Prediction of the surface tension of surfactant mixtures for detergent formulation using Design Expert software

Abstract  

The formulation of a detergent product is a complicated task which depends on many economical, ecological, and practical parameters. The goal is to achieve a product which will have optimal washing properties and significantly decrease the surface tension. Therefore, prediction of the minimal surface tension of a mixture of four different surfactants can be very beneficial for the industry. In this work this task was performed by using Stat-Ease Design Expert software. This program was successfully applied for prediction of the minimal surface tension and optimization of the composition of different surfactant mixtures. Predicted data were compared with experimental results, and very good correlation was achieved. For further application, more complex optimization procedures could be performed by adding additional parameters to the Design Expert software. Therefore, this program is extremely useful for the laundry industry and could be successfully applied in many other, more complex tasks.     

Determination of zwitterionic and cationic surfactants by high-performance liquid chromatography with chemiluminescenscent nitrogen detection

The use of chemiluminescent nitrogen specific detection (CLND) combined with an HPLC separation allows for the identification and quantification of cationic and zwitterionic surfactants. The CLND provides equimolar responses, based on the amount of nitrogen within any compound. This allows for the detection of any nitrogen containing surfactant. Reversed-phase separation methods using cyano columns are developed for cationic and zwitterionic (sulfobetaine) surfactant mixtures. The limits of detection for these surfactants are in the single micromolar range (1 ng N). A linear response was obtained (R2=0.9981) between 50 microM and 5 mM. The methodology was then applied to the determination of an industrial zwitterionic surfactant, Rewoteric AM CAS U [coco(amidopropyl)hydroxyldimethylsulfobetaine].     

Determination of surfactants by capillary electrophoresis

Capillary electrophoresis has been increasingly used during the past few years for the separation and determination of surfactants. These substances are applied in many household and industrial products such as laundry detergents, cosmetics and pharmaceuticals, often as homologous and isomeric mixtures. Product development and control as well as toxicological and environmental analyses require selective and sensitive analytical methods. This review presents capillary electrophoretic techniques to determine important representatives of cationic, anionic, and neutral surfactants. The application of different buffer additives such as organic solvents, cyclodextrins or micelles to enhance the resolution of complex mixtures is discussed. Besides direct and indirect UV and fluorescence detection, examples for conductivity and mass spectrometric detection are also given. Derivatization procedures to improve the detectability and implement charge in neutral analytes are described. The successful use of capillary electrophoresis for surfactant determinations has proven that it can serve as a routine technique in many real-world applications. Robust, validated methods for the quantitation of single compounds, such as alkylbenzene sulfonates, sodium dodecyl sulfate and benzalkonium salts, are now available. Characteristic peak patterns (fingerprint analysis) can be used for the identification of surfactants in multicomponent formulations (e.g. ethoxylates and phosphonates).     

Development and validation of an at-line fast and non-destructive Raman spectroscopic method for the quantification of multiple components in liquid detergent compositions

Implementation of process analytical technology (PAT) tools in the manufacturing process of liquid detergent compositions should allow fast and non-destructive evaluation of the product quality. The aim of this study was to develop and validate a rapid method for quantifying the chemical compounds of five washing liquid precursors. Raman spectroscopy was applied in combination with a two-step multivariate modeling procedure. In first instance, a SIMCA (Soft Independent Modeling of Class Analogy) model was developed and validated, allowing the distinction between the different laundry detergents. Once the product was correctly identified, it was aimed at predicting the concentration of its individual components using partial least squares (PLS) models. Raman spectra were collected at-line with a total acquisition time of 20 s, using a non-contact fiber-optic probe.     

Sorbent extraction behavior of a nonionic surfactant,Triton X-100, onto commercial charcoal from low level radioactive waste

In nuclear power plants and nuclear laboratories, laundry wastewater is generated from decontaminating polluted instruments, worker’s clothes and taking shower after work. Laundry wastewater contains radionuclides and surfactants. The surfactants included in laundry wastewater affect the extraction of radionuclides. Therefore, surfactants should be removed before extraction of radionuclides. The objective of the present work is to assess the ability of commercial charcoal for the removal of nonionic surfactants, where, commercial charcoal is a commonly available adsorbent for treatment. Charcoal was characterized using different analytical techniques. The isotherm models and thermodynamic parameters were evaluated. Charcoal was applied to the removal of surfactant from liquid radioactive waste. The data obtained can be used for designing a plant for treatment of surfactant rich water and wastewater economically.     

Application of an integrated matrix-assisted laser desorption/ionization time-of-flight, electrospray ionization mass spectrometry and tandem mass spectrometry approach to characterizing complex polyol mixtures

Polyols are being used in a wide range of industrial applications including surfactants and precursors for grafted polymers. The characterization of polyols is of significance in correlating compositions and structures with their properties. We illustrate two real world examples where traditional analytical methods including GPC and NMR failed to reveal compositional differences, but the combination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF), electrospray ionization mass spectrometry (ESI MS), and MS/MS can produce compositional information required for problem solving. The first example involves failure analysis of four ethylene oxide and propylene oxide (EO/PO) copolymer products. The results from the mass spectrometry analysis unequivocally demonstrate that one of the samples has a small variation in copolymer composition, leading to its abnormal activity. The second example is in the area of deformulation of complex polyol mixtures. Two samples displaying similar properties and activities were found to be two different polyol blends. One of the samples is a more cost-effective product. These examples demonstrate that MALDI, ESI MS, and MS/MS should be seriously considered as an integrated component of an overall polyol characterization program in product failure analysis and deformulation.     

Studies in Detergency: Influence of Different Factors for Removing Motor Oil Stain from the Cotton Fabric

The ability of surfactants to remove a organic soil from the cotton fabric has been investigated using various parameters such as temperature and hardness of water. The surfactants such as alkylpolyglucosides (APG), sodium lauryl sulphate (SLS), and alpha olefin sulphonate (AOS) have been taken to formulate the detergent as such and in mixtures to evaluate the detergency performance to remove motor oil from the 100% cotton fabric. In the past, the detergency of nonionic APG surfactants has not been well studied. The behavior of commercial APG surfactants and mixtures of APGs with other common surface cleaning agents (SLS & AOS) in laundry applications has been investigated. Motor oil is the toughest soil to remove as it contains nonpolar organic compounds. The performance of detergency was evaluated at different temperatures (30°C, 45°C, and 60°C) and in the presence of hard water (40, 100, and 300 ppm).     

Quantitative monitoring of yeast fermentation using Raman spectroscopy

Compared to traditional IR methods, Raman spectroscopy has the advantage of only minimal interference from water when measuring aqueous samples, which makes this method potentially useful for in situ monitoring of important industrial bioprocesses. This study demonstrates real-time monitoring of a Saccharomyces cerevisiae fermentation process using a Raman spectroscopy instrument equipped with a robust sapphire ball probe. A method was developed to correct the Raman signal for the attenuation caused by light scattering cell particulate, hence enabling quantification of reaction components and possibly measurement of yeast cell concentrations. Extinction of Raman intensities to more than 50 % during fermentation was normalized with approximated extinction expressions using Raman signal of water around 1,627 cm^?1 as internal standard to correct for the effect of scattering. Complicated standard multi-variant chemometric techniques, such as PLS, were avoided in the quantification model, as an attempt to keep the monitoring method as simple as possible and still get satisfactory estimations. Instead, estimations were made with a two-step approach, where initial scattering correction of attenuated signals was followed by linear regression. In situ quantification measurements of the fermentation resulted in root mean square errors of prediction (RMSEP) of 2.357, 1.611, and 0.633 g/L for glucose, ethanol, and yeast concentrations, respectively.     

Detection of the site of phosphorylation in a peptide using Raman spectroscopy and partial least squares discriminant analysis

Normal (non-enhanced) Raman spectroscopy is used to determine the site of phosphorylation on a 13-residue peptide whose sequence derives from the cellular protein pp60(c-src) (protein tyrosine kinase). Raman spectra of serine, threonine and tyrosine amino acids and their phosphorylated derivatives are used to aid in the interpretation of peptide spectra. The purity of the synthetic peptides are confirmed by mass spectroscopy. Peptide Raman measurements are performed using the recently reported drop-coating deposition Raman (DCDR) method, followed by Savistky-Golay second derivative (SGSD) pre-processing and multivariate spectral classification using partial least squares (PLS) discriminant analysis. Leave-one-out training/testing results are displayed using a PLS psuedo-probability score plot and shown to facilitate error-free spectral determination of the site of phosphorylation.     

Multicomponent analysis: Comparison of various graphical and numerical methods

The performance of several graphical (zero-crossing and derivative quotient spectra with standardized divisor) and numerical methods (MULTIC and PLS) for the resolution of binary and ternary mixtures of species is compared. Numerical methods were found to be specially suited to multicomponent analysis, particularly for mixtures containing more than two analytes with highly overlapped spectra. The results obtained by using the compared methods to analyse various synthetic mixtures of acetylsalicylic acid, caffeine and thiamine were quite consistent and errors in the simultaneous quantification of the analytes amounted to less than 5% in all instances.     

Enzyme activity and stability control by amphiphilic self-organizing systems in aqueous solutions

The interaction of surfactants with proteins in aqueous solutions has been the subject of many investigations to understand the interactions between membrane proteins and lipids, structurally similar to synthetic surfactants. The effect of surfactant on enzyme structure and activity is the result of chemically selective interactions that may be influenced both by the enzyme structure and by the chemistry of the surfactant. For many years, surfactants have been considered as non-specific denaturants of proteins, even if in the literature several of them are reported to enhance activity and/or stability of some enzymes: the detergent can interact with the enzyme and cause a conformational change to a more active form and/or stabilize its native folded structure. Although the surfactant head group seems to have a determining role, other structural features of the detergent are also important in influencing the catalytic properties of an enzyme, i.e. head group size and its hydrophobic/hydrophilic balance. Up to now it is very difficult to predict the molecular features of the surfactant and an extensive investigation on the relationship between the surfactant chemical structure and the catalytic properties of enzyme is still required.     

Polymer/surfactant interactions at the air/water interface

The development of neutron reflectometry has transformed the study and understanding of polymer/surfactant mixtures at the air/water interface. A critical assessment of the results from this technique is made by comparing them with the information available from other techniques used to investigate adsorption at this interface. In the last few years, detailed information about the structure and composition of adsorbed layers has been obtained for a wide range of polymer/surfactant mixtures, including neutral polymers and synthetic and naturally occurring polyelectrolytes, with single surfactants or mixtures of surfactants. The use of neutron reflectometry together with surface tensiometry, has allowed the surface behaviour of these mixtures to be related directly to the bulk phase behaviour. We review the broad range of systems that have been studied, from neutral polymers with ionic surfactants to oppositely charged polyelectrolyte/ionic surfactant mixtures. A particular emphasis is placed upon the rich pattern of adsorption behaviour that is seen in oppositely charged polyelectrolyte/surfactant mixtures, much of which had not been reported previously. The strong surface interactions resulting from the electrostatic attractions in these systems have a very pronounced effect on both the surface tension behaviour and on adsorbed layers consisting of polymer/surfactant complexes, often giving rise to significant surface ordering.     

Influence of data pre-processing on the quantitative determination of the ash content and lipids in roasted coffee by near infrared spectroscopy

In near-infrared (NIR) measurements, some physical features of the sample can be responsible for effects like light scattering, which lead to systematic variations unrelated to the studied responses. These errors can disturb the robustness and reliability of multivariate calibration models. Several mathematical treatments are usually applied to remove systematic noise in data, being the most common derivation, standard normal variate (SNV) and multiplicative scatter correction (MSC). New mathematical treatments, such as orthogonal signal correction (OSC) and direct orthogonal signal correction (DOSC), have been developed to minimize the variability unrelated to the response in spectral data. In this work, these two new pre-processing methods were applied to a set of roasted coffee NIR spectra. A separate calibration model was developed to quantify the ash content and lipids in roasted coffee samples by PLS regression. The results provided by these correction methods were compared to those obtained with the original data and the data corrected by derivation, SNV and MSC. For both responses, OSC and DOSC treatments gave PLS calibration models with improved prediction abilities (4.9 and 3.3% RMSEP with corrected data versus 7.1 and 8.3% RMSEP with original data, respectively).     

Surface molecular imprinting on polypropylene fibers for rhodamine B selective adsorption

The interaction between silver nanoparticles (Ag NPs) of different surface charge and surfactants relevant to the laundry cycle has been investigated to understand changes in speciation, both in and during transport from the washing machine. Ag NPs were synthesized to exhibit either a positive or a negative surface charge in solution conditions relevant for the laundry cycle (pH 10 and pH 7). These particles were characterized in terms of size and surface charge and compared to commercially laser ablated Ag NPs. The surfactants included anionic sodium dodecylbenzenesulfonate (LAS), cationic dodecyltrimethylammoniumchloride (DTAC) and nonionic Berol 266 (Berol). Surfactant-Ag NP interactions were studied by means of dynamic light scattering, Raman spectroscopy, zeta potential, and Quartz Crystal Microbalance. Mixed bilayers of CTAB and LAS were formed through a co-operative adsorption process on positively charged Ag NPs with pre-adsorbed CTAB, resulting in charge reversal from positive to negative zeta potentials. Adsorption of DTAC on negatively charged synthesized Ag NPs and negatively charged commercial Ag NPs resulted in bilayer formation and charge reversal. Weak interactions were observed for nonionic Berol with all Ag NPs via hydrophobic interactions, which resulted in decreased zeta potentials for Berol concentrations above its critical micelle concentration. Differences in particle size were essentially not affected by surfactant adsorption, as the surfactant layer thicknesses did not exceed more than a few nanometers. The surfactant interaction with the Ag NP surface was shown to be reversible, an observation of particular importance for hazard and environmental risk assessments.     

Ion-association compounds of anionic surfactants with iron(II)chelates: Part II. Selective determination of surfactants

Homologous anionic surfactants may be separated from each other by solvent extraction of their ion-association compounds with iron(II) chelates. Separations of components from a number of surfactant mixtures were investigated, and the effect of solution variables on extraction and separation was studied. A method is proposed for the determination of surfactants of various chain lengths. Applications of this method to synthetic mixtures and to biodegradation experiments are described.     

Toxicity testing of chemicals without use of animals

A series of publications on the studies of phytotoxicity of chemicals (pollutants, ecotoxicants), carried out by the author and his research group, have been reviewed. Tests (bioassays) based on experiments with many higher plant species, both terrestrial and aquatic ones (macrophytes), were used in these studies. Among the chemicals tested there were various organic (synthetic detergents, surfactants, and pesticides) and some inorganic (e.g., metal oxide nanoparticles) compounds. New methods for bioassay using plant species never used before have been developed by the author. New facts of phytotoxicity of a synthetic detergent have been discovered and reported. Specifically, an aqueous solution of liquid detergent Frosch (Werner & Mertz, FRG) at a concentration of 0.25 mL/L (and higher concentrations) inhibited the elongation rate of seedlings of Lens culinaris higher plant species. Also, phytotoxicity of synthetic cationic surfactant dodecyltrimethylammonium bromide has been reported for the first time. This surfactant at a concentration of 4 mg/L inhibited the elongation of Lens culinaris plant seedlings. The phytotesting methods contribute to the development of alternative approaches to studying the toxicity of chemicals through non-animal testing.     

Simultaneous Spectrophotometric Determination of Uranium and Thorium Using Arsenazo III by H‐Point Standard Addition Method and Partial Least Squares Regression

Simultaneous determination of uranium and thorium using arsenazo III as a chromogenic reagent at pH 1.70 by H‐point standard addition method (HPSAM) and partial least squares (PLS) calibration is described. Under optimum conditions, the simultaneous determinations of uranium and thorium by HPSAM were performed. The absorbencies at one pair of wavelengths, 649 and 669 nm, were monitored with the addition of standard solutions of uranium. The results of applying the HPSAM showed that uranium and thorium can be determined simultaneously with weight concentration ratios of uranium to thorium varying from 20:1 to 1:15 in the mixed sample. By multivariate calibration methods such as PLS, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. In this study, the calibration model is based on absorption spectra in the 600–750 nm range for 25 different mixtures of uranium and thorium. Calibration matrices contained 0.10–21.00 and 0.25–18.5 μg mL^?1 of uranium and thorium, respectively. The RMSEP for uranium and thorium were 0.7400 and 0.7276, respectively. Both proposed methods (HPSAM and PLS) were also successfully applied to the determination of uranium and thorium in several synthetic and real matrix samples.     

Multivariate near infrared spectroscopy models for predicting methanol and water content in biodiesel

The transesterification of vegetable oils, animal fats or waste oils with an alcohol (such as methanol) in the presence of a homogeneous catalyst (sodium hydroxide or methoxyde) is commonly used to produce biodiesel. The quality control of the final product is an important issue and near infrared (NIR) spectroscopy recently appears as an appealing alternative to the conventional analytical methods. The use of NIR spectroscopy for this purpose first involves the development of calibration models to relate the near infrared spectrum of biodiesel with the analytical data. The type of pre-processing technique applied to the data prior to the development of calibration may greatly influence the performance of the model. This work analyses the effect of some commonly used pre-processing techniques applied prior to partial least squares (PLS) and principal components regressions (PCR) in the quality of the calibration models developed to relate the near infrared spectrum of biodiesel and its content of methanol and water. The results confirm the importance of testing various pre-processing techniques. For the water content, the smaller validation and prediction errors were obtained by a combination of a second order Savitsky-Golay derivative followed by mean centring prior to PLS and PCR, whereas for methanol calibration the best results were obtained with a first order Savitsky-Golay derivative plus mean centring followed by the orthogonal signal correction.     

Simultaneous determination of vitamin B12 and its derivatives using some of multivariate calibration 1 (MVC1) techniques

Resolution of binary mixtures of vitamin B12, methylcobalamin and B12 coenzyme with minimum sample pre-treatment and without analyte separation has been successfully achieved by methods of partial least squares algorithm with one dependent variable (PLS1), orthogonal signal correction/partial least squares (OSC/PLS), principal component regression (PCR) and hybrid linear analysis (HLA). Data of analysis were obtained from UV-vis spectra. The UV-vis spectra of the vitamin B12, methylcobalamin and B12 coenzyme were recorded in the same spectral conditions. The method of central composite design was used in the ranges of 10-80mgL(-1) for vitamin B12 and methylcobalamin and 20-130mgL(-1) for B12 coenzyme. The models refinement procedure and validation were performed by cross-validation. The minimum root mean square error of prediction (RMSEP) was 2.26mgL(-1) for vitamin B12 with PLS1, 1.33mgL(-1) for methylcobalamin with OSC/PLS and 3.24mgL(-1) for B12 coenzyme with HLA techniques. Figures of merit such as selectivity, sensitivity, analytical sensitivity and LOD were determined for three compounds. The procedure was successfully applied to simultaneous determination of three compounds in synthetic mixtures and in a pharmaceutical formulation.     

Fast determination of milk fat content using Raman spectroscopy

In our work, we have demonstrated the capability of VIS Raman spectroscopy in combination with partial least square regression (PLS) as a rapid technique for direct milk fat determination. Raman spectra of milk samples revealed contributions from proteins, but mainly from their fat content with different spectral characteristics. Three different methods of sample preparations were applied: (i) liquid milk contained in an open dish, (ii) dried milk droplets on glass plates covered with Al foil, and (iii) liquid milk contained in quartz cuvettes. Methods (i) and (ii) showed a good PLS model for milk fat prediction with low root mean square errors and high correlation coefficients. The main advantage of milk sample contained in the dish lies in its simplicity as well as the fact that the open container maximizes the signal of interest avoiding background contributions. Our results show that Raman spectroscopy is suited for in-line monitoring purposes.