Optimizing Nitrobenzene Synthesis Catalyzed by Sulfated Silica (SO4/SiO2) through Response Surface Methodological Approach

본 연구에서는 국산 소경 신갈나무를 이용하여 약산 전처리를 실시하고, 당으로부터 변환된 푸르푸랄 및 레불린산의 함량 변화를 평가하였다. 약산 전처리는 반응온도(<TEX>$140-180^{\circ}C$</TEX>), 반응시간(10-30분), 황산 촉매 농도(0-2%, w/w)에 따라 수행하였고, 전처리 후 액상 내 글루코오스, XMG (자일로오스 + 만노오스 + 갈락토오스), 푸르푸랄, 레불린산의 함량을 측정/분석하였다. 글루코오스는 반응온도의 상승, 반응시간과 황산 촉매 농도의 증가에 의해 그 함량이 높아져 최대 16.02%까지 나타났으나, 황산 촉매 농도 2% (반응온도 <TEX>$170^{\circ}C$</TEX> 이상, 반응시간 20분 이상)에서 함량이 감소하였다. 한편, XMG 함량은 반응온도의 영향을 크게 받았고, 반응온도와 황산 촉매 농도의 증가에 따라 1.63%까지 감소하 였으며, 반응시간의 증가에 의한 함량변화는 적었다. 푸르푸랄 함량은 반응온도, 반응시간, 황산 촉매 농도 증가에 따라 높아져 초기시료 중량 대비 최대 7.61% (반응온도 <TEX>$180^{\circ}C$</TEX>, 반응시간 20분, 1% 황산 촉매 농도)로 나타났으나, 전처리 조건이 최대 푸르푸랄 함량 조건보다 가혹해지면서 감소하는 경향이 발생하였다. 레불린산 함량은 반응온도, 반응시간, 황산 촉매 농도가 증가함에 따라 높아졌고, 특히 반응온도 <TEX>$170^{\circ}C$</TEX> 이상에서 급격한 함량 증가를 확인하였으며, 최대 10.98% (반응온도 <TEX>$180^{\circ}C$</TEX>, 반응시간 30분, 2% 황산 촉매 농도)로 나타났다. 반면 황산 촉매를 투입하지 않았을 경우 모든 반응온도, 반응시간 조건에서 푸르푸랄 및 레불린산 함량은 1% 미만으로 나타났다. In this study, dilute acid pretreatment was operated using small-diameter Quercus mongolica for evaluating the yield change of furfural and levulinic acid depending on pretreatment factors. The dilute acid pretreatment was conducted depending on reaction temperature (<TEX>$140-180^{\circ}C$</TEX>), reaction time (10-30 min), and sulfuric acid concentration (0-2%, w/w). Then, glucose, XMG (xylose + mannose + galactose), furfural, and levulinic acid contents in the liquid hydrolyzate were measured and analyzed after pretreatment. Glucose content increased to 16.02% as reaction temperature, reaction time, and sulfuric acid concentration increased, but it decreased at the sulfuric acid concentration of 2% (reaction temperature: > <TEX>$170^{\circ}C$</TEX>, reaction time: > 20 min). On the other hand, reaction temperature had a strong influenced on XMG content, and XMG content decreased to 1.63% through increasing of reaction temperature and sulfuric acid concentration, but XMG content was less affected by changes of reaction time. Furfural content increased with the increase of reaction temperature, reaction time, and sulfuric acid concentration, and maximum furfural content was 7.61% (reaction temperature: <TEX>$180^{\circ}C$</TEX>, reaction time: 20 min, sulfuric acid concentration: 1%) based on a weight of raw material, while furfural content was dropped in more severe condition than in maximum furfural content condition. Levulinic acid content also increased with higher reaction temperature, reaction time, and sulfuric acid concentration. Especially, the sharp increase of levulinic acid content was observed above <TEX>$170^{\circ}C$</TEX>, and maximum levulinic acid content was 10.98% (reaction temperature: <TEX>$180^{\circ}C$</TEX>, reaction time: 30 min, sulfuric acid concentration: 2%). However, less than 1% of furfural and levulinic acid content was obtained in non-acidic catalyst condition that in whole conditions of reaction temperature and reaction time.

Response surface optimized free radical grafting of methyl methacrylate on de-lignified rice straw for evaluating its application potential as flame retardant roofing material

Microalgal polysaccharides represent a high-value class of bioactive macromolecules with growing demand in pharmaceutical, nutraceutical, and functional food industries. Yet, inefficient and unsustainable extraction technologies severely constrain their industrial exploitation. Chlorella pyrenoidosa is a particularly attractive biomass source due to its rapid growth and high polysaccharide content, but its highly recalcitrant cell wall remains a major barrier to efficient recovery. The objective of this study was to optimize microwave-assisted extraction (MAE) conditions to maximize polysaccharide yield from Chlorella pyrenoidosa and to evaluate the effects of critical process variables using response surface methodology (RSM). Accordingly, a Box–Behnken experimental design was employed to systematically model and optimize the effects of extraction temperature, solid-to-liquid ratio, and irradiation time. Under optimized conditions (60 °C, 1:80 g/mL, 10 min), a maximum polysaccharide yield of 60.22% was achieved. The quadratic regression model exhibited excellent predictive accuracy (R² = 0.9893, p &lt; 0.05), as confirmed by ANOVA. Compared with conventional extraction methods, the optimized MAE process delivered markedly higher extraction efficiency, substantial reductions in processing time and solvent usage, and superior alignment with green chemistry principles. Collectively, this work provides a scalable and industrially relevant green extraction framework that advances the valorization of microalgal biomass and supports the transition toward sustainable biorefinery platforms.

Water contamination is emerging as the most critical global issues in the world, calling for the treatment eco-techniques. Taking advantage of biowastes as adsorbent materials is not only in accordance with the purpose of environmental protection but also enhance the higher value-added products. In this work, water hyacinth (Eichhornia crassipes) powder was used as an efficient adsorbent for the removal of crystal violet from aqueous solutions. The structure of water hyacinth powder adsorbent was characterized by Fourier transform infrared spectroscopy and scanning electron microscopy analysis. Based on the central composite rotatable design and response surface methodology, the effect of different parameters such as initial pH solution, contact time, adsorbent dosage, and initial crystal violet concentration was optimized. The maximum adsorption capacity of 180.336 mg/g was achieved under the optimum condition as initial pH solution of 6.246, contact time of 125.698 min, the adsorbent dosage of 1.382 g/L, and initial dye concentration of 615.865 mg/L. Moreover, the Langmuir isotherm provided the best fit with a high correlation coefficient of 0.9981 and a maximum monolayer adsorption capacity of 181.818 mg/g at 30 °C. The kinetic studies indicated that the pseudo-second-order model was adequately applied for the adsorption kinetic of crystal violet on the water hyacinth powder adsorbent. The utilization of the water hyacinth plant, an abundant species, as a low-cost biosorbent to remove crystal violet using the central composite rotatable design combined with response surface methodology approach is recommended for the real treatment of organic dyes.

The present work is an attempt to model the diameter of Poly Lactic-co-Glycolic Acid (PLGA) nanofibers by utilizing response surface methodology (RSM) and artificial neural networks (ANNs). Hence, determining the optimal electrospinning process conditions to produce a minimum fiber diameter. For modelling the average diameter of nanofibers, RSM approach based on four parameters (polymer concentration, high voltage and needle tip to collector distance and spinning angle) with five-level was compared to ANN technique. In the RSM approach, central composite design (CCD) was used to determine the individual and interaction impacts of the parameters on the average diameter of nanofibers. Several ANNs of single and double hidden layers with different number of cells for each were tried to obtain the best network structure. The experimental and predicted PLGA fiber diameters using an ANN showed a strong correlation, indicating that the network topology of 4-14-1 has good predictability for analyzing factors impacting PLGA fiber diameter. The average absolute relative error for predicting PLGA nanofibers’ diameter using ANN (2.24%) is slightly less than that obtained from RSM (2.59%). The high regression coefficient between the variables and the response (R2 = 0.9636) shows a good second-order polynomial regression model for evaluating experimental data. The R2 value was 0.945, indicating that the ANN model was good fitting with the experimental results. The optimum combinations (PLGA concentration of 26 wt.%, high voltage 22 kV, needle tip to collector distance 20 cm, and spinning angle 60o) were developed by RSM model for electrospinning PLGA nanofiber that can produce fine, consistent, and high-quality nanofibers.

In this research, artificial neural networks (ANN) and response surface methodology (RSM) were applied for modeling and optimization of carbon dioxide (CO2) absorption using KOH-Pz-CO2 system. In the RSM approach, the central composite design (CCD) describes the performance condition in accordance with the model using the least-squares technique. The experimental data was placed in second-order equations applying multivariate regressions and appraised applying analysis of variance (ANOVA). The p-value for all dependent variables was obtained to be less than 0.0001, indicating that all models were significant. Furthermore, the experimental values obtained for the mass transfer flux satisfactorily matched the model values. The R2 and Adj-R2 models are 0.9822 and 0.9795, respectively, which, it means that 98.22% of the variations for the NCO2 is explained by the independent variables. Since the RSM does not create any details about the quality of the solution acquired, the ANN method was applied as the global substitute model in optimization problems. The ANNs are versatile utensils that can be utilized to model and anticipate different non-linear and involved processes. This article addresses the validation and improvement of an ANN model and describes the most frequently applied experimental plans, about their restrictions and generic usages. Under different process conditions, the developed ANN weight matrix could successfully forecast the behavior of the CO2 absorption process. In addition, this study provides methods to specify the accuracy and importance of model fitting for both methodologies explained herein. The MSE values for the best integrated MLP and RBF models for the mass transfer flux were 0.00019 and 0.00048 in 100 epochs, respectively.

With the increasing depths of underground mines due to the scarcity of near-surface ores, the introduction of fibre-reinforced cemented paste backfill (F-CPB) has emerged as a novel solution to address the demanding geomechanical conditions in deep mining operations. However, the widespread adoption of F-CPB in mining and industrial backfill operations necessitates a comprehensive understanding of its key engineering properties, including strength, yield stress, modulus of elasticity, and cost. Moreover, it is crucial to investigate the influence of the constituent materials (water, fibres, binders, tailings) and their interactions on these properties. This research paper presents the application of response surface methodology (RSM) to model the effects of binder content (Portland cement/Slag), water content, fibre content, tailings and their interactions on the mechanical and rheological properties, as well as the cost of F-CPB. Central Composite Design (CCD) experiments were conducted, and a high degree of agreement was observed between the experimental and predicted responses. The RSM approach proves suitable for accurately estimating the responses and assessing the interactions between the model parameters and the properties of F-CPB. Furthermore, a combination of RSM and the desirability approach enables the development of an optimisation tool for F-CPB, facilitating the formulation of optimal backfill mixtures. The results obtained from this study highlight the effectiveness of the combined RSM and desirability approach in F-CPB mix proportioning, offering an advanced engineering approach to F-CPB mix design. The proposed design method has the potential to reduce the laboratory testing protocol required for determining the optimal mix composition.

The study aims to leach copper from a low-grade flotation middling by optimizing the leaching process using response surface methodology. The effect of key parameters, i.e., sulfuric acid concentration, nitric acid concentration and leaching time, on the leaching efficiency was investigated and a quadratic model was suggested by the methodology to correlate the variables to the efficiency. The results indicate that the model is in good agreement with the experimental data at a correlation coefficient (R2) of 0.97 and the most influential parameter on efficiency was identified as sulfuric acid concentration. The optimum conditions for copper leaching from the middling were identified as sulfuric acid concentration at 103.74 g/L, nitric acid concentration at 12.50 g/L and leaching time of 30.98 min; under such a condition, an average leaching efficiency of 93.16% was achieved from the middling

Spent coffee grounds (SCG) are one of the lignocellulosic biomasses that have gained much attention due to their high potential both in valorization and biomethane production. Previous studies have reported single processes that extract either fatty acids/lignin or biogas. In this study, an integrated physicochemical and biological process was investigated, which sequentially recovers lignin, fatty acid methyl esters (FAME) and biogas from the residue of SCG. The determination of optimal conditions for sequential separation was based on central composite design (CCD) and response surface methodology (RSM). Independent variables adopted in this study were reaction temperature (86.1–203.9 °C), concentration of sulfuric acid (0.0–6.4%v/v) and methanol to SCG ratio (1.3–4.7 mL/g). Under determined optimal conditions of 161.0 °C, 3.6% and 4.7 mL/g, lignin and FAME yields were estimated to be 55.5% and 62.4%, respectively. FAME extracted from SCG consisted of 41.7% C16 and 48.16% C18, which makes the extractives appropriate materials to convert into biodiesel. Results from Fourier transform infrared spectroscopy (FT-IR) further support that lignin and FAME extracted from SCG have structures similar to previously reported extractives from other lignocellulosic biomasses. The solid residue remaining after lignin and FAME extraction was anaerobically digested under mesophilic conditions, resulting in a methane yield of 36.0 mL-CH4/g-VSadded. This study is the first to introduce an integrated resource recovery platform capable of valorization of a municipal solid waste stream.

This study posits that strategically optimizing irrigation and fertilization regimes can enhance the productivity and water use efficiency (WUE) of alfalfa (Medicago sativa L.), thereby mitigating the constraints imposed by soil impoverishment and water scarcity in forage production systems of arid and semi-arid regions. Conducted over two years, the outdoor pot experiment investigated the effects of water regulation during the branching and bud stages (each at 60-100% θ0.85, where θ0.85 = 0.85θfc) and different levels of nitrogen and phosphorus fertilization (0-280 kg/ha each) on alfalfa yield and WUE. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), we modeled the relationships between input variables and key response parameters: total yield, evapotranspiration (ET), and WUE. The response surface models exhibited high reliability, with coefficients of determination R2, adjusted R2, predicted R2, and adequate precision exceeding 0.94, 0.90, 0.86, and 13.6, respectively. Sensitivity analysis indicated that water regulation during critical growth stages, particularly the branching stage, had the most significant impact on yield and ET, while nitrogen and phosphorus fertilization positively influenced WUE. Within the appropriate range of water management, judicious fertilization significantly enhanced alfalfa production performance, although excessive inputs resulted in diminishing returns. This study identified the optimal conditions for sustainable production: branching stage water regulation (82.26-83.12% θ0.85) and bud stage water regulation (78.11-88.47% θ0.85), along with nitrogen application (110.59-128.88 kg/ha) and phosphorus application (203.86-210 kg/ha). These findings provide practical guidelines for improving the sustainability and efficiency of alfalfa production in resource-limited environments.

Objectives : This study evaluated and identified the removal of colors and chemocal oxygen demands from thextile dye effluents by Bacillus cereus isolated from the local textile wastewater treatment plant.Methods : Central composite design (CCD) from response surface methodology (RSM) was applied in order to achieve the optimized treatment process condition for the textile dyes wastewater degradation. Two-level of three process parameters with six center points resulted a total of twenty runs of experiments were performed. Bacterial inoculum (-1,+1) (%, v/v), agitation (-1, +1) (rpm), and pH (-1, +1) were tested.Results and Discussion : During the ten days of biodegradation process, highest decolourization achieved was 88.67% with low pH and agitation; and medium level of initial concentration of bacterial inoculum. Highest chemical oxygen demand (COD) removal was achieved with 99.20% from high pH (pH 10), low agitation (100 rpm) and high initial concentration of bacterial inoculum (15%, v/v).Conclusions : The biological treatments was able to remove colour and chemical oxygen demand with application of CCD, giving the optimum settings of the three process parameters studied.

Nanocellulose is one of the most significant nanomaterials that can be derived from lignocellulosic materials. The properties of nanocellulose make it a promising material for a variety of applications, including paper and paperboard production, antibacterial agents, coatings, cosmetics, drug delivery, soft tissue transplant, blood vessel replacements, and others. This study focuses on the extraction of nanocellulose from teff straw, which is an agricultural residue and locally available in Ethiopia. Nanocellulose was extracted by acid-chlorite delignification, alkali, and acid hydrolysis method. The effect of acid hydrolysis process parameters, sulfuric acid concentration, time, and the temperature was studied using response surface methodology. The central composite design was used to screen and adjust the design matrix with three factors and five levels. The optimum yield was 62.2% when acid concentration, time, and temperature were 44.4%v/v, 32 min, and 40.5 ° C respectively. The Analysis of variance (ANOVA) was carried out to identify the most significant factors that influence the percentage of nanocellulose yield. The Fourier-transform infrared (FTIR) result confirms the reduction and total removal of lignin, and the amorphous parts in straw. The average particle size determined by dynamic light scattering (DLS) was 101.6 nm with a polydispersity index of 0.047. From the X-ray diffractometer (XRD) result crystallinity index of straw and nano-cellulose was 47.7% and 77.1% respectively. The thermogravimetry analysis demonstrates the maximum temperature of nanocellulose and cellulose was 270 °C and 360 °C respectively. The Scanning electron microscopy (SEM) result implies the surface of nano-cellulose was improved by the chemical treatments.

This work is an effort to remediate rice grain-based biodigester effluent (BDE) by applying the sono-electrocoagulation (SEC) process using Iron as a sacrificial electrode to accomplish this process. A batch reactor is used for the investigation. The effect of the SEC process on the reduction of chemical oxygen demand (COD) and color from the wastewater was studied by varying operating parameters including ultrasonic power (U), current density (j), initial pH (pHi), and electrolysis time (t) in the ranges of 20-60 W, 49.5-247.5 A/m2, 2-10 and 12-60 minutes respectively. The results obtained were optimized by using central composite design (CCD) which is a special feature of the response surface method (RSM). This tool is well applicable in the SEC process to explores the relationships between different varying operating parameters with two responses namely COD and color removal efficiency. The RSM is to use a sequence of designed experiments to obtain an optimal response. The analysis demonstrated that the quadratic regression model fitted well with SEC-generated data. Moreover, no significant difference was found between experimental and predicted data. The coefficient of determination (R2) of 0.9995 and 0.9895 were observed for COD and color removal efficiency. Results indicated that the COD removal efficiency of 93% and color removal efficiency of 88% were found at optimum conditions U of 50, J of 198 A/m2, pHi of 7, and t of 48 minutes.

Safflower seed oil reveals well known therapeutic values. Response surface methodology (RSM), an effective statistical tool was used to study the enhancement of its oil percentage. A central composite design was applied to evaluate effects of four independent parameters like seed amount, reaction time, volume of hexane and temperature on oil extraction from its seeds. Oil percentage has been estimated as 22.76%, 21.73% and 25.1% respectively after thermal pretreatment for 10, 20 and 30 min. The optimized parameters were obtained as 3 g for the amount of seeds, 30 min for extraction process, 30 ml for volume of hexane and 45 °C temperature after applying RSM. The predicted oil percentage was obtained as 31.968% by second order polynomial equation while the estimated oil percentage was 50.12% for the optimum parameters. The oil percentage has been enhanced almost two times by using RSM. Statistically, the optimization of extraction parameters for the maximum oil recovery may add a positive value in the safflower crop with world economy.

In this work, thealkaline roasting and sulfuric acid leaching processes were employed to extract vanadium from the magnetite ore of Saghand mine in central Iran. The response surface methodology based on the central composite design model was applied to optimize the parameters involved in the processes. The studied roasting parameters were temperature (900-1100 °C), sodium carbonate percentage (30-50 wt%), and time (1-3 h). In addition, the studied leaching factors included temperature (70-90 °C), liquid-to-solid ratio (L/S) (5-20 mL/g), sulfuric acid concentration (2-6 M), and time (3-6 h). Under the optimal conditions, the values for temperature, time, and sodium carbonate amounted to 1010 °C, 2.1 h, and 41 wt%, respectively, for the roasting process, while the values for temperature, L/S, sulfuric acid concentration, and time for the leaching process were estimated to be 85 °C, 12.4 mL/g, 4.25 M, and 4.7 h, respectively. Under these conditions, about 83.8 ± 0.9% of vanadium was leached from the magnetite ore.