Humic Acids Aggregates as Microheterogeneous Reaction Media: Alkaline Hydrolysis Reactions

 Compounds 2022, 2(2), 131-143

The influence of humic aggregates in a water solution upon the chemical stability under basic conditions of different substrates was reviewed. The kinetic behavior of each substrate was modeled in terms of a micellar pseudophase model.

Interaction of Caffeic Acid with SDS Micellar Aggregates

Molecules 2019, 24(7), 1204

DOI: 10.3390/molecules24071204

Micellar systems consisting of a surfactant and an additive such as an organic salt or an acid usually self-organize as a series of worm-like micelles that ultimately form a micellar network. The nature of the additive influences micellar structure and properties such as aggregate lifetime. For ionic surfactants such as sodium dodecyl sulfate (SDS), CMC decreases with increasing temperature to a minimum in the low-temperature region beyond which it exhibits the opposite trend. The presence of additives in a surfactant micellar system also modifies monomer interactions in aggregates, thereby altering CMC and conductance. Because the standard deviation of β was always lower than 10%, its slight decrease with increasing temperature was not significant. However, the absolute value of Gibbs free enthalpy, a thermodynamic potential that can be used to calculate the maximum of reversible work, increased with increasing temperature and caffeic acid concentration. Micellization in the presence of caffeic acid was an endothermic process, which was entropically controlled. The enthalpy and enthropy positive values resulted from melting of “icebergs” or “flickering clusters” around the surfactant, leading to increased packing of hydrocarbon chains within the micellar core in a non-random manner. This can be possibly explained by caffeic acid governing the 3D matrix structure of water around the micellar aggregates. The fact that both enthalpy and entropy were positive testifies to the importance of hydrophobic interactions as a major driving force for micellization. Micellar systems allow the service life of some products to be extended without the need to increase the amounts of post-harvest storage preservatives used. If a surfactant is not an allowed ingredient or food additive, carefully washing it off before the product is consumed can avoid any associated risks. In this work, we examined the influence of temperature and SDS concentration on the properties of SDS–caffeic acid micellar systems. Micellar properties can be modified with various additives to develop new uses for micelles. This allows smaller amounts of additives to be used without detracting from their benefits.

Approach of Different Properties of Alkylammonium Surfactants using Artificial Intelligence and Response Surface Methodology

Tenside, Surfactants and Detergents

http://www.hanser-elibrary.com/doi/abs/10.3139/113.110483

Response surface methodology (RSM) and artificial neural networks (ANNs) architectures to predict the density, speed of sound, kinematic viscosity, and surface tension of aqueous solutions were developed. All models implemented using the root mean square error (RMSE) for training and validation phase were evaluated. The ANN models implemented show good values of R2 (upper than 0.974) and low errors in terms of average percentage deviation (APD) (lower than 2.92 %). Nevertheless, RSM models present low APD values for density and speed of sound prediction (lower than 0.31 %) and higher APD values around 5.18 % for kinematic viscosity and 14.73 % for surface tension. The results show that the different individual artificial neural networks implemented are a useful tool to predict the density, speed of sound, kinematic viscosity, and surface tension with reasonably accuracy.

Approach of different properties of alkylammonium surfactants using artificial intelligence and response surface methodology

Tenside, Surfactants, Detergents

Response surface methodology (RSM) and artificial neural networks (ANNs) architectures to predict the density, speed of sound, kinematic viscosity, and surface tension of aqueous solutions were developed. All models implemented using the root mean square error (RMSE) for training and validation phase were evaluated. The ANN models implemented show good values of R2 (upper than 0.974) and low errors in terms of average percentage deviation (APD) (lower than 2.92%). Nevertheless, RSM models present low APD values for density and speed of sound prediction (lower than 0.31%) and higher APD values around 5.18% for kinematic viscosity and 14.73% for surface tension. The results show that the different individual artificial neural networks implemented are a useful tool to predict the density, speed of sound, kinematic viscosity, and surface tension with reasonably accuracy.

Cleavage of carbofuran and carbofuran-derivatives in micellar aggregates

Progress in Reaction Kinetics and Mechanism, 40 (2015) 105-118

DOI: /10.3184/146867815X14259195615547

In recent years, the stability of carbamate pesticides have been studied by our research group in a wide range of biomimetic microheterogeneous media such as micelles or reverse micelles. These microheterogeneous media included different surfactant species and, hence, different self-assembled structures. In particular, basic hydrolysis of carbofuran and its derivatives have been analysed in the presence of anionic, cationic, non-ionic and reverse micelles. The results obtained from these physicochemical and kinetic studies, as well as a consistent comparison of them, are now summarised.