• Applied Chemistry for Engineering
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• v.32 no.2
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• pp.168-173
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• 2021

In this study, we measured total flavonoids after extracting the total flavonoids from lemongrass which is known to have a high content of antioxidant ingredients when using microwave energy. Also, optimal extraction conditions of active ingredients using central composite design-response surface methodology (CCD-RSM) were presented. Both ultrapure water and alcohol were used as extraction solvents and the volume ratio of ethanol/ultrapure water, microwave irradiation time, and microwave irradiation power were set as independence variables. And the extraction yield and total flavonoids were measured. The optimal extraction conditions using CCD-RSM were the volume ratio of ethanol/ultrapure water = 56.3 vol.%, the microwave irradiation time = 6.1 min, and the microwave irradiation power = 574.6 W. We could also obtain expected results of yield = 17.2 wt.% and total flavonoids = 44.7 ㎍ QE/mL dw under the optimum conditions. The comprehensive satisfaction degree of this formula was 0.8562. The P-value was calculated for the yield of 0.037 and the total flavonoids content of 0.002. The average error from actual experiments established for the verification of conclusions was lower than 2.5%. Therefore, a high favorable level could be obtained when the CCD-RSM was applied to the optimization of extraction process.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.8-13
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• 2015

The experimental design methodology was applied in the drop tube furnace (DTF) to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of DTF. The dependent variables such as burnout ratios (BOR) of coal and $CO/CO_2$ ratios were mathematically described as a function of three independent variables (coal particle size, carrier gas flow rate, wall temperature) being modeled by the use of the central composite design (CCD), and evaluated using a second-order polynomial multiple regression model. The prediction of BOR showed a high coefficient of determination (R2) value, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the simulation data. However, $CO/CO_2$ ratio had a big difference between calculated values and predicted values using conventional RSM, which might be mainly due to the dependent variable increses or decrease very steeply, and hence the second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, $CO/CO_2$ ratio was taken as common logarithms and worked again with RSM. The application of logarithms in the transformation of dependent variables showed that the accuracy was highly enhanced and predicted the simulation data well.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.1
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• pp.48-56
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• 2018

Due to the growing concerns of energy resource depletion and environmental destruction, the mass production of microalgae has been studied. The scale-up of a photobioreactor (PBR) is required for the mass production of biomass. In this paper, the geometric parameters and oxygen transfer rate (OTR) are considered, to scale up a flat panel photobioreactor (FP PBR). The PBR is designed using the goal-driven optimization (GDO) method to accomplish the scale-up. The local sensitivity of each output parameter with respect to the input parameter is analyzed through the design of experiment (DOE), and the design candidates are evaluated with the screening sampling method. The volumetric mass transfer coefficient is measured by the dynamic method.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.10
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• pp.568-574
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• 2017

The purpose of this study was to optimize experimental conditions (time ($X_1$) (ranging of 26.36 - 93.64 min), concentration of sulfuric acid ($X_2$) (ranging of 0-2.5%) and temperature ($X_3$) (ranging of $136.4-203.6^{\circ}C$) for an organosolv pretreatment process to extract lignin from waste wood. The resulting quadratic model equation using RSM (response surface methodology) represented y (lignin yield) = $-79.89+0.91X_1+9.8X_2-2.54{\times}10^{-3}X_1{^2}-2.11X_2{^2}$. The $R^2$ (coefficient of determination) value of 0.8531 for a model indicates this model has statistically significant predictors at the 10% levels. The predictive results optimized by quadratic model produced a lignin yield of 12.46 g/100 g of dry wood under conditions of $178.2^{\circ}C$ and 2.32% $H_2SO_4$. The lignin yield was more affected by the acid catalyst concentrations than the reaction temperature, but the reaction time was not an influential factor for improving lignin extraction from waste wood in this organosolv pretreatment. According to ANOVA (analysis of variance), the significance probability (p-value) of model was smaller than 0.001 and simulation of obtained model equations showed a good reproducibility based on actual organosolv tests under optimal conditions.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.320-325
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• 2021

In this study, an optimization for the production of water emulsion was designed by adding an extract of wheat sprout, which is known to contain a large amount of antioxidants. The central composite design of reaction surface analysis method (CCD-RSM) was used for the optimization process. The amount of emulsifier, emulsification time, and added amount of wheat sprout extract were selected as independent variables based on our preliminary experiments. The mean droplet size (MDS), viscosity, and emulsion stability index (ESI) were set as the responses to evaluate the stability of the emulsion. For each independent variable, the P-value and coefficient of determination were evaluated to verify the reliability of the experiments. From the result of CCD-RSM, optimum conditions for the emulsification were determined as 23.6 min, 7.7 wt.%, and 3.9 wt.% for the emulsification time, amount of emulsifier, and amount of sprout, respectively. From the optimized condition obtained, MDS, viscosity, and ESI after 7 days from reaction were estimated as 252.3 nm, 616.7 cP, and 88.7%, respectively. The overall satisfaction was 0.9137, which supported the validity of the experiments, and the error rate was measured at 0.5% or less by advancing the experiments. Therefore, an optimized process for producing an emulsion by adding the malt extract was designed by the CCD-RSM.

• Archives of Pharmacal Research
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• v.29 no.9
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• pp.795-799
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• 2006

Peptides, although high efficacy and specificity in their physiological function, usually have low therapeutical activities due to their poor bioavailability when administrated orally. Nanoparticles have been regarded as a useful vector for targeted drug delivery system because they can protect drug from being degraded quickly and pass the gastrointestinal barriers. Here we described a novel oral N-trimethyl chitosan nanoparticles formulation containing thymopentin (Tp5-TMC-NP). N-trimethyl chitosan (TMC) was synthesized and then used to prepare Tp5-TMC-NP by ionotropic gelation. A three-factor, five-level CCD (Central Composite Design) design was used in the optimization procedure, with HPLC as the analyzing method. The resulting Tp5-TMC-NP had a regular spherical surface and a narrow particle size range with a mean diameter of 110.6 nm. The average entrapment efficiency was 78.8%. The lyophilized Tp5-TMC-NP formulation was stable in $4^{\circ}C\;or\;-20^{\circ}C$ after storage of 3 months without obvious changes in morphology, particle size, pH and entrapment ratio. The results of the flow cytometer determination showed that the ratio of $CD4^+/CD8^+$ of Wistar female rat given Tp5-TMC-NP (ig) was 2.59 time that of the group given Tp5 (ig).

• Integrative Medicine Research
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• v.6 no.4
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• pp.388-394
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• 2017

Background: The present study optimized ultrasound-assisted extraction conditions to maximize extraction yields of glycyrrhizic acid from licorice. Methods: The optimal extraction temperature ($X_1$), extraction time ($X_2$), and methanol concentration ($X_3$) were identified using response surface methodology (RSM). A central composite design (CCD) was used for experimental design and analysis of the results to obtain the optimal processing parameters. Results: Statistical analyses revealed that three variables and the quadratic of $X_1$, $X_2$, and $X_3$ had significant effects on the yields and were followed by significant interaction effects between the variables of $X_2$ and $X_3$ (p<0.01). A 3D response surface plot and contour plots derived from the mathematical models were applied to determine the optimal conditions. The optimum ultrasound-assisted extraction conditions were as follows: extraction temperature, $69^{\circ}C$; extraction time, 34?min; and methanol concentration, 57%. Under these conditions, the experimental yield of glycyrrhizic acid was 3.414%, which agreed closely with the predicted value (3.406%). Conclusion: The experimental values agreed with those predicted by RSM models, thus indicating the suitability of the model employed and the success of RSM in optimizing the extraction conditions.

• Food Engineering Progress
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• v.21 no.3
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• pp.256-266
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• 2017

This study was designed to optimize ethanol extraction process of unfertilized corn silk (UCS) to maximize phytochemical contents and bioactivities. The response surface methodology (RSM) with central composite design (CCD) was employed to obtain the optimal extraction conditions. The influence of ethanol concentration, extraction temperature and extraction time on total polyphenol contents, total flavonoid contents, maysin contents, 2,2-diphenyl-1-picrylhydrazyl(DPPH) radical scavenging activities and tyrosinase inhibition were analyzed. For all dependable variables, the most significant factor was ethanol concentration followed by extraction temperature and extraction time. The following optimum conditions were determined by simultaneous optimization of several responses with the Derringer's desirability function using the numerical optimization function of the Design-Expert program: ethanol concentration 80.45%, extraction temperature $53.49^{\circ}C$, and extraction time 4.95 h. Under these conditions, the predicted values of total polyphenol contents, total flavonoid contents, maysin contents, DPPH radical scavenging activity and tyrosinase inhibition were $2758.74{\mu}g\;GAE/g$ dried sample, $1520.81{\mu}g\;QUE/g$ dried sample, 810.26 mg/100g dried sample, 56.86% and 43.49%, respectively, and the overall desirability (D) was 0.74.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.561-578
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• 2020

The present work addresses the surface integrity and chip morphology in finish hard turning of AISI D3 steel under nanofluid assisted minimum quantity lubrication (NFMQL) condition. The surface integrity aspects include microhardness, residual stress, white layer formation, machined surface morphology, and surface roughness. This experimental investigation aims to explore the feasibility of low-cost multilayer (TiCN/Al2O3/TiN) coated carbide tool in hard machining applications and to assess the propitious role of minimum quantity lubrication using graphene nanoparticles enriched eco-friendly radiator coolant based nano-cutting fluid for machinability improvement of hardened steel. Combined approach of central composite design (CCD) - analysis of variance (ANOVA), desirability function analysis, and response surface methodology (RSM) have been subsequently employed for experimental investigation, predictive modelling and optimization of surface roughness. With a motivational philosophy of "Go Green-Think Green-Act Green", the work also deals with economic analysis, and sustainability assessment under environmental-friendly NFMQL condition. Results showed that machining with nanofluid-MQL provided an effective cooling-lubrication strategy, safer and cleaner production, environmental friendliness and assisted to improve sustainability.

• Advances in nano research
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• v.12 no.4
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• pp.387-403
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• 2022

Silica nanoparticles, which have a broad range of sizes and specific surface features, have been used in many industrial applications. This study was conducted to synthesize monodispersed silica nanoparticles directly from tetraethyl orthosilicate (TEOS) with an alkaline catalyst (NH₃) based on the sol-gel process and the Stöber method. A central composite design (CCD) is used to build a second-order (quadratic) model for the response variables without requiring a complete three-level factorial experiment. The process was then optimized to achieve the minimum particle size with the lowest concentration of TEOS. Dynamic light scattering and scanning electron microscopy were used to analyze the size, dispersity, and morphology of the synthesized nanoparticles. After optimization, a confirmation test was carried out to evaluate the confidence level of the software prediction. The results revealed that the predicted optimization is consistent with experimental procedures, and the model is significant at the 95% confidence level.