possess antiviral activity against ALV-J, but its function was limited to the virus adsorption stage. In order to improve the antiviral activity of the SFP, in this study, three new SFP long-chain alkyl group nanomicelles (SFP-C12M, SFP-C14M and SFP-C16M) were prepared. The nanomicelles were characterized according to their physical and chemical properties. The nanomicelles were characterized by particle size, zeta potential, polydispersity index, critical micelle concentration and morphology. The results showed the particle sizes of the three nanomicelles were all approximately 200 nm and SFP-C14M and SFP-C16M were more stable than SFP-C12M. The newly prepared nanomicelles exhibited a better anti-ALV-J activity than the SFP, with SFP-C16M exhibiting the best antiviral effects in both the virus adsorption stage and the replication stage. The results of the giant unilamellar vesicle exposure experiment demonstrated that the new virucidal effect of the nanomicelles might be caused by damage to the phospholipid membrane of ALV-J. This study provides a potential idea for ALV-J prevention and development of other antiviral drugs.

Norm index-based QSPR model for describing the n-octanol/water partition coefficients of organics

The n-octanol/water partition coefficient (logK_ow) is widely used in the environmental, agricultural and pharmaceutical fields for the risk evaluation and application of organic chemicals. In this work, grounded on atomic distribution matrices, a norm index-based QSPR model was built for organic chemicals with 18 kinds of diverse structures. The statistical results (R² = 0.9037, RMSE = 0.4515) showed that the QSPR model for describing the logK_ow of organics was fitted well. Various validation results showed that the model had good robustness, good predictability and wide applicability. These satisfactory results indicated that the model was applicable for the logK_ow description of organic chemicals and that norm descriptors were reliable and general for the description of organic structures. The model was relatively better at describing logK_ow for aromatics, alcohols, nitriles, esters, amides, halogenated compounds, acids and amine compounds. The intensity of spatial branching and the space charge distribution intensity descriptors could have a greater impact on the logK_ow value of a compound.

The Emulsifying Properties of Hydrogenated Rosin Xylitol Ester as a Biomass Surfactant for Food: Effect of pH and Salts

The xylitol ester of hydrogenated rosin (XEHR) was obtained for the first time from biomass-based hydrogenated rosin and xylitol using an environmentally friendly, high-pressure CO2 catalytic synthesis. This compound is intended for use as an emulsifier for food. Analyses by ICP-AES showed the absence of heavy metal residues in the product, such that it met food standards. Fourier transform infrared and nuclear magnetic resonance spectroscopies together with gel permeation chromatography confirmed the successful esterification and the formation of a monoester and diester with molar masses of 427 and 772 g/mol. The emulsification of water/soybean oil mixtures by adding the XEHR was assessed at pH values of 4, 6.86, and 10 and in the presence of NaCl, KCl, MgCl2, and CaCl2. The XEHR was found to act as an emulsifier by reducing the interfacial tension of such mixtures to less than 2 mN/m under all conditions. The highest emulsifying activity index (9.52 m2/g) and emulsifying stability index (94.53%) were obtained after adding MgCl2 (100 mM). Particle size and confocal microscopy showed that the presence of salts gave a more uniform droplet size and a finer emulsion structure. The high viscosities of the emulsions containing salts also suggested a more cohesive oil droplet network.