Siti Salwa Abd Gani

Statistical Optimization of Process Parameters for Lipase-Catalyzed Synthesis of Triethanolamine-Based Esterquats Using Response Surface Methodology in 2-Liter Bioreactor

Lipase-catalyzed production of triethanolamine-based esterquat by esterification of oleic acid (OA) with triethanolamine (TEA) in n-hexane was performed in 2 L stirred-tank reactor. A set of experiments was designed by central composite design to process modeling and statistically evaluate the findings. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio of OA to TEA, and agitation speed, were studied under the given conditions designed by Design Expert software. Experimental data were examined for normality test before data processing stage and skewness and kurtosis indices were determined. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum conversion of product. Response surface methodology with central composite design gave the best performance in this study, and the methodology as a whole has been proven to be adequate for the design and optimization of the enzymatic process.

Optimization of Natural Lipstick Formulation Based on Pitaya (Hylocereus polyrhizus) Seed Oil Using D-Optimal Mixture Experimental Design

The D-optimal mixture experimental design was employed to optimize the melting point of natural lipstick based on pitaya (Hylocereus polyrhizus) seed oil. The influence of the main lipstick components—pitaya seed oil (10%–25% w/w), virgin coconut oil (25%–45% w/w), beeswax (5%–25% w/w), candelilla wax (1%–5% w/w) and carnauba wax (1%–5% w/w)—were investigated with respect to the melting point properties of the lipstick formulation. The D-optimal mixture experimental design was applied to optimize the properties of lipstick by focusing on the melting point with respect to the above influencing components. The D-optimal mixture design analysis showed that the variation in the response (melting point) could be depicted as a quadratic function of the main components of the lipstick. The best combination of each significant factor determined by the D-optimal mixture design was established to be pitaya seed oil (25% w/w), virgin coconut oil (37% w/w), beeswax (17% w/w), candelilla wax (2% w/w) and carnauba wax (2% w/w). With respect to these factors, the 46.0 °C melting point property was observed experimentally, similar to the theoretical prediction of 46.5 °C. Carnauba wax is the most influential factor on this response (melting point) with its function being with respect to heat endurance. The quadratic polynomial model sufficiently fit the experimental data.

Control strategy on the double-diffusive convection in a nanofluid layer with internal heat generation

The influences of feedback control and internal heat source on the onset of Rayleigh–Benard convection in a horizontal nanofluid layer is studied analytically due to Soret and Dufour parameters. The confining boundaries of the nanofluid layer (bottom boundary–top boundary) are assumed to be free–free, rigid–free, and rigid–rigid, with a source of heat from below. Linear stability theory is applied, and the eigenvalue solution is obtained numerically using the Galerkin technique. Focusing on the stationary convection, it is shown that there is a positive thermal resistance in the presence of feedback control on the onset of double-diffusive convection, while there is a positive thermal efficiency in the existence of internal heat generation. The possibilities of suppress or augment of the Rayleigh–Benard convection in a nanofluid layer are also discussed in detail.

Effect of Internal Heat Source on the Onset of Double-Diffusive Convection in a Rotating Nanofluid Layer with Feedback Control Strategy

A linear stability analysis has been carried out to examine the effect of internal heat source on the onset of Rayleigh–Benard convection in a rotating nanofluid layer with double diffusive coefficients, namely, Soret and Dufour, in the presence of feedback control. The system is heated from below and the model used for the nanofluid layer incorporates the effects of thermophoresis and Brownian motion. Three types of bounding systems of the model have been considered which are as follows: both the lower and upper bounding surfaces are free, the lower is rigid and the upper is free, and both of them are rigid. The eigenvalue equations of the perturbed state were obtained from a normal mode analysis and solved using the Galerkin method. It is found that the effect of internal heat source and Soret parameter destabilizes the nanofluid layer system while increasing the Coriolis force, feedback control, and Dufour parameter helps to postpone the onset of convection. Elevating the modified density ratio hastens the instability in the system and there is no significant effect of modified particle density in a nanofluid system.

The Use of D-Optimal Mixture Design in Optimising Okara Soap Formulation for Stratum Corneum Application

Okara, soybean waste from tofu and soymilk production, was utilised as a natural antioxidant in soap formulation for stratum corneum application. D-optimal mixture design was employed to investigate the influence of the main compositions of okara soap containing different fatty acid and oils (virgin coconut oil A (24–28% w/w), olive oil B (15–20% w/w), palm oil C (6–10% w/w), castor oil D (15–20% w/w), cocoa butter E (6–10% w/w), and okara F (2–7% w/w)) by saponification process on the response hardness of the soap. The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for okara soap hardness in terms of the six design factors considered in this study. Results revealed that the best mixture was the formulation that included 26.537% A, 19.999% B, 9.998% C, 16.241% D, 7.633% E, and 7.000% F. The results proved that the difference in the level of fatty acid and oils in the formulation significantly affects the hardness of soap. Depending on the desirable level of those six variables, creation of okara based soap with desirable properties better than those of commercial ones is possible.

Characterization and effect on skin hydration of engkabang-based emulsions.

Formulations containing engkabang fat and engkabang fat esters, F10 and E15 respectively were prepared using a high-shear homogenizer, followed by a high-pressure homogenizer. Both formulations were stable at room temperature, at 45 °C, and after undergoing freeze-thaw cycles. The particle sizes of F10 and E15 after high pressure were 115.75 nm and 148.41 nm respectively. The zeta potentials of F10 and E15 were −36.4 mV and −48.8 mV respectively, while, the pH values of F10 and E15 were 5.59 and 5.81 respectively. The rheology of F10 and E15 showed thixotropy and pseudoplastic behavior respectively. There were no bacteria or fungal growths in the samples. The short-term moisturizing effect on 20 subjects analyzed by analysis of variance (ANOVA), gave p-values of 7.35×10−12 and 2.77×10−15 for F10 and E15 respectively. The hydration of the skins increased after application of F10 and E15 with p-value below 0.05.

Formulation and process optimizations of nano-cosmeceuticals containing purified swiftlet nest

The good effects of swiftlet nest (SN) on the skin have been widely investigated. However, the importance of the SN in the area of nano-cosmeceutical research is still limited as it is commonly consumed, rather than being applied to the skin. Formulation and optimization processes are two important issues in the manufacturing of cosmetics. In this work, Response surface methodology (RSM) was utilized to investigate the influence of the nano-cosmeceuticals composition; purified SN (1–5% w/w), and Tween 80 (3–6% w/w) as well as the preparation method; time of homogenization (10–30 min), on the physicochemical properties of nano-cosmeceuticals. The response variables were particle size and zeta potential which were very important characteristics in nano-cosmeceuticals. Formulation and optimization of three independent variables were carried out to obtain an optimum nano-cosmeceuticals with the lowest particle size and high stability formulation. The optimized nano-emulsion containing purified SN with particle size of 136.35 nm and zeta potential of −40.2 mV was successfully formulated. This was obtained experimentally and was closer to the predicted values of 136.22 nm and −40.07 mV, respectively. The optimized formulation remained stable for three months after the centrifugation test as well as storage at different temperatures of 4 °C, 25 °C and 45 °C.

Modeling of a natural lipstick formulation using an artificial neural network

An artificial neural network (ANN) was applied in conjunction with experimental data from a mixture of experimental designs to predict the melting point of a lipstick formulation. The experimental data were utilized for training and testing the suggested model. By using the ANN performance results, the optimum parameters were found to be pitaya seed oil 25% w/w, virgin coconut oil 37% w/w, beeswax 17% w/w, candelilla wax 2% w/w, and carnauba wax 2% w/w. The relative standard error under these parameters was only 0.8772%. It was found that batch back-propagation (BBP) gave the optimal algorithm and topology with a configuration of five inputs, two hidden nodes and one output node; the most important parameter was the carnauba wax content with a relative importance of 24.5%.

Phase behavior of engkabang fat with nonionic surfactants

Abstract Phase behavior of engkabang fat was determined through the construction of ternary phase diagrams using nonionic surfactants. Several phase regions appeared in the ternary phase diagrams such as isotropic, homogenous, liquid crystal, two phase and three phase regions. The increase of hydrophilic-lipophilic balance (HLB) values of the nonionic surfactants used gave larger isotropic and homogenous region in the ternary phase diagrams. The combination of engkabang fat:Solubilisant Gamma (2:1) in the ternary phases diagram gave an even larger isotropic and homogenous regions as well as the formation of liquid crystal region.

Development of Phaleria macrocarpa (Scheff.) Boerl Fruits Using Response Surface Methodology Focused on Phenolics, Flavonoids and Antioxidant Properties

In this study, the optimal conditions for the extraction of antioxidants from the Buah Mahkota Dewa fruit (Phaleria macrocarpa) was determined by using Response Surface Methodology (RSM). The optimisation was applied using a Central Composite Design (CCD) to investigate the effect of three independent variables, namely extraction temperature (°C), extraction time (minutes) and extraction solvent to-feed ratio (% v/v) on four responses: free radical scavenging activity (DPPH), ferric ion reducing power assay (FRAP), total phenolic content (TPC) and total flavonoid content (TFC). The optimal conditions for the antioxidants extraction were found to be 64 °C extraction temperature, 66 min extraction time and 75% v/v solvent to-feed ratio giving the highest percentage yields of DPPH, FRAP, TPC and TFC of 86.85%, 7.47%, 292.86 mg/g and 3.22 mg/g, respectively. Moreover, the data were subjected to Response Surface Methodology (RSM) and the results showed that the polynomial equations for all models were significant, did not show lack of fit, and presented adjusted determination coefficients (R2) above 99%, proving that the yield of phenolic, flavonoid and antioxidants activities obtained experimentally were close to the predicted values and the suitability of the model employed in RSM to optimise the extraction conditions. Hence, in this study, the fruit from P. macrocarpa could be considered to have strong antioxidant ability and can be used in various cosmeceutical or medicinal applications.