Box-Behnken Design Of Response Surface Methodology Research Articles

Optimizing injection molding parameters to minimize and prediction potential for flashing defects

The injection molding process is a manufacturing process that can produce products in a short time in large quantities, in the injection molding process the factor of setting process parameters plays a significant role in product quality, so it requires special treatment. The purpose of this study is to find the optimal parameters in the injection moulding process of yogurth container lid with polypropylene material, so that the process can reduce the incidence of flashing defects that result in the emergence of initial waste in the industrial environment. The method used in this research is to create a Response Surface Methodology Box-Behnken Design (RSM - BBD) optimization model and an Artificial Neural Network (ANN) model approach in analyzing optimal parameters and predicting the appearance of flashing defects in a designed cycle. The results obtained from this research are the optimal parameters from the RSM and ANN model recommendations, namely the clamping force setting of 70 tons, holding time 0.1 seconds, and holding pressure. The ANN model provides the highest level of prediction accuracy with an R2 value of 100% and a prediction error rate of 7.9689E-09. In comparison, the RSM model obtains a prediction accuracy level with an R2 of 71% with an error rate of 0.24315.

Response surface methodology and artificial intelligence modeling for in vitro regeneration of Brazilian micro sword (Lilaeopsis brasiliensis)

In this study, response surface methodology (RSM) was used to optimize in vitro regeneration of the Brazilian micro sword (Lilaeopsis brasiliensis) aquatic plant, followed by data prediction and validation using machine learning algorithms. The basal salt, sucrose and Benzyaminopurine (BAP) concentrations were derived from Box-Behnken design of RSM. The response surface regression analysis revealed that 1.0 g/L MS + 0.1 mg/L BAP + 25 g/L sucrose was optimized for maximum regeneration (100%), shoot counts (63.2), and fresh weight (1.382 g). The RSM-based predicted scores were fairly similar to the actual scores, which were 100% regeneration, 63.39 shoot counts, and 1.44 g fresh weight. Pareto charts analysis illustrated the significance of MS for regeneration and fresh weight but remained insignificant. Conversely, MS × BAP was found to be the most crucial factor for the shoot counts, with MS coming in second and having a major influence. The analysis of the normal plot ascertained the negative impact of elevated MS concentration on shoot counts and enhanced shoot counts from the combination of MS × BAP. Results were further optimized by constructing contour and surface plots. The response optimizer tool demonstrated that maximum shoot counts of 63.26 and 1.454 g fresh weight can be taken from the combination of 1.0 g/L MS + 0.114 mg/L BAP + 23.94 g/L. Using three distinct performance criterias, the results of machine learning models showed that the multilayer perceptron (MLP) model performed better than the random forest (RF) model. Our findings suggest that the results may be utilized to optimize various input variables using RSM and verified via ML models.Key messageOptimization of in vitro whole plant regeneration of Brazilian sword wood using response surface methodologyData analysis through ANOVA, response surface regression anlaysis and machine learningGraphical presentation of data via Pareto charts, normal plots, contour plots and surface plots for optimizationBetter performance of ANN-based MLP model compared to decision tree based RF modelGraphical abstract

Simultaneous Extraction and Decaffeination Process Optimization of Green Coffee Bean-Based Beverages Using Response Surface Methodology

Simultaneous Extraction and Decaffeination Process Optimization of Green Coffee Bean-Based Beverages Using Response Surface Methodology

Hydrothermal carbonization of organic waste using faecal sludge as a water source: Response surface methodology-Box Behnken design

In this research, organic waste was subjected to hydrothermal carbonization (HTC) using faecal sludge as the water source. HTC is a sustainable method for converting organic waste into valuable hydrochar. However, the use of portable water as a reaction medium in HTC is environmentally unsustainable and increases operational costs. The aim of this study was to optimize HTC operating parameters such as residence time, temperature, and biomass to water (BTW) ratio for maximizing both higher heating value (HHV) and hydrochar yield and also to determine the effects of these operating parameters on the hydrochar properties. This study utilized a Box Behnken design within the response surface methodology to identify optimal HTC conditions. Temperature was varied between 180 and 250 °C, residence time between 30 min and 120 min, and BTW ratio between 1 and 10. Volatile matter percentage was reduced in the hydrochar compared to that of the feedstock. A progressive rise in carbon percentage and a decline in oxygen percentage were observed with increasing temperatures. Temperature and residence time were the most significant factors affecting HHV, on the other hand, temperature and BTW ratio were the most significant factors that affected hydrochar yield. Numerical optimization of the factors revealed that a maximum HHV of 28.409 MJ/kg was obtained at 250 °C, 116 min, and a 1:9 BTW ratio, while an ideal hydrochar yield of 57.491% was obtained at 242 °C, 95 min and a BTW ratio of 1:9. This study highlights the environmental sustainability of utilizing faecal sludge as a water source in HTC, presenting a promising possibility for transforming organic waste into valuable hydrochar while addressing concerns related to water use.

"UHPLC-Q-TOF/MS-chemometrics-network pharmacology" integrated strategy to discover quality markers of raw and stir-fried Fructus Tribuli and process optimization of stir-fried Fructus Tribuli.

Fructus Tribuli, the dried ripe fruit of Tribulus terrestris L., has various beneficial effects, including liver-calming and depression-relieving effects. Raw Fructus Tribuli (RFT) and stir-fried Fructus Tribuli (SFT) are included in the Chinese Pharmacopoeia 2020 edition (Ch. P 2020). However, owing to the lack of specific regulations on SFT-processing parameters in Ch. P 2020, it is difficult to ensure the quality of commercially available SFT. The present study aimed to screen the quality markers (Q-markers) of RFT and SFT and optimize the processing technology of SFT based on the identified Q-markers. First, the ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) technology as well as multiple statistical analysis along with network pharmacology was used to comprehensively identify the Q-markers of RFT and SFT. Then, based on single-factor experiments, the Box-Behnken design (BBD) response surface methodology (RSM) was used to optimize the processing technology of SFT and perform process validation. A total of 63 components were identified in RFT and SFT extracts. Terrestrosin D and Terrestrosin K were initially considered the Q-markers of RFT and SFT, respectively. The optimum processing technology conditions were 208°C, 14 min, and 60 r·min-1 . Three batches of process validation were performed, and the mean composite score was 56.87, with a relative standard deviation (RSD) value of 1.13%. The content of steroidal saponin components in RFT was significantly different before and after stir-frying. Terrestrosin D and Terrestrosin K were validated as the Q-markers of RFT and SFT, respectively. The identification of Q-markers for RFT and SFT offered a clear index for optimizing the SFT-processing technology and provided a basis for the quality control of RFT and SFT decoction pieces.

Mix proportion and microscopic characterization of coal-based solid waste backfill material based on response surface methodology and multi-objective decision-making

The mix proportion of multi-source coal-based solid waste (CSW) for underground backfilling affects transportation and support performance of backfill materials, and even the backfilling cost. In this study, the optimal mix proportion of desulfurization gypsum (DG), furnace bottom slag (FBS) and gasification fine slag (GFS) is determined by the Response Surface Methodology–Box Behnken Design (RSM-BBD). Then the fluidity, bleeding rate, 3-day strength, 7-day strength and preparation cost are evaluation indicators, the optimal mix proportion of backfill materials is determined by the multi-objective decision-making method (MDM). Finally, the microstructure of the backfill material with optimal mix proportion was studied by TGA, MIP, SEM–EDS and XRD. The results show that the mix proportion of CSW with the optimal comprehensive index is coal gangue (CG): coal fly ash (CFA): DG: FBS: GFS = 1:1.5:0.2:0.1:0.1, the mass concentration is 78%, and ordinary Portland cement (OPC)/CSW = 7.5%. The weight loss phenomenon of the backfill material with the optimal mix proportion occurs continuously during the heating process, mainly due to the evaporation of crystal water, structural water and hydroxyl water. There are dense narrow-necked pores in the backfill material, and the pore connectivity is poor. There is no hydration reaction occurs between CSW particles, and the strength increase of the backfill material mainly depends on the hydration reaction of cement. In ettringite, part of Al2O3 is replaced by SiO2, and part of CaSO4 is replaced by CaCO3. This study provides a reference for the engineering application of underground backfilling with multi-source CSW.

Effect of Thermally Extracted Carrot Oil Using Biomass Solvent to Boost Consumer Goods: Box-Behnken Design Approach

Massive production of fast-moving consumer goods boosts the economy of any nation. Thus, the need to look into ways of accelerating and transforming carrot utilization into more commercialized usage in order to add value to the developmental strides of any nation where carrot is cultivated like Nigeria. This study concluded that the optimization of the carrot oil extracted from crushed carrot and coconut oil (biomass volume) via soxhlet equipment using Box-Behnken Design (BBD) of Response Surface Methodology (RSM) approach, generated an ideal optimal output of 18.58 wt% at SW of 60 g, BV of 200 ml and ET of 14mins. Although, three input elements which are sample weight (SW), biomass volume (BV), and extraction time (ET) were modelled to generate 17 setups by BBD, but standard order (Std) 8 from the 17 setups generated an ideal output of 18.58 wt%. Thus, the process optimization of the extraction process via BBD of RSM showed that both the coefficient of determination (R2) which is 0.9886, and the difference between adjusted R2 and predicted R2 which is less than 0.2 fall within an ideal range. Also, the elements considered for modeling are mutually significant with the quadratic model equation and the interactive effects of the independent parameters on the carrot oil output showed that an increase in the sample weight and time led to a corresponding increase in the carrot oil output, and this is corroborated by the perturbation plot. Additionally, the physiochemical valuables of the carrot oil generated showed that the free fatty acid and the acid value were very low signifying that the carrot oil is edible and can be used in the manufacturing process using the saponification method in making soap and moisturizing cream for the benefit of mankind.

Optimization of intumescent flame retardant system based on ammonium polyphosphate, double pentaerythritol, and zinc borate for thermoplastic polyurethane composite

AbstractThe widespread industrial applications of thermoplastic polyurethane (TPU) are partially limited by its flammability. The design of high‐performance intumescent flame retardants (IFR) is of great significance for enhancing flame retardant (FR) performance of TPU. In this work, an IFR system consisting of ammonium polyphosphate (APP), double pentaerythritol (DPER), and zinc borate (ZB) is proposed. The optimized experimental parameters with 15 wt.% additive amount of FR, APP‐DPER weight ratio of 2.28:1 and 15.56 wt.% ZB content are regulated based on Box–Behnken design‐response surface methodology (BBD‐RSM) to obtain TPU/FR composite with superior limiting oxygen index value of 30.2%. Noticeably, the design efficiency of TPU/FR composite is significantly improved by utilizing BBD‐RSM. Results of vertical burning test show that the optimized TPU/FR composite passes UL 94 V‐0 rating and peak heat release rate is dramatically reduced from 1355.88 (neat TPU) to 201.01 KW/m2 through cone calorimeter test. In addition, scanning electron microscopy accompanied with Raman spectroscopy are conducted to characterize the morphology and composition of residual char for further exploring the FR mechanism of IFR system in TPU. The as‐prepared TPU/FR composite has provided new potential application in engineering fields.

Valorisation of Napier grass through fibre extraction and coloration by natural dye from Rubia tinctorum

AbstractAgricultural biomass is a well‐known renewable resource with a strong possibility of recycling. The current work focuses on extracting, preparing and colouring Napier grass fibre (NGF) with a colourant extracted from Rubia tinctorum (RT) (which is generally known as madder). NGF that had been water‐retted was alkaline scoured and bleached using hydrogen peroxide to increase the material's whiteness index and water absorption capacity without degrading its breaking strength. After being mordanted with tannic acid, the bleached NGF was coloured with an aqueous extract of the colourant extracted from RT. The Box–Behnken response surface methodology design model was employed to optimise the dyeing concentration, temperature and time. The dyed fibre showed good colour strength (K/S) and adequate wash, rub and light fastness. Adopting the findings from the current study would increase the efficient utilisation of biomass for use in textiles, which is unnecessarily wasted.

Adsorption of Cu(II) on silica gel synthesized from chemical bottle glass waste: Response surface methodology-Box Behnken design optimization

Recent research has reported on the extraction and synthesis of silica gels from a waste glass of chemicals. This study aims to optimize silica gel synthesized from chemical glass waste as heavy metal adsorbent Cu2+. Silica gel adsorbent has been successfully synthesized by reacting silica from chemical glass waste and sodium hydroxide (NaOH) by a fusion reaction and sol–gel process. Synthesized silica gel has an amorphous diffractogram at 2θ 20–30°, a purity of 75.63 %, a surface area of 297.08 m2/g, and a pore radius of 15.74 nm. The adsorption formulation was optimized using Design Box–Behnken and optimum conditions were obtained at adsorbent doses close to 3.5 g, initial concentration 50–100 ppm, contact time 10 min, and pH 9. Adsorption Isotherm Langmuir, Freundlich, Temkin, and Dubinin–Raduskevich were investigated to determine the mechanism of adsorption. Adsorption data show that the adsorption is well-fitted to the Langmuir isotherm model. The results of SEM–EDX characterization showed that the surface morphology of silica gel showed a spherical and irregular surface then after adsorption cu metal was distributed on the surface of the silica gel. Based on all the results of the study it can be indicated that silica gel synthesized from chemical glass bottle waste can be applied as adsorbent Cu2+.

Application of waste derived magnetic acid-base bifunctional CoFe/biochar/CaO as an efficient catalyst for biodiesel production from waste cooking oil

The loss of active components, weak acid resistance, and low recover efficiency of common Ca-based catalysts limited its further development and application. In this study, to effectively produce biodiesel from waste cooking oil (WCO), a green and recyclable magnetic acid-base bifunctional CoFe/biochar/CaO catalyst was prepared from sargassum and river snail shell waste via hydrothermal method. The catalysts' structure and properties were investigated by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), CO2/NH3 temperature programmed desorption (CO2/NH3 TPD), etc., The prepared catalyst mainly consisted of the carbon skeleton, CoFe alloy, and CaO. CoFe alloy provided catalyst's ferromagnetism for magnetic separation as well as acid sites for transesterification of WCO. Ca and other metal species with nanoscale (∼5.64 nm) were dispersively anchored on sargassum biochar surface, thereby leading to good catalytic activity (99.21% biodiesel yield) and stability (91.70% biodiesel yield after the 5th cycle). In addition, response surface methodology-Box-Behnken design (RSM-BBD) revealed the optimal operational conditions were 16:1 methanol/oil molar ratio, 3 wt% catalyst dosage, 73 °C for 157 min. The maximum biodiesel yield predicted value was 98.29% and the experimental value was 99.21%, indicating good satisfaction of the established model. Moreover, the quality of WCO biodiesel met the ASTM D6751 standards. This study benefits magnetic waste-derived acid-base bifunctional catalysts for the disposal of WCO towards sustainable biodiesel production.

Optimization of extraction process of Astragali radix-Paeoniae radix alba by comparing BBD-RSM and SA-BPNN and antioxidant activity

The Box-Behnken design-response surface methodology (BBD-RSM) and Back-propagation neural network prediction model optimized by Simulated annealing (SA-BPNN) were used to optimize the extraction process of Astragali radix-Paeoniae radix alba by the green natural deep eutectic solvent (NADES), and the antioxidant activity of them was discussed. The best NADES for extracting Astragali radix-Paeoniae radix alba need to be screened out. The comprehensive evaluation value of the extraction yield was used as the index. The BBD-RSM and SA-BPNN were established for prediction and optimization. The antioxidant activity of Astragali radix-Paeoniae radix alba in vitro and in vivo was studied by detecting 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging rate and ferric reducing antioxidant power (FRAP) and the expression levels of SOD, MDA and GSH-Px in rat plasma. The results showed that the best NADES formula screened was Betaine-Urea (Bet-Ur). Compared with the BBD-RSM, the SA-BPNN had a higher degree of fitting, the comprehensive evaluation value was higher, and the error between tested and predicted value was smaller, which was more suitable as a prediction model for the extraction yield of Astragali radix-Paeoniae radix alba. Through the determination of antioxidant kits and oxidative factors, the results showed that Astragali radix-Paeoniae radix alba had antioxidant activity in vitro and in vivo. The study on the extraction process optimization and antioxidant activity of Astragali radix-Paeoniae radix alba were expected to provide a theoretical basis for its effective utilization.

Extraction Process Optimization of Curcumin from Curcuma xanthorrhiza Roxb. with Supercritical Carbon Dioxide Using Ethanol as a Cosolvent.

Curcuma xanthorrhiza Roxb., known as temulawak, Javanese ginger, or Javanese turmeric, is a plant species belonging to the ginger family. This plant originated in Indonesia, more specifically on Java Island, and is usually used as medicine. It contains a high amount of a phenolic compound, namely, curcumin. A supercritical carbon dioxide extraction technique was employed to extract curcumin from C. xanthorrhiza. The objective of this work was to investigate the effects of temperature, pressure, and CO2 flow rate on the extraction yield and curcumin recovery from C. xanthorrhiza, which was extracted using supercritical carbon dioxide and ethanol as a cosolvent. The Box-Behnken design (BBD) experimental design and response surface methodology were used to optimize the extraction yield and curcumin recovery. The extraction conditions at a temperature of 40 °C, a pressure of 25 MPa, and a CO2 flow rate of 5.34 mL/min produced the optimum extraction yield of 10.4% and curcumin recovery of 3.2%. From Fourier transform infrared analysis, although the physical-chemical structure in the residue of the starting material was almost similar, the quantity of all functional groups in the residue decreased from the starting material. From scanning electron microscopy analysis, it was confirmed that the cell was broken due to the high-pressure effect, so that the extraction process runs easily.

Exploring tensile properties of bio composites reinforced date palm fibers using experimental and Modelling Approaches

The objective of this study was to assess the tensile strength of epoxy bio-composites reinforced with palm fibers, both untreated and treated with sodium carbonate NaHCO3 at a concentration of 10 % (w/v) for 24 and 96 h, with varying weight percentages of fibers (15 %, 20 %, 25 %, and 30 %). To predict the mechanical performance of the composites, two methods were employed: artificial neural network (ANN) and response surface methodology (RSM). A Box-Behnken RSM design was used to conduct experiments and establish a mathematical model of the bio-composite behavior as a function of the fiber percentage in the samples, specimen cross-section, and treatment time. The ANN forecasts showed consistent expected values for the bio-composite sample behavior, with a correlation coefficient (R2) greater than 0.98 for Young's modulus and 0.97 for stress. Similarly, the correlation coefficients obtained by RSM for the mechanical properties were also highly satisfactory, with an R2 of 0.89 for Young's modulus and 0.87 for stress. Finally, the errors generated by each method (Box-Behnken and ANN) were compared to the experimental results.

Experimental study on the thermodynamic performance optimization of phase change energy storage permeable concrete

To prepare Phase Change Energy Storage Permeable Concrete (PCESPC) with excellent thermodynamic performance, it is necessary to determine the optimal volume fraction of Microencapsulated Phase Change Material (MPCM), volume fraction of Carbon Nanotubes (CNTs), and Water-Binder ratio (W/B). In this study, we utilized the response surface methodology Box-Behnken Design (RSM-BBD) in Design-Expert software to optimize the experimental design and establish regression models to investigate the effects of the three aforementioned parameters on PCESPC's compressive strength, permeability coefficient, temperature change range, and snow melting rate. This approach aims to optimize the relationship between key factors and response variables in studying complex systems, helping researchers find the optimal process conditions to achieve the best response variable results. The study revealed that the optimal formulation includes 1.39 % volume content of MPCM, 0.3 % volume content of CNTs, and W/B of 0.33. This formulation yields PCESPC with compressive strength of 20.25 MPa, permeability coefficient of 1.25 mm/s, temperature drop amplitude of 3.97 ℃, temperature rise amplitude of − 4.96 ℃, and snow melting rate of 11.40 g/min. After experimental validation, the error between the predicted results and the experimental values was found to be less than 5 %, indicating the accuracy and reliability of the optimized results. Furthermore, the introduction of two MPCM with distinct phase change temperature ranges enabled dual-temperature regulation and snow melting effects for permeable concrete pavement under both high and low temperature conditions, which can provide valuable insights for the optimization of PCESPC composition and road surface temperature control.

Optimization of extraction process for classic prescription Yihuang Decoction based on Box-Behnken design-response surface methodology, standard relation, and analytic hierarchy process combined with entropy weight method

Based on the concept of quality by design(QbD), the Box-Behnken design-response surface methodology combined with standard relation(SR) and analytic hierarchy process(AHP)-entropy weight method(EWM) was applied to optimize the extraction process of the classic prescription Yihuang Decoction. The content of geniposidic acid, phellodendrine hydrochloride, and berberine hydrochloride in Yihuang Decoction, the extract yield, and fingerprint similarity were used as the critical quality attributes(CQAs) of the extraction process. The extraction time, water addition, and extraction times were used as the critical process parameters(CPPs). After determining the levels of each factor and level through single-factor experiments, response surface experiments were designed according to the Box-Behnken principle, and the experimental results were analyzed. The SR between each sample and the reference sample under various evaluation indicators of different extraction parameters was calculated. The weights of the five evaluation indicators were determined using AHP-EWM, followed by comprehensive evaluation. A function model between CPPs and CQAs characterized by comprehensive scores was established to predict the optimal extraction process parameters. In the final comprehensive weight coefficients, the yield rate accounted for 43.1%, and the content of berberine hydrochloride, phellodendrine hydrochloride, and geniposidic acid accounted for 35.1%, 6.3%, and 15.5%, respectively. After comprehensive score analysis with SR, the established second-order polynomial model was statistically significant(P<0.01, and the lack of fit was not significant). The predicted optimal extraction conditions for Yihuang Decoction were determined as follows: 8-fold volume of water, extraction time of 1.5 h, and extraction once. The mean comprehensive score of the validation experiment was 85.77, with an RSD of 0.99%, and it met the quality control stan-dards for the reference sample of Yihuang Decoction. The results indicate that the optimized extraction process for Yihuang Decoction is stable and reliable, and the water extract is close in quality attributes to the reference sample. This can serve as a foundation for the research and development of granules in the future. Box-Behnken design-response surface methodology combined with SR and AHP-EWM can provide references for the modern extraction process research of other classic prescriptions.

Development of flexible grouting material for cement-stabilized macadam base using response surface and genetic algorithm optimization methodologies

To repair the voids and cracks in the Cement-stabilized macadam base (CSMB), a grouting material with lower elastic modulus, enhanced fluidity and slight expansion called Flexible Grouting Material (FGM) was developed using superfine cement, fly ash (FA), silica fume (SF), vinyl acetate-ethylene (VAE) copolymer emulsion, and polyvinyl alcohol (PVA) fiber. After that, the study optimized the proportion of FGM using Response Surface Methodology (RSM) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) in Multi-Objective Optimization (MOO). Firstly, to determine the component contents for subsequent experiments, the fluidity, setting time, compressive/flexural strength (1d + 3d), and ratio of compressive strength to flexural strength (C/F, 1d + 3d) were tested. Subsequently, the Response Surface Methodology-Box Behnken Design (RSM-BBD) was employed using VAE content, PVA content, and water-to-cement ratio (W/C) as factors. Additionally, the fluidity, setting time, compressive/flexural strength and C/F (28d), elastic modulus (28d), and drying shrinkage (28d) were considered as responses in RSM-BBD. The VAE content and W/C significantly influenced the response values, while the PVA content had a relatively minor influence. Finally, the NSGA-II was utilized to determine the optimal proportion of FGM. Compared to the control group, the optimal FGM demonstrated 16.53 % increase in fluidity, 37.86 % decrease in elastic modulus (28d), 47.98 % decrease in C/F (28d), 22.22 % reduction in drying shrinkage (28d), and 54.07 % increase in final setting time.

Optimization of microreactor-intensified transesterification reaction of sesame cake oil (sesame waste) for biodiesel production using magnetically immobilized lipase nano-biocatalyst

Enzyme-catalyzed transesterification to produce biodiesel is a time-consuming reaction. This study aimed to use a recoverable nanomagnetic immobilized enzyme and microreactor-intensified process to design a significantly rapid transesterification reaction. Immobilization of Candida Rugosa lipase (CRL) on GO-Fe3O4@TiO2 nanocomposite was optimized using response surface methodology-box–Behnken design (RSM-BBD). Results showed the highest immobilization efficiency of 92.73% at the optimum condition of CRL concentration of 2.59 mg/mL, time of 4.96 h, and temperature of 37.61 °C. Newly synthesized GO-Fe3O4@TiO2@CRL nano-biocatalyst (NBC) was characterized using FTIR, XRD, VSM, FE-SEM, EDX and elemental mapping. Immobilized CRL showed improved stability under different parameters, including pH, thermal, and methanol medium compared to free CRL. Freshly synthesized NBC was used in a microreactor to intensify the transesterification reaction of sesame cake oil to produce biodiesel. The RSM-BBD optimization of the transesterification reaction showed a maximum conversion rate of 97.03%, achieved at the NBC amount of 4.47 wt%, residence time of 13.29 min, and Me/oil molar ratio of 4.28. The generated biodiesel has all characteristics well within the ASTM D6751, demonstrating its good quality. The results of this study showed that using a microreactor could sufficiently intensify the transesterification reaction and reduce the reaction time using GO-Fe3O4@TiO2@CRL NBC.

PH-responsive magnetic graphene oxide composite as an adsorbent with high affinity for rapid capture of nucleosides.

Anovel pH-responsive magnetic graphene oxide composite (MGO@PEI-BA) isproposed for the first time as an adsorbent for the rapid capture and detection of nucleosides (cytidine, uridine, guanosine, and adenosine). The morphology, structure, and magnetic properties of thecomposite were evaluated using various characterization techniques. The results indicated that the composite was successfully fabricated. A series of parameters that affect extraction and elution were optimized through one-factor-at-a-time and Box-Behnken design of response surface methodology (BBD-RSM). The unique layered structures and easily accessible active sites of the composite facilitated molecular transport, resulting in instantaneous equilibrium of nucleosides adsorption within 5 min. Based on this study, a magnetic dispersive micro-solid-phase extraction (MD-μ-SPE) method assisted by the MGO@PEI-BA was developed in combination with UHPLC-UV analysis for the determination of nucleosides in rat urine. Under the optimum conditions, a wide linear range (10-2000 ng mL-1), good linearity (r > 0.99), low detection limits (1-3 ng mL-1), low relative standard deviations (RSDs ≤ 3.9%), and satisfactory recoveries (82.7-96.3%) were achieved. These results demonstrate that the MGO@PEI-BA is an excellent adsorbent for extracting nucleosides from biological samples.

Ionic liquid-based ultrasonic-assisted extraction coupled with HPLC to analyze isoquercitrin, trifolin and afzelin in Amygdalus persica L. flowers

This study aimed to establish a method for the simultaneous determination of isoquercitrin, trifolin and afzelin in A. persica flowers by high performance liquid chromatography (HPLC) with ionic liquid as extractant and ultrasonic-assisted extraction. The effects of ionic liquid concentration, solid–liquid ratio, number of crushing mesh, ultrasonic time, extraction temperature, and ultrasonic power on the extraction yield of three target compounds were investigated using the extraction yield of target analytes as the index. According to the results of single factor experiment, the Box-Behnken design-response surface methodology (BBD) was used to optimize the extraction method and compared with the traditional extraction method. The results showed that, calibration curves had excellent linearity (R2 > 0.9990) within the test ranges. In combination with other validation data, this method demonstrated good reliability and sensitivity, and can be conveniently used for the quantification of isoquercitrin, trifolin and afzelinin A. persica flowers. And the contents of isoquercitrin, trifolin and afzelin were 64.08, 20.55 and 75.63 μg/g, respectively. The optimal process obtained by BBD was as follows: ionic liquid concentration was 1.0 mol/L, solid–liquid ratio was 1:40 g/ml, mesh sieve was 50 mesh, ultrasonic time was 40 min, extraction temperature was 50 °C, and ultrasonic power was 400 W. Under the optimal conditions, the theoretical predicted total extraction yield of the three target compounds was 159.77 μg/g, which was close to the actual extraction value (160.26 μg/g, n = 3), this result indicating that the optimal process parameters obtained by response surface methodology analysis were accurate and reliable. The method was simple, accurate and rapid for determination the contents of three active ingredients in A. persica flowers.