Response Surface Methodology as a Useful Tool for Evaluation of the Recovery of the Fluoroquinolones from Plasma—The Study on Applicability of Box-Behnken Design, Central Composite Design and Doehlert Design

Magnetic Hydrogel Beads as a Reusable Adsorbent for Highly Efficient and Rapid Removal of Aluminum: Characterization, Response Surface Methodology Optimization, and Evaluation of Isotherms, Kinetics, and Thermodynamic Studies

Biopolymers such as alginate and gelatin have attracted much attention because of their exceptional adsorption properties and biocompatibility. The magnetic hydrogel beads produced and used in this study had a core structure composed of magnetite nanoparticles and gelatin and a shell structure composed of alginate. The combination of the metal-ion binding ability of alginate and the mechanical strength of gelatin in magnetic hydrogel beads presents a new approach for the removal of metal from water sources. The beads were designed for aluminum removal and fully characterized using various methods, including Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy-energy-dispersive X-ray spectroscopy, vibrating sample magnetometry, microcomputed tomography, and dynamic mechanical analysis. Statistical experimental designs were employed to optimize the parameters of the adsorption and recovery processes. Plackett-Burman Design, Box-Behnken Design, and Central Composite Design were used for identifying the significant factors and optimizing the parameters of the adsorption and recovery processes, respectively. The optimum parameters determined for adsorption are as follows: pH: 4, contact time: 30 min, adsorbent amount: 600 mg; recovery time: reagent 1 M HNO3; and contact time: 40 min. The adsorption process was described by using the Langmuir isotherm model. It reveals a homogeneous bead surface and monolayer adsorption with an adsorption capacity of 5.25 mg g-1. Limit of detection and limit of quantification values were calculated as 4.3 and 14 μg L-1, respectively. The adsorption process was described by a pseudo-second-order kinetic model, which assumes that chemisorption is the rate-controlling mechanism. Thermodynamic studies indicate that adsorption is spontaneous and endothermic. The adsorbent was reusable for 10 successive adsorption-desorption cycles with a quantitative adsorption of 98.2% ± 0.3% and a recovery of 99.4% ± 2.6%. The minimum adsorbent dose was determined as 30 g L-1 to achieve quantitative adsorption of aluminum. The effects of the inorganic ions were also investigated. The proposed method was applied to tap water and carboy water samples, and the results indicate that magnetic hydrogel beads can be an effective and reusable bioadsorbent for the detection and removal of aluminum in water samples. The recovery values obtained by using the developed method were quantitative and consistent with the results obtained from the inductively coupled plasma optical emission spectrometer.

Microalgae to Bioenergy: Optimization of Aurantiochytrium sp. Saccharification

Microalgae are a promising feedstock for bioethanol production, essentially due to their high growth rates and absence of lignin. Hydrolysis-where the monosaccharides are released for further fermentation-is considered a critical step, and its optimization is advised for each raw material. The present study focuses on the thermal acid hydrolysis (with sulfuric acid) of Aurantiochytrium sp. through a response surface methodology (RSM), studying the effect of acid concentration, hydrolysis time and biomass/acid ratio on both sugar concentration of the hydrolysate and biomass conversion yield. Preliminary studies allowed to establish the range of the variables to be optimized. The obtained models predicted a maximum sugar concentration (18.05 g/L; R² = 0.990) after 90 min of hydrolysis, using 15% (w/v) biomass/acid ratio and sulfuric acid at 3.5% (v/v), whereas the maximum conversion yield (12.86 g/100 g; R² = 0.876) was obtained using 9.3% (w/v) biomass/acid ratio, maintaining the other parameters. Model outputs indicate that the biomass/acid ratio and time are the most influential parameters on the sugar concentration and yield models, respectively. The study allowed to obtain a predictive model that is very well adjusted to the experimental data to find the best saccharification conditions for the Aurantiochytrium sp. microalgae.

The Chemometric Evaluation of the Factors Influencing Cloud Point Extraction for Fluoroquinolones

This study aimed to analyze the factors that impact the cloud point extraction of ciprofloxacin, levofloxacin, and moxifloxacin. The following independent variables were analyzed: Triton X-114 concentration, NaCl concentration, pH, and incubation temperature. The dependent variable studied was recovery. A central composite design model was used. The applied quantitation method was HPLC. The method was validated for linearity, precision, and accuracy. The results underwent ANOVA^® analysis. The polynomial equations were generated for each analyte. The response surface methodology graphs visualized them. The analysis showed that the factor most affecting the recovery of levofloxacin is the concentration of Triton X-114, while the recovery of ciprofloxacin and moxifloxacin is most affected by pH value. However, the concentration of Triton X-114 also plays an important role. The optimization resulted in the following recoveries: for ciprofloxacin, 60%; for levofloxacin, 75%; and for moxifloxacin, 84%, which are identical to those estimated with regression equations-59%, 74% and 81% for ciprofloxacin, levofloxacin, and moxifloxacin, respectively. The research confirms the validity of using the model to analyze factors affecting the recovery of the analyzed compounds. The model allows for a thorough analysis of variables and their optimization.

Conversion of Free Fatty Acid in Calophyllum inophyllum Oil to Fatty Acid Ester as Precursor of Bio-Based Epoxy Plasticizer via SnCl2-Catalyzed Esterification

The preparation and application of bio based plasticizers derived from vegetable oils has gained increasing attention in the polymer industry to date due to the emerging risk shown by the traditional petroleum-based phthalate plasticizer. Epoxy fatty acid ester is among the prospective alternative plasticizers since it is ecofriendly, non-toxic, biodegradable, low migration, and low carbon footprint. Epoxy plasticizer can be synthesized by the epoxidation reaction of fatty acid ester. In this study, the preparation of fatty acid ester as a green precursor of epoxy ester plasticizer was performed via esterification of free fatty acid (FFA) in high acidic Calophyllum inophyllum Seed Oil (CSO) using methanol in the presence of SnCl₂.2H₂O catalyst. The analysis of the process variables and responses using Box-Behnken Design (BBD) of Response Surface Methodology (RSM) was also accomplished. It was found that the quadratic model is the most appropriate model for the optimization process. The BBD analysis demonstrated that the optimum FFA conversion and residual FFA content were 75.03% and 4.59%, respectively, achieved at the following process condition: a reaction temperature of 59.36 °C, a reaction time of 117.80 min, and a catalyst concentration of 5.61%. The fatty acid ester generated was an intermediate product which can undergo a further epoxidation process to produce epoxy plasticizer in polymeric material production.

Maximization of growth and lipid production of a toxic isolate of Anabaena circinalis by optimization of various parameters with mathematical modeling and computational validation

Toxic cyanobacterial blooms are recurrent for few decades throughout the globe, due to climate change, atmospheric warming and various anthropogenic activities with severe impacts of potential toxins on various ecosystems finally affecting the entire environment. These cyanobacteria are merely unexplored regarding their biochemical components except toxins. Variable influences and interactions of different factors including nitrogen, carbon, and availability of light are well known to crucially regulate cyanobacterial growth and metabolism. Thus, current research work is motivated for the evaluation and optimization of the effects of the aforementioned vital factors for improvement of biomass and lipid production of a freshwater, toxic strain of Anabaena circinalis. The modelling and optimization of factors such as nitrogen, light intensity and bicarbonate concentration (source of carbon) to maximize growth and lipid production were based on 20 design point experiments by Response Surface Methodology (RSM) and optimized values were further improved and validated by Particle Swarm Optimization (PSO) algorithm. The maximum optima were obtained 1.829 g L^-1 and 39.64 % for biomass production and lipid content respectively from PSO optimization with two different sets of optimal values of factors. It shows 0.44 % and 2.77 % higher values of responses than that of RSM optimization. These asynchronous findings pioneered the enhanced lipid accumulation as well as the growth of a toxic cyanobacterium by optimizing interaction effects of culture conditions through various statistical and computational approaches.

Modeling and Optimization of β-Galactosidase Entrapping in Polydimethylsiloxane-Modified Silica Composites

Protein entrapment has multiple applications in enzymatic hydrolysis, drug delivery, etc. Here, we report the studies that successfully utilized the Box–Behnken design to model and optimize the parameters of β-galactosidase entrapment in sol–gel-derived silica composites. We have also demonstrated the influence of polymer–polydimethylsiloxane as a composite modifying agent on the activity of entrapped enzymes. We have determined how different sol-gel process parameters influence the activity of entrapped enzymes. The highest impact on β-galactosidase activity was exerted by the water:tetramethoxysilane ratio, followed by polydimethylsiloxane content. Optimized synthesis parameters have been utilized to obtain a composite with maximum β-galactosidase activity. Performed porosity studies have shown that the addition of polydimethylsiloxane increased the pore diameter. Microscopy studies demonstrated that polydimethylsiloxane-modified composites are softer and less rough. Studies of β-galactosidase activity using the o-NPG test showed statistically significant shifts in the enzyme temperature and pH profiles compared to the soluble form. An improvement in the reusability of the enzyme and a significant increase in the thermal stability was also observed. When lactose was used, a strong correlation was observed between the substrate concentration and the type of the catalyzed reaction. Moreover, we have demonstrated that the yields and rates of both lactose hydrolysis and galactooligosaccharides formation were correlated with reaction temperature and with the presence of polydimethylsiloxane. All these findings provide the opportunity for industrial use of optimized PDMS-modified silica composites in lactose elimination from dairy products, e.g., milk or whey.

Rice Husk Ash-Based Geopolymer Binder: Compressive Strength, Optimize Composition, FTIR Spectroscopy, Microstructural, and Potential as Fire-Retardant Material

Compressive strength is an important property in construction material, particularly for thermal insulation purposes. Although the insulation materials possess high fire-retardant characteristics, their mechanical properties are relatively poor. Moreover, research on the correlation between fire-retardant and compressive strength of rice husk ash (RHA)-based geopolymer binder (GB) is rather limited. In addition, previous studies on RHA-based GB used the less efficient one-factor-at-a-time (OFAT) approach. In understanding the optimum value and significant effect of factors on the compressive strength, it was deemed necessary to employ statistical analysis and a regression coefficient model (mathematical model). The objective of the study is to determine the effect of different material behavior, namely brittle and ductile, on the compressive strength properties and the optimum material formulation that can satisfy both compressive strength and fire-retardant properties. The factors chosen for this study were the rice husk ash/activated alkaline solution (RHA/AA) ratio and the sodium hydroxide (NaOH) concentration. Compressive strength and fire-retardant tests were conducted as part of the experiments, which were designed and analyzed using the response surface methodology (RSM). The microstructure of geopolymer samples was investigated using a scanning electron microscope (SEM). Results showed that RHA/AA ratio was highly significant (p < 0.000) followed by NaOH concentration (p < 0.024). When the RHA/AA ratio was at 0.7 to 0.8 and the NaOH concentration was between 12 and 14 M, high compressive strength above 28 MPa was recorded. Optimum compressive strength of approximately 47 MPa was achieved when the RHA/AA ratio and NaOH concentration were 0.85 and 14 M, respectively. Brittle samples with low Si/Al ratio of 88.95 were high in compressive strength, which is 33.55 MPa, and showed a high degree of geopolymerization. Inversely, ductile samples showed low compressive strength and degree of geopolymerization. Water content within the geopolymer binder had a major effect on its fire-retardant properties. Semi-ductile GB showed the best fire-retardant properties, followed by semi-brittle and brittle GB. Using RHA as an aluminosilicate source has proven to be a promising alternative.

Rice-Husk-Ash-Based Geopolymer Coating: Fire-Retardant, Optimize Composition, Microstructural, Thermal and Element Characteristics Analysis

Geopolymer using aluminosilicate sources, such as fly ash, metakaolin and blast furnace slag, possessed excellent fire-retardant properties. However, research on the fire-retardant properties and thermal properties of geopolymer coating using rice husk ash (RHA) is rather limited. Additionally, the approach adopted in past studies on geopolymer coating was the less efficient one-factor-at-a-time (OFAT). A better approach is to employ statistical analysis and a regression coefficient model (mathematical model) in understanding the optimum value and significant effect of factors on fire-retardant and thermal properties of the geopolymer coating. This study aims to elucidate the significance of rice husk ash/activated alkaline solution (RHA/AA) ratio and NaOH concentration on the fire-retardant and thermal properties of RHA-based geopolymer coating, determine the optimum composition and examine the microstructure and element characteristics of the RHA-based geopolymer coating. The factors chosen for this study were the RHA/AA ratio and the NaOH concentration. Rice husk was burnt at a temperature of approximately 600 °C for 24 h to produce RHA. The response surface methodology (RSM) was used to design the experiments and conduct the analyses. Fire-retardant tests and thermal and element characteristics analysis (TGA, XRD, DSC and CTE) were conducted. The microstructure of the geopolymer samples was investigated by using a scanning electron microscope (SEM). The results showed that the RHA/AA ratio had the strongest effect on the temperature at equilibrium (TAE) and time taken to reach 300 °C (TT300). For the optimization process using RSM, the optimum value for TAE and TT300 could be attained when the RHA/AA ratio and NaOH concentration were 0.30 and 6 M, respectively. SEM micrographs of good fire-resistance properties showed a glassy appearance, and the surface coating changed into a dense geopolymer gel covered with thin needles when fired. It showed high insulating capacity and low thermal expansion; it had minimal mismatch with the substrate, and the coating had no evidence of crack formation and had a low dehydration rate. Using RHA as an aluminosilicate source has proven to be a promising alternative. Using it as coating materials can potentially improve fire safety in the construction of residential and commercial buildings.

Talib R, Zakaria R, Kamarudin SH. Novel Mangosteen-Leaves-Based Marker Ink: Color Lightness, Viscosity, Optimized Composition, and Microstructural Analysis

Dry mangosteen leaves are one of the raw materials used to produce marker ink. However, research using this free and abundant resource is rather limited. The less efficient one-factor-at-a-time (OFAT) approach was mostly used in past studies on plant-based marker ink. The use of statistical analysis and the regression coefficient model (mathematical model) was considered essential in predicting the best combination of factors in formulating mangosteen leaf-based marker ink. Ideally, ink should have maximum color lightness, minimum viscosity, and fast-drying speed. The objective of this study to study the effect of glycerol and carboxymethyl cellulose (CMC) on the color lightness and viscosity of mangosteen-leaves-based marker ink. The viscosity, color lightness, and drying properties of the ink were tested, the significant effect of glycerol and CMC (responses) on ink properties was identified and the prediction model on the optimum value of the responses was developed by using response surface methodology (RSM). The microstructure of mangosteen leaves was analyzed to study the surface morphology and cell structure during dye extraction. A low amount of glycerol used was found to increase the value of color lightness. A decrease in CMC amounts resulted in low viscosity of marker ink. The optimum formulation for the ink can be achieved when the weight percents of glycerol, benzalkonium chloride, ferrous sulphate, and CMC are set at 5, 5, 1, and 3, respectively. SEM micrographs showed the greatest amount of cell wall structure collapse on samples boiled with the lowest amount of glycerol.

A New Approach for Design Optimization and Parametric Analysis of Symmetric Compound Parabolic Concentrator for Photovoltaic Applications

A compound parabolic concentrator (CPC) is a non-imaging device generally used in PV, thermal, or PV/thermal hybrid systems for the concentration of solar radiation on the target surface. This paper presents the geometric design, statistical modeling, parametric analysis, and geometric optimization of a two-dimensional low concentration symmetric compound parabolic concentrator for potential use in building-integrated and rooftop photovoltaic applications. The CPC was initially designed for a concentration ratio of “2×” and an acceptance half-angle of 30°. A MATLAB code was developed in house to provoke the CPC reflector’s profile. The height, aperture width, and concentration ratios were computed for different acceptance half-angles and receiver widths. The interdependence of optical concentration ratio and acceptance half-angle was demonstrated for a wide span of acceptance half-angles. The impact of the truncation ratio on the geometric parameters was investigated to identify the optimum truncation position. The profile of truncated CPC for different truncation positions was compared with full CPC. A detailed statistical analysis was performed to analyze the synergistic effects of independent design parameters on the responses using the response surface modeling approach. A set of optimized design parameters was obtained by establishing specified optimization criteria. A 50% truncated CPC with an acceptance half-angle of 21.58° and receiver width of 193.98 mm resulted in optimum geometric dimensions.

Talib R, Mohamed Amin Tawakkal IS, Kamarudin SH, Mazlan N, Maidin NA, Ab Rahman MH. Rice Husk Ash/Silicone Rubber-Based Binary Blended Geopolymer Coating Composite: Fire Retardant, Moisture Absorption, Optimize Composition, and Microstructural Analysis

Geopolymer coating using rice husk ash (RHA) as the aluminosilicate source has shown excellent fire retardant properties. However, incorporation of rice husk ash into the geopolymer matrix increased water absorption properties of the polymer composite. As such, silicone rubber (SiR) was introduced to improve the moisture absorption and fire retardant properties of the composite. Additionally, the less efficient one-factor-at-a-time (OFAT) approach was conventionally used in past studies on the RHA-based geopolymer composite. In understanding the optimum value and significant effect of factors on the fire retardant and moisture absorption properties of the binary blended geopolymer coating composite, the use of statistical analysis and regression coefficient model (mathematical model) was considered essential. The objectives of this study are to identify the significant effect of factors on moisture absorption and fire retardant properties, to determine the optimum composition, and to study the microstructure of the rice husk ash/silicone rubber (RHA/SiR)-based binary blended geopolymer coating composite. The RHA/AA and SiR/Ge ratios were chosen as factors, and the response surface methodology (RSM) was employed to design experiments and conduct analyses. Fire retardant and moisture absorption tests were conducted. A scanning electron microscope (SEM) was used to observe the microstructure of geopolymer samples. The RHA/alkaline activator (AA) and SiR/Ge ratios were shown to have a significant effect on the responses (temperature at equilibrium and moisture absorption). The high ratio of RHA/AA and SiR/Ge resulted in a lower temperature at equilibrium (TAE) below 200°C and at moisture absorption below 16%. The optimum formulation for the geopolymer coating composite can be achieved when the RHA/AA ratio, SiR/Ge ratio, and sodium hydroxide concentration are set at 0.85, 0.70, and 14 M, respectively. SEM micrographs of samples with good fire retardant properties showed that the char residue of the geopolymer composite coating, which is a layer of excess silicone rubber, is porous and continuous, thus providing a shielding effect for the layer of geopolymer underneath. The sample with good moisture absorption showed the formation of a thin outer layer of silicone rubber without any cracks. The unreacted SiR formed a thin layer beneath the geopolymer composite matrix providing a good moisture barrier.

Optimization of Adhesion Strength and Microstructure Properties by Using Response Surface Methodology in Enhancing the Rice Husk Ash-Based Geopolymer Composite Coating

As a result of their significant importance and applications in vast areas, including oil and gas, building construction, offshore structures, ships, and bridges, coating materials are regularly exposed to harsh environments which leads to coating delamination. Therefore, optimum interfacial bonding between coating and substrate, and the reason behind excellent adhesion strength is of utmost importance. However, the majority of studies on polymer coatings have used a one-factor-at-a-time (OFAT) approach. The main objective of this study was to implement statistical analysis in optimizing the factors to provide the optimum adhesion strength and to study the microstructure of a rice husk ash (RHA)-based geopolymer composite coating (GCC). Response surface methodology was used to design experiments and perform analyses. RHA/alkali activated (AA) ratio and curing temperature were chosen as factors. Adhesion tests were carried out using an Elcometer and a scanning electron microscope was used to observe the microstructure. Results showed that an optimum adhesion strength of 4.7 MPa could be achieved with the combination of RHA/AA ratio of 0.25 and curing temperature at 75 °C. The microstructure analysis revealed that coating with high adhesion strength had good interfacial bonding with the substrate. This coating had good wetting ability in which the coating penetrated the valleys of the profiles, thus wetting the entire substrate surface. A large portion of dense gel matrix also contributed to the high adhesion strength. Conversely, a large quantity of unreacted or partially reacted particles may result in low adhesion strength.

Optimization for Liquid-Liquid Extraction of Cd(II) over Cu(II) Ions from Aqueous Solutions Using Ionic Liquid Aliquat 336 with Tributyl Phosphate

This study investigates the separation of two heavy metals, Cd(II) and Cu(II), from the mixed synthetic feed using a liquid-liquid extraction. The current study uses tri-octyl methylammonium chloride (Aliquat 336) as the extractant (with tributyl phosphate (TBP) as a phase modifier), diluted in toluene, in order to investigate the selective extraction of Cd(II) over Cu(II) ions. We investigate the use of ethylenediaminetetraacetic acid (EDTA) as a masking agent for Cu(II), when added in aqueous feed, for the selective extraction of Cd(II). Five factors that influence the selective extraction of Cd(II) over Cu(II) (the equilibrium pH (pH_eq), Aliquat 336 concentration (Aliquat 336), TBP concentration (TBP), EDTA concentration (EDTA), and organic to aqueous ratio (O:A)) were analyzed. Results from a 2^5–1 fractional factorial design show that Aliquat 336 significantly influenced Cd(II) extraction, whereas EDTA was statistically significant for the antagonistic effect on the E% of Cu(II) in the same system. Moreover, results from optimization experiment showed that the optimum conditions are Aliquat 336 concentration of 99.64 mM and EDTA concentration of 48.86 mM—where 95.89% of Cd(II) was extracted with the least extracted Cu(II) of 0.59%. A second-order model was fitted for optimization of Cd(II) extraction with a R² value of 0.998, and ANOVA results revealed that the model adequately fitted the data at a 5% significance level. Interaction between Aliquat 336 and Cd(II) has been proven via FTIR qualitative analysis, whereas the addition of TBP does not affect the extraction mechanism.

Optimizing the Processing Factor and Formulation of Oat-Based Cookie Dough for Enhancement in Stickiness and Moisture Content Using Response Surface Methodology and Superimposition

Despite the utilization of dusting flour and oil to reduce dough stickiness during the production process in food industry, they do not effectively help in eliminating the problem. Stickiness remains the bane of the production of bakery and confectionery products, including cookies. In addition, the high moisture content of cookie dough is unduly important to obtain a high breaking and compression strengths (cookies with high breaking tolerance). This study was conducted in light of insufficient research hitherto undertaken on the utilization of response surface methodology and superimposition to enhance the stickiness and moisture content of quick oat-based cookie dough. The study aims at optimizating, validating and superimposing the best combination of factors, to produce the lowest stickiness and highest moisture content in cookie dough. In addition, the effect of flour content and resting time on the stickiness and moisture content of cookie dough was also investigated, and microstructure analysis conducted. The central composite design (CCD) technique was employed and 39 runs were generated by CCD based on two factors with five levels, which comprised flour content (50, 55, 60, 65, and 70%), resting time (10, 20, 30, 40, and 50 min) and three replications. Results from ANOVA showed that all factors were statistically significant at p < 0.05. Flour content between 56% and 62%, and resting time within 27 and 50 min, resulted in dough with high stickiness. High-region moisture content was observed for flour content between 60% and 70%, and within 10 and 15 min of resting time. The optimized values for flour content (V1) = 67% and resting time (V2) = 10 min. The predicted model (regression coefficient model) was found to be accurate in predicting the optimum value of factors. The experimental validation showed the average relative deviation for stickiness and moisture content was 8.54% and 1.44%, respectively. The superimposition of the contour plots was successfully developed to identify the optimum region for the lowest stickiness and highest moisture content which were at 67–70% flour content and 10–15 min resting time.