Employing Response Surface Methodology Research Articles

Characterization and optimization of ultrasound assisted oxidative desulfurization of a model fuel using a novel magnetic deep eutectic solvent

ABSTRACT In various studies, researchers have utilised different solvents to extract sulfur compounds from the fuels. This paper introduces a novel magnetic deep eutectic solvent employed in the ultrasound-assisted oxidative desulfurisation of dibenzothiophene within a model fuel. The solvent, synthesised at 85°C by combining choline chloride, p-toluene sulfonic acid, and FeCl₃, underwent characterisation through Fourier transform-infrared, Vibrating-sample magnetometer, and Raman spectrometry. Exploration of the key parameters, including oxidant to model fuel volumetric fraction percentage (0.2–0.3), Iron (III) chloride to choline chloride mole fraction (0.1–0.3), and Magnetic deep eutectic solvent to model fuel volumetric fraction (0.2–0.3), was conducted to assess their impact on dibenzothiophene conversion rates. Employing response surface methodology based on central composite experimental design, optimal operational parameters for the ultrasound-assisted oxidative desulfurisation process were identified, resulting in a sulfur removal rate of 98.7%. The findings highlight the solvent sustained efficiency even at higher dibenzothiophene concentrations. Additionally, the solvent paramagnetic properties facilitated an expedited separation from the fuel, leading to the significantly reduced process times.

Optimizing reverse osmosis desalination from brackish waters: Predictive approach employing response surface methodology and artificial neural network models

A mathematical model frame has been developed to optimize the performance of reverse osmosis (RO) desalination in brackish waters with medium to high salt concentrations using response surface methodology (RSM) and artificial neural network (ANN), specifically catered towards efficiently operating RO desalination systems. The RSM model aims at predicting RO performance with second-order polynomials based on 15 experimental datasets. Inputs for RSM model include feed TDS concentration, feed water flow rate, and concentration-to-desalination ratio, while the outputs consider rejection, membrane flux, performance index, and specific energy consumption. The Genetic Algorithm optimized back-propagation Neural Network was employed to update network weights and biases, leading to an optimal ANN network structure of 3–10-4. A ratio of 70 % training, 15 % validation, and 15 % test data was chosen to establish an ANN model that predicts the performance of RO desalination. The ANN model demonstrated significantly higher prediction accuracy than the RSM model, with impressive correlation coefficients of 0.9936 for the performance index and 0.9932 for SEC prediction, and low RMSE of 0.85 for rejection. To maximize the performance index and minimize specific energy consumption, a two-step optimization method was further set up by applying the RSM model to initially determine optimal process conditions followed by the ANN model to enhance the accuracy of performance forecasts. Optimal process conditions were proposed for specific feed TDS scenarios, which involved setting a feed TDS concentration limit to meet drinking water standards.

Investigating cultivation strategies for enhancing protein content in Auxenochlorella pyrenoidosa FACHB-5

This study investigated the influence of yeast extract addition, carbon source, and photoperiod on the growth dynamics of Auxenochlorella pyrenoidosa FACHB-5. Employing response surface methodology, the culture strategy was optimized, resulting in the following optimal conditions: yeast extract addition at 0.75 g L-1, glucose concentration of 0.83 g L-1, and a photoperiod set at Light: Dark = 18 h: 6 h. Under these conditions, the biomass reached 1.76 g L-1 with a protein content of 750.00 g L-1, containing 40 % of essential amino acids, representing a 1.52-fold increase. Proteomic analysis revealed that the targeted cultivation strategy up-regulated genes involved in microalgal protein synthesis. The combined effect of yeast extract and glucose enhanced both the glutamine synthetase-glutamate synthetase mechanism and the free amino acid content.

Optimizing properties of clayey soil using lime and waste marble powder: a sustainable approach for engineering applications

Several studies have explored the potential of waste marble powder (WMP) and lime (LM) as solutions for issues associated with clayey soils. While WMP enhances mechanical properties and addresses environmental concerns, LM effectively improves soil characteristics. This research investigates the efficacy of LM and WMP, both individually and in combination, in addressing challenges specific to clayey soils in Bouzaroura El Bouni, Algeria. These soils typically exhibit low load-bearing capacity, poor permeability, and erosion susceptibility. LM demonstrates promise in enhancing soil properties, while WMP not only addresses environmental concerns but also enhances mechanical characteristics, providing a dual benefit. The study utilizes a three-variable experiment employing Response Surface Methodology (RSM) Box-Behnken Design, with variations in clay content (88%–100%), LM treatment (1.5%–9%), and WMP inclusion (1.5%–9%). Statistical analysis, including ANOVA, reveals significant patterns with p-values <5%. Functional relationships between input variables (clay, LM, and WMP) and output variables (cohesion, friction angle, and unconfined compressive strength) are expressed through high determination coefficients (R2 = 99.84%, 77.83%, and 96.78%, respectively). Numerical optimization identifies optimal mixtures with desirability close to one (0.899–0.908), indicating successful achievement of the objective with 88% clay content, 3% LM, and 6% WMP. This study provides valuable insights into optimizing clay soil behavior for environmental sustainability and engineering applications, emphasizing the potential of LM and WMP as strategic additives.

Unveiling Environmental Influences on Sustainable Fertilizer Production through Insect Farming

Entomocomposting is fast and environmentally friendly, boosts soil quality and crop production, and improves resilience to climate change. The black soldier fly larvae (BSFL) catalyze the composting process, but their efficiency is highly influenced by environmental factors and the quality of the substrate. This study employs response surface methodology to discern physical–chemical factors that influence the nutrient quality of BSF frass fertilizer. Internet of Things (IoT) sensors were deployed to monitor in real-time both independent variables (air temperature, moisture content, humidity, and substrate temperature) and dependent variables (nitrogen, phosphorous, and potassium); the data were relayed to the cloud. A non-linear regression model was used to study the relationship between the dependent and independent variables. Results showed that air humidity and air temperature did not have a significant effect on nitrogen and phosphorus accumulation in frass fertilizer, respectively, but phosphorus was significantly influenced by air humidity. On the other hand, neither air temperature nor moisture content has a significant effect on potassium concentration in frass fertilizer. We found that an air temperature of 30 °C and 41.5 °C, substrate temperature of 32.5 °C and 35 °C, moisture content between 70 and 80%, and relative humidity beyond 38% can be conducive for the production of high-quality BSF frass fertilizer. Model validation results showed better robustness of prediction with R2 values of 63–77%, and Radj2 values of 62–76% for nitrogen, phosphorous, and potassium. Our findings highlight the potential for the application of digital tools as a fast and cost-effective decision support system to optimize insect farming for the production of high-quality frass fertilizer for use in sustainable agriculture and crop production.

Terminalia catappa Leaf Extract as a Capping Agent for ZnO Nanoparticle Synthesis via Sol-gel Method and its Microbial Effects on Selected Fungi and Bacterial

This study presents a reliable process for synthesizing ZnO nanoparticles using a green method. In this approach, we harness Terminalia catappa leaf extract as an effective chelating and capping agent to synthesize ZnO nanoparticles from zinc nitrate hexahydrate salt through a sol-gel method, employing Response Surface Methodology (RSM) and its microbial assessment. Optical properties of the ZnO nanoparticles were investigated using UV-visible spectroscopy, and determined their band-gap to range between 4.13 and 5.175 eV. To explore the outcomes, Response Surface Methodology (RSM), was employed which revealed that the Model F-value of 2.62 signifies the significance of the model for the response. Furthermore, when examining the contour plot relating the inhibition zone to temperature and plant extract dosage, we found that an increase in dosage and decrease in temperature resulted in an increase in the bandgap. This method of biosynthesizing zinc oxide nanoparticles through Terminalia catappa leaf extract offers effect against the bactieria and fungi such as; Escherichia -coli, Straphylococcus aureus, Pseudomonas aeuginosa and Trichophyton rubrum, Penicillium marnaffei, Atteneria spp respectively. Therefore, ZnO nanoparticles though this route gives an eco-friendly and more straightforward alternative to chemical and physical synthesis techniques for various environmental applications.

Experimental study of the mechanical and optical properties of glass-polyester fiber composite based on response surface methodology

Due to the intricate amalgamation of various components, composite materials boast mechanical properties that surpass those of their constituents. Among these composite materials, glass fiber-reinforced polyester composites emerge as prominent contenders, finding extensive utility, especially in agricultural greenhouse construction. These structures garner significant acclaim for their exceptional ability to withstand adverse weather conditions, ensure prolonged durability, and transmit light efficiently, thus creating optimal growing conditions. Consequently, they have become the favored choice among farmers seeking dependable and sustainable environments for cultivation. Within the scope of this study, we employ Response Surface Methodology (RSM) as a comprehensive tool to delve deeply into the mechanical and optical characteristics inherent in such composite materials. Our investigation is meticulously tailored to unravel the intricate interplay among crucial factors such as fiber content, length, and plate thickness, elucidating their direct impacts on mechanical properties like stress and elasticity modulus. Our rigorous examination reveals that the pinnacle of mechanical performance is attained within a specific range: fiber content ranging from 20% to 40%, fiber lengths spanning 35 to 45 mm, and plate thicknesses measuring between 0.6 to 3 mm. Furthermore, our meticulous analysis of transmittance measurements uncovers an intriguing correlation: thinner thicknesses and lower fiber content correspond with heightened light transmission across the visible spectrum. Conversely, elevating the fiber content or thickness enhances mechanical robustness but concurrently diminishes light transmittance. Thus, achieving a harmonious equilibrium among these attributes becomes imperative for the pragmatic construction of agricultural greenhouses. Additionally, we venture into incorporating ultraviolet (UV) plastic films to augment the optical prowess of these composites, further elevating their efficacy in greenhouse applications. By embarking on this comprehensive investigation, our overarching objective is to propel sustainable farming practices forward by furnishing a nuanced understanding of the multifaceted factors that shape the performance of glass fiber-polyester composites in agricultural greenhouse applications.

Optimizing operational parameters for highly-concentrated sodium hydroxide production via electrodialysis with bipolar membranes from concentrated brines

Sodium hydroxide necessitates the implementation of cleaner production methods that deviate from the conventional practices in the chlor-alkali industry. New sustainable sources such as concentrated brines, which are typically regarded as waste, are currently being investigated for the production of sodium hydroxide using Electrodialysis with Bipolar Membranes (EDBM). This process has the advantages of not producing gas by-products, reducing operational risks, and providing value to waste brines after converting them into acids or alkali solutions. However, the production of sodium hydroxide via EDBM using brines is limited by the low concentration of the final base (e.g. typically below 2 M), which increases the cost of transport. This study aims to overcome this limitation by optimizing parameters such as salt-to-base volume ratio, initial salt concentration, and current density values. Notably, this research is one of the few to employ Response Surface Methodology with a Central Composite Design to maximize the final sodium hydroxide concentration; two models using second-order polynomial equations were proposed. Results showed the possibility to achieve 5.3 M NaOH under a volume ratio range of 9.8:1–10:1, a current density range of 490 A/m−2 to 500 A/m−2, and an initial salt concentration in the range of 6 M NaCl. Moreover, the energetic analysis showed values of specific energy consumption in a range of 2.5 kWh kgNaOH-1-3.5 kWh kgNaOH-1 and specific productivity of the process up to 3.08 tonNaOH year−1 m−2, which are moderate in comparison with values previously presented in literature. Finally, an economic analysis showed that energy was the most significant cost component, making up 89 % of the total process cost, which was estimated to be 0.69 € kgNaOH-1 (concentration 21.2 % w/w). Overall, these high concentration values open a real chance to shift towards sustainable production of NaOH by means of EDBM from brines, highlighting the novelty of this study.

Effects of aggregate shape on the macrotexture and performance of chip seal: a laboratory study

Chip seal is an efficient maintenance strategy for bituminous pavements, with aggregate shape significantly impacting its embedment and performance, but there is limited quantification of its effects. Using the Aggregate Image Measurement System II (AIMS-II) for shape classification, this study investigated the influence of aggregate shape on chip seal's macrotexture and performance through a series of tests, including 3D laser scanning test, aggregate coverage test, skid resistance test, and sweep test, employing response surface methodology (RSM) for quantification. Results indicated that an abundance of flat aggregates deteriorates surface quality by increasing roughness and altering texture spacing, recommending their proportion be kept under 10%. Conversely, elongated aggregates enhance performance by enriching texture depth and sharpening surface peaks. Spearman rank correlation analysis identified the arithmetic mean peak curvature (Spc ) and the root mean square height (Sq ) as reliable measures for evaluating skid resistance and aggregate retention of chip seals, respectively.

Removal of Staphylococcus aureus using electro-fenton, UV/H2O2, and combination of electro-fenton and UV/H2O2 processes; optimization of operational parameters

Staphylococcus aureus (S. aureus) is an opportunistic pathogen of the gram-positive variety, known to cause a range of severe infections including cellulitis, pneumonia, osteomyelitis, endocarditis, and sepsis. These infections are associated with significant morbidity and mortality rates in both hospital and community settings. Therefore, it is important to remove S. aureus from the aqueous solution. The present study employed response surface methodology as an effective strategy to optimize the removal of S. aureus through the electro-Fenton (EF), UV/H2O2, and combination EF-UV/H2O2 processes. Under the optimized conditions, the maximum removal efficiency in the EF process of 48.5%, UV/H2O2 process of 36.2%, and combination EF-UV/H2O2 process of 100%. The optimum condition for removal efficiency using combination EF-UV/H2O2 process of 100% was attained at S. aureus concentration of 5 × 106 CFU mL−1, current density of 8.0 mA cm−2, H2O2 dosage of 170 µL L−1, and 2 lamps UV during 7.0 min. Both the production of •OH in the EF and UV/H2O2 process and the additive oxidation effect of UV/H2O2 are the main reasons for the better performance of combination EF-UV/H2O2 process. The results indicate that the EF-UV/H2O2 process is highly promising and environmentally sustainable method for treating wastewater samples contaminated with S. aureus.

Investigation of heat and mass transfer of oldroyd – 8 constant fluid in wire coating process employing response surface methodology

Wire coating is widely used for electrical insulation, shock protection, preventing leakage, and facilitating smooth current flow. This study aims to evaluate the applicability of Oldroyd-8 constant fluid for wire applications in a magnetic field using a pressure-type die. Based on the Buongiorno model with a constant pressure gradient and temperature-dependent thermophysical properties, governing equations are developed. These equations are transformed into dimensionless form and solved numerically. The study thoroughly investigates key features, including momentum, thermal distribution, nanoparticle volume fraction, and shear stress rate. Also, this study employs Response Surface Methodology to optimize heat transfer and shear stress rates in coated wire. Quadratic models, developed through a central-composite design, determine optimal levels for the Oldroyd-8 constant fluid parameter and nanofluid parameters, ensuring optimal heat transfer and shear stress rates for the melt. Nanofluid parameters contribute to an improvement in the thermal distribution profile. Optimal heat transfer and shear stress rate occur when the nanofluid parameters are minimized, and non – Newtonian fluid parameter is maximized.

Influence of bio-based kenaf polymer composites on mechanical and acoustic properties for futuristic applications: An initiative towards net-zero carbon emissions

In the pursuit of net-zero carbon emissions, the development of sustainable materials like kenaf fiber composites is pivotal. This innovative approach, which harnesses eco-friendly properties and enhances material performance, holds promise in reducing carbon footprints across diverse industries. As ecological sustainability awareness continues to rise, there is a growing imperative to embrace biodegradable, lightweight, and recyclable materials to address existing limitations in conventional materials. Kenaf fiber, with its unique electromagnetic, acoustic, mechanical, and physical properties, presents a compelling solution. The production process involves impregnating kenaf fiber with bio-based materials, utilizing nanofillers of nickel (Ni), bamboo charcoal (BC), and carbon black (CB), which are blended with epoxy resin through magnetic agitation to ensure homogeneous dispersion. This resulting composite is fortified between two layers of kenaf fiber mats, creating a robust sandwich structure. Employing response surface methodology (RSM) and the central composite design (CCD), the study calculates the optimal weight percentages of nanofillers in various test specimens. Mechanical and acoustic property testing, conducted using appropriate equipment, reveals that a combination of 15 wt% BC, 9 wt% Ni, and 6 wt% CB exhibits the highest tensile strength at 42 MPa, while the blend of 10 wt% BC, 6 wt% Ni, and 4 wt% CB achieves a maximum noise reduction coefficient (NRC) of 0.524. These impressive findings underscore the potential of this suggested material as a superior substitute for conventional materials, further aligning it with the imperative for eco-conscious and sustainable solutions.

Hydrogen storage properties of magnesium based alloys Mg67Ni(32-x)Nb1Alx (x = 1, 3, and 5) by using response surface methodology

Nano metals and hydrogen storage have attracted significant attention in recent years due to their numerous unique properties and wide range of applications. This study explores the synthesis of nanostructured Al and Nb-substituted Mg2Ni intermetallic compounds through high-energy ball milling and investigates their electrochemical performance for energy-related applications. The research emphasizes the critical influence of crystallinity and crystallite size on electrode material performance. Employing Response Surface Methodology (RSM), the study identifies key factors affecting discharge capacity. Notably, current density emerges as the most significant factor, contributing 73% to discharge capacity, as confirmed by perturbation plots. Interaction effects among the factors were found to be relatively insignificant concerning the chemical kinetics of the electrode material. Furthermore, a second-order polynomial equation was developed through RSM to quantitatively relate discharge capacity to composition, milling time, and current density, with a high R2 value of 98.3%. To optimize discharge capacity, a fuzzy parameter setting was generated based on the mathematical model, resulting in a predicted discharge capacity of 398.209 mAh g−1, closely aligned with actual experimental results (394.203 mAh g−1). This work showcases the significance of advanced statistical techniques in elucidating the intricate relationships governing electrochemical performance, particularly in the context of nanocrystalline materials.

Screening of cellulose-degrading bacteria and optimization of cellulase production from Bacillus cereus A49 through response surface methodology

Cellulose-degrading microorganisms hold immense significance in utilizing cellulose resources efficiently. The screening of natural cellulase bacteria and the optimization of fermentation conditions are the hot spots of research. This study meticulously screened cellulose-degrading bacteria from mixed soil samples adopting a multi-step approach, encompassing preliminary culture medium screening, Congo red medium-based re-screening, and quantification of cellulase activity across various strains. Particularly, three robust cellulase-producing strains were identified: A24 (MT740356.1 Brevibacillus borstelensis), A49 (MT740358.1 Bacillus cereus), and A61 (MT740357.1 Paenibacillus sp.). For subsequent cultivation experiments, the growth curves of the three obtained isolates were monitored diligently. Additionally, optimal CMCase production conditions were determined, keeping CMCase activity as a key metric, through a series of single-factor experiments: agitation speed, cultivation temperature, unit medium concentration, and inoculum volume. Maximum CMCase production was observed at 150 rpm/37 °C, doubling the unit medium addition, and a 5 mL inoculation volume. Further optimization was conducted using the selected isolate A49 employing response surface methodology. The software model recommended a 2.21fold unit medium addition, 36.11 °C temperature, and 4.91 mL inoculant volume for optimal CMCase production. Consequently, three parallel experiments were conducted based on predicted conditions consistently yielding an average CMCase production activity of 15.63 U/mL, closely aligning with the predicted value of 16.41 U/mL. These findings validated the reliability of the model and demonstrated the effectiveness of optimized CMCase production conditions for isolate A49.

Enhancing biodiesel yield and purification with a recently developed centrifuge machine: A response surface methodology approach

Biodiesel production processes, such as gravity settling, have limitations in terms of biodiesel yield, purification efficiency, operating time in the separation process, and more extensive equipment. Therefore, this study has focused on using a recently developed centrifuge machine for biodiesel separation to address these challenges due to its compact design, high efficiency, and simplicity. Additionally, this study aimed to optimize the separation efficiency of glycerol from biodiesel using a centrifuge machine, employing response surface methodology (RSM) with central composite design (CCD). The optimum conditions for separating glycerol from biodiesel via centrifuge machine are a rotation speed of 1800 rpm, a mixture flow rate of 192.25 ml/min, and a temperature of 55 °C, respectively. In optimum conditions, 94.52% separation efficiency was achieved. Biodiesel production can be improved, leading to higher yields and greater purity. The utilization of RSM proved valuable in determining the optimum conditions for separation. Furthermore, the machine successfully separated the biodiesel to meet ASTM D6751 and EN 14,214 standards. The results highlight the potential of the centrifuge machine for efficient and reliable biodiesel production, contributing to the advancement of the biodiesel industry.

Optimizing hydrothermal treatment for sustainable valorization and fatty acid recovery from food waste

This study employs response surface methodology and a central composite design (CCD) to optimize hydrothermal treatment (HTT) conditions for the valorization of food waste (FW). Lab-scale pressure reactor-based HTT processes are investigated to detect the effects of temperature (220–340 °C) and resident time (90–260 min) on elemental composition and fatty acid recovery in the hydrothermal liquid. Central to the study is the identification of temperature as the primary factor influencing food waste conversion during the HTT process, showcasing its impact on HTT product yields. The liquid fraction, rich in saturated fatty acids (SFA), demonstrates a temperature-dependent trend, with higher temperatures favoring SFA recovery. Specifically, HTT at 340 °C in 180 min exhibits the highest SFA percentages, reaching up to 52.5 wt%. The study establishes HTT as a promising avenue for nutrient recovery, with the liquid fraction yielding approximately 95% at optimized conditions. Furthermore, statistical analysis using response surface methodology predicts the optimal achievable yields for hydrochar and hydrothermal liquid at 6.15% and 93.85%, respectively, obtained at 320 °C for 200 min.

Optimization of Pb (II) Ion Removal from Synthetic Wastewater Using Dead (Chlorophyta) Macroalgae: Prediction by RSM Method

The Pb2+ ions biosorption removal onto dead biomass of Chlorophyta algae is optimized by employing response surface methodology (RSM). Central composite design (CCD)-based experiments were carried out, and RSM was used to evaluate the results. The effects of contact time (15-120min), with pH solution (2-7), initial lead concentration (25-100 mg/L), biomass dose (0.01-1 g/100 mL), agitation speed (100-300 rpm) on the biosorption process were investigated. The optimal conditions of the experimental, data were pH (5), metal concentration (50mg/L), dosage (0.2g/100mL), agitation speed (200 rpm), and contact time of 120 min with constant particle size (63 mm), which gave 98.88% removal efficiency. All the variables and reactions in the biosorption experiments were evaluated using the desirability function to determine the optimal point at which the desired parameters may be attained. The promising results obtained indicate the potential use of Chlorphyta green macroalgae to treat industrial wastewater polluted with toxic metals.

Three-dimensional Electrocoagulation Process Optimization Employing Response Surface Methodology that Operated at Batch Recirculation Mode for Treatment Refinery Wastewaters

The performance of a three-dimensional electrocoagulation process operated at a batch recirculation mode for treating petroleum refinery wastewater using aluminium as a sacrificial anode, stainless steel as a cathode, and granular activated carbon with metal impregnated carbon (GACMI (Al: Fe)) with mass ratio (2:1) as a third particle electrode was investigated. Effects of operating factors such as the applied voltage (15-30 v), flow rate (50-175 mL/min), pH (4-10), and GACMI dosage (5-10) g/L on the chemical oxygen demand removal were investigated. Using Box-Behnken design (BBD), a mathematical model relating the essential operational parameters to chemical oxygen demand (COD) reduction was constructed. Results showed that the effect of GACMI dosage on the efficiency of COD removal was the major one, where COD removal increased as GACMI dosage increased. However, increasing applied voltage would enhance the performance of the electrocoagulation reaction. Experimental chemical oxygen demand removal of 96.25 % was attained at the optimized conditions (applied voltage=27.7 v, flow rate=128 mL/min, pH=5.6, GACMI dosage= 8.7 g/L). BET-specific surface area, total pore volume, X-ray fluorescence (XRF), energy-dispersive X-ray spectroscopy (EDX), and scanning electron microscopy (SEM) were employed for the characterization of GACMI particle electrodes.

FORMULATING AND CHARACTERIZING AN OIL-IN-WATER PALM OIL FREE FATTY ACID-BASED NANOEMULSIONS FOR CRUDE OIL EXTRACTION PERFORMANCE

Nanoemulsion is a promising medium for chemically enhanced oil recovery (cEOR) due to its ability to reduce interfacial tension and modify the wettability of reservoir rocks. This work focuses on formulating stable oil-in-water (O/W) nanoemulsions through high-energy ultrasonication method, with oleic acid as the primary component and is stabilized with a non-ionic Tween 40 surfactant in distilled water. Systematic experimental designs, employing response surface methodology (RSM), were implemented to develop polynomial models for various responses related to the dynamic and stability properties, and crude oil extraction performance. The p-value indicator (p-value < 0.05) is utilized to assess the significance of the models and independent variables. Overall, the formulation for achieving the lowest surface tension involves 0.41 wt.% oleic acid mixed with 0.81 wt.% Tween 40 at 60 °C. Meanwhile, the highest viscosity attained with 1.0 wt.% oleic acid mixed with 1.0 wt.% Tween 40 at 30 °C. For stable nanoemulsion, the best conditions are 1.69 wt.% oleic acid, sonicated for 15 minutes at 25 °C. Additionally, an optimal condition for effective crude oil extraction is at nanoemulsion preparation with sonication time of 15 minutes and contact time of 12 hours in the immersion experiment. To this end, this work contributes valuable insights into the formulation and characterization of stable oleic acid O/W nanoemulsions for potential EOR applications. The findings enhance understanding of nanoemulsion properties and their potential as effective agents in crude oil recovery.

Experimental Investigation on Magnetic Abrasive Finishing for Internal Surfaces of Waveguides Produced by Selective Laser Melting.

To enhance the surface quality of metal 3D-printed components, magnetic abrasive finishing (MAF) technology was employed for post-processing polishing. Experimental investigation employing response surface methodology was conducted to explore the impact of processing gap, rotational speed of the magnetic field, auxiliary vibration, and magnetic abrasive particle (MAP) size on the quality enhancement of internal surfaces. A regression model correlating roughness with crucial process parameters was established, followed by parameter optimization. Ultimately, the internal surface finishing of waveguides with blind cavities was achieved, and the finishing quality was comprehensively evaluated. Results indicate that under optimal process conditions, the roughness of the specimens decreased from Ra 2.5 μm to Ra 0.65 μm, reflecting a reduction rate of 74%. Following sequential rough and fine processing, the roughnesses of the cavity bottom, side wall, and convex surface inside the waveguide reduced to 0.59 μm, 0.61 μm, and 1.9 μm, respectively, from the original Ra above 12 μm. The findings of this study provide valuable technical insights into the surface finishing of metal 3D-printed components.