Class Of Surfactants Research Articles

Nonylphenol and Cetyl Alcohol Polyethoxylates Disrupt Thyroid Hormone Receptor Signaling to Disrupt Metabolic Health.

Surfactants are molecules with both hydrophobic and hydrophilic structural groups that adsorb at the air-water or oil-water interface and serve to decrease the surface tension. Surfactants combine to form micelles that surround and break down or remove oils, making them ideal for detergents and cleaners. Two of the most important classes of nonionic surfactants are alkylphenol ethoxylates (APEOs) and alcohol ethoxylates (AEOs). APEOs and AEOs are high production-volume chemicals that are used for many industrial and residential purposes, including laundry detergents, hard-surface cleaners, paints, and pesticide adjuvants. Commensurate with better appreciation of the toxicity of APEOs and the base alkylphenols, use of AEOs has increased, and both sets of compounds are now ubiquitous environmental contaminants. We recently demonstrated that diverse APEOs and AEOs induce triglyceride accumulation and/or pre-adipocyte proliferation in vitro. Both sets of contaminants have also been demonstrated as obesogenic and metabolism disrupting in a developmental exposure zebrafish model. While these metabolic health effects are consistent across models and species, the mechanisms underlying these effects are less clear. This study sought to evaluate causal mechanisms through reporter gene assay assessments, relative binding affinity assays, co-exposure experiments, and use of both human cell and zebrafish models. We report that antagonism of thyroid hormone receptor signaling appears to mediate at least a portion of the polyethoxylate-induced metabolic health effects. These results suggest further evaluation is needed, given the ubiquitous environmental presence of these thyroid disrupting contaminants and reproducible effects in human cell models and vertebrate animals.

Locally Produced Sustainable and Resilient Surfactants for Enhanced Oil Recovery

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 24518, “Locally Produced Sustainable and Resilient Surfactants for Enhanced Oil Recovery,” by Syed Muhammad Shakil Hussain, SPE, Muhammad Shahzad Kamal, SPE, and Afeez Gbadamosi, King Fahd University of Petroleum and Minerals, et al. The paper has not been peer reviewed. Copyright 2024 International Petroleum Technology Conference. _ Chemical flooding is a major enhanced oil recovery (EOR) method for recovering residual oil within rock pores. Injected chemicals such as surfactant, however, must be soluble in low- and high-salinity brine, compatible with reservoir ions, and stable at elevated temperatures. The main objective of the study described in the complete paper is to explore the potential of locally produced surfactants for EOR in high-temperature and high-salinity reservoir environments. Design and synthesis of the new surfactants were achieved using green or no solvents. Importance of Chemical EOR Because only 15–20% of hydrocarbons can be extracted in the primary recovery stage, the waterflooding or gas-injection techniques usually are applied in the secondary recovery stage to extract 15–20% more oil and maintain the oilfield’s original pressure. After the application of these two techniques, however, a large amount of oil remains, the extraction of which requires the use of EOR, which can include thermal, gas, or chemical techniques. In thermal EOR, hot water or steamflooding are usually used to recover heavy oil. Currently, other thermal EOR methods such as in-situ combustion or steam-assisted gravity drainage receive considerable attention, especially in reservoirs containing heavy to extra-heavy crude oil. Gas methods normally are used in reservoirs featuring light and volatile oil. CO2 flooding is perhaps the most extensively applied gas EOR method for light oil extraction. Other gases such as nitrogen, hydrocarbon gas, acid gas, and air also are used for oil recovery. Chemical EOR involves the injection of chemicals including surfactants, polymers, alkali, and mixtures thereof. The polymer tends to increase the viscosity of the aqueous phase and lower the permeability of reservoir rocks. Surfactants minimize the interfacial tension (IFT), cause emulsification, and alter the wettability of the reservoir rocks. Alkali flooding generates in-situ surfactant by reacting with organic acid and ultimately reducing the IFT. Surfactants are organic compounds having both lipophilic and lipophobic parts. The lipophilic part is called a nonpolar compound and is soluble in the oil phase. The lipophobic part is termed a polar group and is soluble in the aqueous phase. Because of the availability of both lipophilic and lipophobic compounds in the same chemical structure, the surfactant stays on the interface ­of the water and oil phase and reduces the IFT. Based on the charge of the lipophobic head, the surfactants can be classified as nonionic, cationic, anionic, and zwitterionic (Fig. 1). Each class of surfactants possesses unique properties. For example, anionic surfactants are the material of choice in sandstone reservoirs because of their low adsorption into reservoir rocks. Similarly, the cationic surfactants exhibit minimum adsorption in carbonate rocks because of charge repulsion. Zwitterionic surfactants (ZS) show high heat-stability and salt-tolerance properties, and nonionic surfactants are known for their use as cosurfactants or solvents.

Photoswitchable detergents for light-controlled liposome lysis and channel gating.

Modulation of membrane properties via photoswitchable lipids has attracted attention due to the unparalleled spatiotemporal resolution of their functional control. Beside lipids, detergents are another prominent class for selective membrane perturbations owing to their ease of handling and spontaneous insertion in lipid bilayers. Herein, we describe the synthesis and characterization of three classes of visible light-sensitive surfactants with various azobenzene tail chain lengths. The photoswitchable detergents show water-solubility and micellization as well as undergo reversible isomerization under blue-/green light illumination. We demonstrate that the light-induced structural change of azobenzene can lead to vesicle rupture, making them a tool for controlled cargo release from vehicles. Via spontaneous insertion into the plasma membrane of mammalian cells transiently transfected with MscL, we used the azobenzene-derived detergents to optically activate the transmembrane mechanosensitive channel. This led to the rapid controlled uptake of membrane-impermeable molecules. Since detergents are extensively used in biochemistry and biotechnology, we propose that the photoswitchable detergents will be useful tools for the spatiotemporal modulation of membrane properties. Additionally, our work provides a design strategy for new detergents in membrane (protein) research.

Synthesis and properties of pH‐dependent Gemini surfactant containing tripeptide structure

AbstractAmino acid surfactants have mild performance and are sourced from renewable biomass. Compared to classical surfactants, Gemini surfactants have superior properties. The amino acid Gemini surfactants are believed to be adopted more widely. The Gemini surfactant with tripeptide structure, sodium di(lauroyl glutamyl) lysine (DLGL), was prepared by amidation utilizing methyl laurate, glutamate and lysine and characterized by 1H NMR, 13C NMR and MS. Additionally, the pKa value, surface activities, aggregation, foaming properties and emulsifying attributes of the DLGL surfactant in aqueous solution with varied pH values were examined. The results indicate that the protonation‐deprotonation behavior of the DLGL surfactant is highly dependent on pH values. The surface tension, critical micelle concentration (cmc), foamability and foam stability exhibited superior performance at pH 6 and 7. Conversely, superior emulsifying ability was observed at pH 9 and 10. Moreover, the spherical vesicles were formed by the DLGL surfactant at pH 6, 7 or 8 while the micelles were generated at pH 9 or 10.

Salt-Induced Linker Dehydration Modulates Micellar Structure in Ether-Linked Sulfate Surfactants.

Ether-linked surfactants are widely used in formulations such as liquid soaps, but despite their ubiquity, it is unclear how n-ethylene glycol linkers in surfactants, such as sodium lauryl n-(ethylene glycol) sulfate (SLEnS), influence micellar packing in the presence of NaCl. In the present work, we probe the structure and hydration of ether linkers in micelles comprising monodisperse SLEnS surfactants using contrast-variation small-angle neutron scattering (CV-SANS) and small-angle X-ray scattering (SAXS). Using SAXS, changes in micellar structure were observed for SLEnS (n = 1, 2, or 3) arising from the extent of ethoxylation. Scattering profiles indicated a clear transition from elongated cylindrical micelles to shorter ellipsoidal micelles with increasing ethoxylation. With CV-SANS, micellar structure and linker geometries of SLE3S were able to be resolved, indicating that a change in micellar architecture is modulated by dehydration of the tri(ethylene glycol) linker, offering new insights into the role of water and ions in the self-assembly of this key class of surfactants.

Effect of a fluorinated surfactant on Langmuir monolayer properties of minimal-linker gemini surfactants

A new class of carboxylic acid-terminated gemini surfactants which contain the smallest possible headgroup linker (a single bond) has recently been reported in the literature. In this current work, we have explored how Langmuir monolayers of two different alkyl tail chain length variants (n = 12, n = 16) of these surfactants, dubbed Cn-0-Cn, are impacted by mixing with a benchmark perfluorinated surfactant, perfluorotetradecanoic acid (PF). Pure PF and C16-0-C16 monolayers share similar general characteristics, yielding compact, incompressible, solid-like films at the air-water interface. In contrast, the shorter tail chain variant, C12-0-C12 forms expanded, compressible liquid-like films. While both tail chain variants formed mixed films with PF that were generally expanded in comparison with their pure components, and were also phase-separated, the extent of interactions between film components and the resulting micron-scale morphology of the mixed films were different for the two alkyl chain lengths. Overall, PF induces different packing behavior in both the systems and the observations are attributed to the difference in the dispersion forces originating from the tail chain length differences.

Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks.

The critical micelle concentration (CMC) of surfactant molecules is an essential property for surfactant applications in the industry. Recently, classical quantitative structure-property relationship (QSPR) and graph neural networks (GNNs), a deep learning technique, have been successfully applied to predict the CMC of surfactants at room temperature. However, these models have not yet considered the temperature dependence of the CMC, which is highly relevant to practical applications. We herein develop a GNN model for the temperature-dependent CMC prediction of surfactants. We collected about 1400 data points from public sources for all surfactant classes, i.e., ionic, nonionic, and zwitterionic, at multiple temperatures. We test the predictive quality of the model for the following scenarios: (i) when CMC data for surfactants are present in the training of the model in at least one different temperature and (ii) CMC data for surfactants are not present in the training, i.e., generalizing to unseen surfactants. In both test scenarios, our model exhibits a high predictive performance of R2 ≥ 0.95 on test data. We also find that the model performance varies with the surfactant class. Finally, we evaluate the model for sugar-based surfactants with complex molecular structures, as these represent a more sustainable alternative to synthetic surfactants and are therefore of great interest for future applications in the personal and home care industries.

Kinetic of Aerobic Decomposition Process of Linear Alkylbenzene Sulfonate (LAS) in a Well-Shaped Bioreactor Using Commercial Inoculum

Linear alkylbenzene sulfonate (LAS) belongs to a class of surfactants claimed as an environmentally friendly detergent due to its biodegradability. However, the disposal of LAS waste into the waters without prior treatment causes a risk to the ecosystem. These experiments aimed to study the effects of commercial inoculum size EM-4 on the aerobic decomposition process of LAS in a well-shaped bioreactor. These experiments of LAS decomposition were carried out in a batch system aerated by 2.5 L/min for the low and high initial LAS concentrations. The effects of inoculum acclimation were also investigated for the high LAS concentration. The effects of inoculum size were explored at sizes ranging from 5 to 20% v/v, and samples were taken on a regular basis for residual LAS assessment. The first-order kinetic model gave the best fit to the rate of LAS decomposition, with the highest rate coefficient of 10.44 x 10-2 hour-1. This was achieved by using a 20% v/v inoculum for the initial low concentration of LAS, resulting in the highest decomposition efficiency of 89.4% after 24 hours of incubation. The decomposition rate was slower at the high LAS concentrations than at the low concentrations. The inoculum acclimation increased the decomposition rate for the high LAS concentrations. The results of this study show great potential for the bioremediation of LAS detergent waste using commercial inoculum in a well-shaped batch bioreactor.

Metabolism of alcohol ethoxylates (AEs) in rat, hamster, and human hepatocytes and liver S9: a pilot study for metabolic stability, metabolic pathway, and metabolites identification in vitro and in silico

Alcohol ethoxylates (AEs) are a well-known class of non-ionic surfactants widely used by the personal care market. The aim of this study was to evaluate and characterize the in vitro metabolism of AEs and identify metabolites. Five selected individual homologue AEs (C8EO4, C10EO5, C12EO4, C16EO8, and C18EO3) were incubated using human, rat, and hamster liver S9 fraction and cryopreserved hepatocytes. LC–MS was used to identify metabolites following the incubation of AEs by liver S9 and hepatocytes of all three species. All AEs were metabolized in these systems with a half-life ranging from 2 to 139 min. In general, incubation of AE with human liver S9 showed a shorter half-life compared to rat liver S9. While rat hepatocytes metabolized AEs faster than human hepatocytes. Both hydrophobic alkyl chain and hydrophilic EO head group groups of AEs were found to be target sites of metabolism. Metabolites were identified that show primary hydroxylation and dehydrogenation, followed by O-dealkylation (shortening of EO head groups) and glucuronidation. Additionally, the detection of whole EO groups indicates the cleavage of the ether bond between the alkyl chain and the EO groups as a minor metabolic pathway in the current testing system. Furthermore, no difference in metabolic patterns of each individual homologue AE investigated was observed, regardless of alkyl chain length or the number of EO groups. Moreover, there is an excellent agreement between the in vitro experimental data and the metabolite profile simulations using in silico approaches (OECD QSAR Toolbox). Altogether, these data indicate fast metabolism of all AEs with a qualitatively similar metabolic pathway with some quantitative differences observed in the metabolite profiles. These metabolic studies using different species can provide important reference values for further safety evaluation.

Studies on the properties and molecular dynamics simulations of nonionic surfactants based on succinic acid derivatives

AbstractNonionic surfactants have proven useful in various applications such as wastewater treatment, enhanced oil recovery, dyeing, and cosmetics. Novel nonionic surfactants such as PEMP, BEMP, HEMP and BEEP were synthesized based on succinic acid derivatives and using L‐isoleucine as the linking group and four polyether alcohols as the hydrophilic group. First, the structures of the four nonionic surfactants were studied using Fourier transform infrared (FTIR) spectroscopy and nuclear magnetic resonance (NMR) spectra. Then the critical micelle concentration (CMC) and surface tension at CMC (γCMC) of the four nonionic surfactants in aqueous solution were tested. γ‐lg c curves determined the relationships of their surface properties as BEEP > PEMP > BEMP > HEMP. In order to expand the range of applications for nonionic surfactants, we evaluated the salt‐resistant properties of four such surfactants. Our findings demonstrated that this class of surfactants indeed has superior salt‐resistant properties. Molecular dynamics (MD) simulations were used to study how surfactant molecules aggregate in the interfacial film. The study investigated the trend of solvent accessible surface area (SASA) over time. Results showed that the surfactant molecules interacted well with solvent molecules in the equilibrium state. This study investigates the performance differences among four types of surfactants using the electrostatic potential (ESP) distribution of their molecules. The study employed both experimental and computational simulations to provide a more comprehensive understanding of surfactant properties. The results offer insights into the theoretical research and application extension of this class of surfactants.

Thin layer chromatography of methylated derivatives of sodium alkylbenzenesulfonates in water analysis by GC-MS

Sodium alkylbenzene sulfonates or linear alkyl benzene sulfonates (LAS) are the most common synthetic anionic surfactants and water pollutants. They can cause both acute and chronic toxic effects on water organisms. Selective determination of sodium alkylbenzene sulfonates as a separate class of anionic surfactants is possible using gas chromatography coupled with mass spectrometry (GC-MS) in the form of linear alkylbenzenesulfonic acid methyl esters (LABSA ME). In order to purify the extracts and concentrate the analytes, we studied the behaviour of these compounds by ascending high-performance thin-layer chromatography using Kieselgel 60 F254 and Sorbfil plates. A mixture of n-hexane and methanol solvents in a ratio of 23:1 (by volume) was used as the mobile phase. Under these conditions, sodium alkylbenzenesulphonates remain on the start line, while their derivatives (ME ABSC), obtained by methylation with trimethyl orthoformate in the presence of trifluoroacetic acid (with a yield of η=98%), form zones characterised by retention coefficient values of Rf = 0.62 and Rf = 0.71 on Kieselgel 60 F254 and Sorbfil plates, respectively. The repeatability of the Rf values was characterised by a standard deviation of 6.1 and 5.9 %, respectively (n=16). The completeness of extraction (95.0–100.0 %) of analytes from the plates by descending TLC with acetonitrile was noted. The applicability of the TLC method for the concentration of analytes and pretreatment of extracts on the example of real water samples was shown. Using GC-MS with electron impact ionisation, we determined the concentrations of sodium alkylbenzenesulphonates in water sampled in the southern basin of Lake Baikal from a depth of 400 m (0.24±0.02 µg/dm3) and in snowmelt water from the ice of the Krestovka River where it flows into Lake Baikal near the village of Listvyanka (31.1 ± 1.0 µg/dm3).

Urea as hydrogelator of surfactants

HypothesisThe formation of adducts via urea interaction with distinct classes of surfactants (cationic, anionic, nonionic, and zwitterionic), leading to their assembly into lamellar structures and subsequent formation of hydrogels. The characteristics of these hydrogels are associated with both, the length of the alkyl chain, and the specific head group of the surfactant molecules. ExperimentsCharacterization of adduct formation was conducted using Wide-Angle X-ray Scattering (WAXS), while Small-Angle X-ray Scattering (SAXS) was employed to probe the subsequent assembly into lamellar structures. The kinetics of hydrogel formation were assessed through rheological measurements and observed thermal transitions utilizing Differential Scanning Calorimetry (DSC). FindingsThe investigation revealed a universal propensity for hydrogel formation across all surfactant classes. The formation arises from the interactions between urea molecules via hydrogen bonding, forming adducts around the surfactant chains. In sequence, the adducts self-assemble in lamellae. This process constructs the intricate three-dimensional network characteristic of the hydrogel. Furthermore, the kinetics of hydrogel formation, and their rheological properties under equilibrated conditions, were found to be significantly influenced by the nature of the polar head group of the surfactant molecules. This is the first evidence on the formation of adducts of urea with classes of surfactants. As they are common components in cosmetic, supramolecular hydrogels have high potential to be used in formulations.

Synergistic effects of nonionic surfactants ethoxylated alkylamines and sodium dodecyl sulfate in mixed systems

HypothesisIn general, the performance of surfactant hybrid systems is better than that of single surfactants, so surfactant hybrid systems are widely used in various industries. As a very important class of nonionic surfactants, ethoxylated alkylamines have been widely used in industries such as washing, coating, and pesticide, but little research has been conducted on their mixed systems. In order to improve the utilization efficiency of surfactants and reduce wastage, the surface properties and aggregation behavior of ethoxylated alkylamine mixed systems should be further explored. ExperimentIn this study, the nonionic surfactant ethoxylated dodecylamine (AC-1202) and the anionic surfactant sodium dodecyl sulfate (SDS) were used to form a mixed system. The static surface tension and interaction parameters of the mixed system under the influence of inorganic salt ions were investigated using a KRÜSS K12 surface tensiometer. The diffusion process of the mixed system was investigated using a KRÜSS bubble pressure tensiometer. At the same time, the aggregate behavior of the mixed system was studied by particle size analyzer. In addition, the contact angle and rheological properties of the mixed solution were also investigated. FindingsThe SDS/AC-1202 mixture system formed a synergistic effect that could reduce the CMC value to 24.20 mN/m and the CMC value was as low as 22.89 mN/m after the addition of inorganic salts. The mixed system conforms to the kinetic mechanism of mixing and diffusion and the Ostwald de model for non-Newtonian fluids. Finally, there is a good aggregation pattern in the mixed system, and the stronger synergistic effect will lead to the reduction of the average particle size of the mixture to 45.41 nm.

Graph neural networks for surfactant multi-property prediction

Surfactants are of high importance in different industrial sectors such as cosmetics, detergents, oil recovery and drug delivery systems. Therefore, many quantitative structure–property relationship (QSPR) models have been developed for surfactants. Each predictive model typically focuses on one surfactant class, mostly nonionics. Graph Neural Networks (GNNs) have exhibited a great predictive performance for property prediction of ionic liquids, polymers and drugs in general. Specifically for surfactants, GNNs can successfully predict critical micelle concentration (CMC), a key surfactant property associated with micellization. A key factor in the predictive ability of QSPR and GNN models is the data available for training. Based on extensive literature search, we create the largest available CMC database with 429 molecules and the first large data collection for surface excess concentration (Γm), another surfactant property associated with foaming, with 164 molecules. Then, we develop GNN models to predict the CMC and Γm and we explore different learning approaches, i.e., single- and multi-task learning, as well as different training strategies, namely ensemble and transfer learning. We find that a multi-task GNN with ensemble learning trained on all Γm and CMC data performs best. Thus, our results show that the simultaneous use of data from highly correlated properties can improve the predictability of surfactant properties for which only a small amount of experimental data is available. Finally, we test the ability of our CMC model to generalize on industrial grade pure component surfactants. The GNN yields highly accurate predictions for CMC, showing great potential for future industrial applications.

Self-assembly mechanism and application performance in aqueous solutions mediated by ethylene oxide chains in alcohol ether carboxylates and cocamidopropyl betaine

Zwitterionic Cocoamidopropyl Betaine (CAB) and anionic alcohol ether carboxylates have garnered significant attention within the realms of green and colloid chemistry owing to their inherent biocompatibility, multi-responsiveness, and diverse applications. Systematic inquiry into the physicochemical properties, self-assembly mechanisms, and application efficacy of complex systems comprising alcohol ether carboxylate salts with varying ethylene oxide (EO) units (AECnH, n = 5, 7, 9) and CAB-35 in aqueous solutions was undertaken. It was discerned that the optimum physicochemical attributes of the complex system are attained at a molar ratio of AEC of 0.5 (αAEC = 0.5). Incremental augmentation in the number of EO units facilitated the formation of rod-like micelles, exhibiting relatively unstable characteristics, while a reduction in the number of EO units led to the generation of comparatively stable spherical micelles. The self-assembly of micelles in these hybrid systems predominantly hinges upon hydrogen bonding, electrostatic interactions, and hydrophobic forces. Furthermore, kinetic analysis validated that the genesis of micelles in all three hybrid systems is propelled by enthalpy, with the adsorption process entailing a mechanism characterized by mixed diffusion-kinetic adsorption. The optimal wetting performance of the complex system was observed at αAEC = 0.5, while the foam performance demonstrated a diminishing trend with escalating αAEC. This comprehensive discourse delineates the synergistic mechanisms and application efficacy of two distinct classes of green surfactants with disparate charges in aqueous solutions, while contemplating the influence of varying numbers of ethylene oxide chains. Not only does it furnish fundamental insights into their properties, but it also proffers a novel standpoint for the exploration of green surfactants.

Topical pickering emulsion versus classical excipients: A study of the residual film on the human skin

The interest in Pickering emulsions is based on the possibility of replacing classical emulsifiers with solid particles. These emulsions are very attractive in the pharmaceutical field for their stability virtues and as a vehicle to deliver active ingredients. The study aimed to analyze the properties of the residual film of the Pickering emulsions on the human skin compared to conventional systems.For this project, three types of solid particles were used: titanium dioxide, zinc oxide and silicon dioxide. All of them are capable of stabilizing the oil/water interface and thus forming totally emulsified systems. To create an emulsion of reference, a classical surfactant was used as an excipient. Complementary systems containing both particles and the emulsifier were also analyzed. Then, a combined approach between physicochemical and biometrological in vivo analysis was employed.The study proved that Pickering emulsions stabilized by the metal oxides were distinct from the reference emulsion in terms of droplet sizes and organization, rheological and textural responses. Consequently, it impacted the properties of the residual film once the product was applied to the skin. The particle-stabilized emulsions formed a hydrophobic film counter to conventional excipients.Also, the Friction parameter (or the roughness of the film) was directly linked to the quantity of the particles used in the formulation and their perception on the skin surface. The use of the particles blurs the glossy effect of the oil phase. Finally, it was observed that the appearance of the residual film was impacted by the type of the particle, namely TiO2 and ZnO particles.

Research Progress of eco-friendly Sugar-based Surfactants

Surfactant is a common industrial product widely used in chemical industry, food production, biomedicine and other fields. A variety of glucose-based bisubstituted surfactants have been developed, which not only contain the advantages of other classes of sugar-based surfactants, but also have the properties of mild conditions of use, good bactericidal ability, and non-irritation of the skin, etc. In addition, sugars are widely sourced and renewable, and the production of sugar-based surfactants with degradability has become a hot spot of the current research. This paper summarises the types of common sugar-based surfactants, the test methods of related properties and the application prospects.

Research Progress in Structure Synthesis, Properties, and Applications of Small-Molecule Silicone Surfactants.

Silicone surfactants have garnered significant research attention owing to their superior properties, such as wettability, ductility, and permeability. Small-molecular silicone surfactants with simple molecular structures outperform polymeric silicone surfactants in terms of surface activity, emulsification, wetting, foaming, and other areas. Moreover, silicone surfactants with small molecules exhibit a diverse and rich molecular structure. This review discusses various synthetic routes for the synthesis of different classes of surfactants, including single-chain, "umbrella" structure, double chain, bolaform, Gemini, and stimulus-responsive surfactants. The fundamental surface/interface properties of the synthesized surfactants are also highlighted. Additionally, these surfactants have demonstrated enormous potential in agricultural synergism, drug delivery, mineral flotation, enhanced oil recovery, separation, and extraction, and foam fire-fighting.

QSPR for the prediction of critical micelle concentration of different classes of surfactants using machine learning algorithms

The determination of the critical micelle concentration (CMC) is a crucial factor when evaluating surfactants, making it an essential tool in studying the properties of surfactants in various industrial fields. In this present research, we assembled a comprehensive set of 593 different classes of surfactants including, anionic, cationic, nonionic, zwitterionic, and Gemini surfactants to establish a link between their molecular structure and the negative logarithmic value of critical micelle concentration (pCMC) utilizing quantitative structure-property relationship (QSPR) methodologies. Statistical analysis revealed that a set of 14 significant Mordred descriptors (SlogP, GATS6d, nAcid, GATS8dv, GATS4dv, PEOE_VSA11, GATS8d, ATS0p, GATS1d, MATS5p, GATS3d, NdssC, GATS6dv and EState_VSA4), along with temperature, served as appropriate inputs. Different machine learning methods, such as multiple linear regression (MLR), random forest regression (RFR), artificial neural network (ANN), and support vector regression (SVM), were employed in this study to build QSPR models. According to the statistical coefficients of QSPR models, SVR with Dragonfly hyperparameter optimization (SVR-DA) was the most accurate in predicting pCMC values, achieving (R2 = 0.9740, Q2 = 0.9739, r‾m2 = 0.9627, and Δrm2 = 0.0244) for the entire dataset.

Exploring fungal bioemulsifiers: insights into chemical composition, microbial sources, and cross-field applications.

The demand for emulsion-based products is crucial for economic development and societal well-being, spanning diverse industries such as food, cosmetics, pharmaceuticals, and oil extraction. Formulating these products relies on emulsifiers, a distinct class of surfactants. However, many conventional emulsifiers are derived from petrochemicals or synthetic sources, posing potential environmental and human health risks. In this context, fungal bioemulsifiers emerge as a compelling and sustainable alternative, demonstrating superior performance, enhanced biodegradability, and safety for human consumption. From this perspective, the present work provides the first comprehensive review of fungal bioemulsifiers, categorizing them based on their chemical nature and microbial origin. This includes polysaccharides, proteins, glycoproteins, polymeric glycolipids, and carbohydrate-lipid-protein complexes. Examples of particular interest are scleroglucan, a polysaccharide produced by Sclerotium rolfsii, and mannoproteins present in the cell walls of various yeasts, including Saccharomyces cerevisiae. Furthermore, this study examines the feasibility of incorporating fungal bioemulsifiers in the food and oil industries and their potential role in bioremediation events for oil-polluted marine environments. Finally, this exploration encourages further research on fungal bioemulsifier bioprospecting, with far-reaching implications for advancing sustainable and eco-friendly practices across various industrial sectors.