Utilizing Response Surface Methodology Research Articles

Numerical investigation and optimization of a multi-stage Tesla-valve channel based photovoltaic/thermal module

As an essential form of solar energy utilization, photovoltaic/thermal modules (PV/T) have higher efficiency than solely photovoltaic or photothermal. With regard to the heat recovery issues of PV/T, a novel thermal management method by utilizing a Tesla-valve channel is proposed. Besides, the effect of channel number, Tesla-valve number, solar irradiation, water inlet velocity, as well as water inlet temperature are analyzed using a thermal-electrical-flow coupling CFD simulation. In comparison to the straight channel and zig-zag channel PV/T, reverse multi-stage Tesla-valve channel based PV/T (MSTV-PV/T) can further enhance the solar cell panel efficiency and reduce thermal stress with decreasing max and average temperature of solar cell panel by over 4.5% and 3%, respectively. Utilizing response surface methodology, the optimization of MSTV-PV/T performance is conducted with respect to both single and multi-objective criteria. Channel number 8 is the optimal design parameter for all optimization objectives, the maximum output thermal energy, output thermal exergy, and output electrical energy/exergy of the proposed MSTV-PV/T module can be achieved to 1376.34W, 76.74 W, and 432.86 W, respectively.

Utilizing response surface methodology (RSM) to predict the mechanical characteristics of concrete incorporating treated recycled construction and demolition waste aggregate (CDW) and discarded reverse osmosis (RO) membrane

Utilizing response surface methodology (RSM) to predict the mechanical characteristics of concrete incorporating treated recycled construction and demolition waste aggregate (CDW) and discarded reverse osmosis (RO) membrane

Optimal design and modelling of sustainable bio-catalytic enzyme for wastewater treatment using response surface methodology and artificial neural network

ABSTRACT The accessibility of various wastewater treatment systems has become increasingly prominent in current times, coinciding with a rising concern regarding the substantial content of food waste that poses a significant challenge in waste management. In this context, ecoenzymes have emerged as a promising technique for water treatment due to their remarkable efficiency in pollutant removal and cost-effectiveness. Nevertheless, many experts encounter difficulties in determining the optimal combination of ecoenzyme variables to maximize pollutant removal. The objective of this study is to apply a comprehensive approach utilizing Response Surface Methodology (RSM), Artificial Neural Networks (ANN), and Multi-objective Genetic Algorithm (MOGA) methods for the modeling and optimization of ecoenzyme-based water treatment processes. The research outcomes demonstrate a noteworthy alignment between the actual removal rates of Total Suspended Solids (TSS), Volatile Suspended Solids (VSS), and Total Ammonia Nitrogen (TAN) with the values predicted by both RSM and ANN models, validating the robustness of the regression analysis (R2 >0.95). From the optimization results, it is elucidated that to attain the maximum removal of TSS, VSS, and TAN, the treatment process should be conducted over a period of 3.5 days, employing specific enzyme concentrations of 0.07 units/ml for protease, 0.027 units/ml for amylase, and 0.36 units/ml for lipase. This study employed machine learning approaches and MOGA optimization to predict the optimum ecoenzyme properties for maximum wastewater removal utilizing the concept of a low-cost, sustainable purification technology.

Unveiling the phytochemical profiles, selective bioactivity potential, and molecular docking study of bioactive compounds with target proteins using optimized bark extracts of Grewia asiatica L.

The current study aimed to explore the phytochemicals, estimate the anti-inflammatory, antioxidant, antimicrobial, and anticancer potentials of polyphenol enriched methanolic bark extract of Grewia asiatica (PEMGa), and perform molecular docking studies with identified phytocompounds. Here, we utilized response surface methodology (RSM) with a Box Behnken design (BBD) to enhance the phenolic content of the methanolic extract from G. asiatica bark by optimizing three crucial parameters like extraction time (h.), temperature of extraction (°C), and solvent ratio (% v/v of methanol: water). Phytochemical quantification of PEMGa illustrated that the bark part contains a good amount of therapeutically potent phytochemical groups like phenolics, flavonoids, and tannins. Additionally, through HPLC analysis, eight compounds belonging to the phenolic and flavonoid groups have been quantified from PEMGa. By GC-MS (Gas chromatography–mass spectrometry) analysis of PEMGa, eleven phytochemicals were identified. Moreover, employing in-vitro bioactivity studies, PEMGa has unveiled its remarkable potential as an anti-inflammatory, antimicrobial, antioxidant, and anticancer agent. During the in-silico molecular docking study, out of eleven phytocompounds identified by the GC-MS study, three compounds, namely, γ-sitosterol, stigmasterol, and campesterol, formed the most stable docked complex with anti-inflammatory, antimicrobial, and antioxidant target proteins. The present study provides justification for the bark part of G. asiatica as a rich source of potent phytochemicals, and its potential against oxidative stresses, inflammations, cancer, and microbial infections.

Recycling and reusing potential of disposable low-density polyethylene plastic waste for flexible paver tile construction for outdoor application

Plastic waste disposal has escalated into a serious global concern due to the non-biodegradable nature of plastics, which are composed of high-molecular-mass organic polymers along with other ingredients. Therefore, this study focuses on reusing and recycling LDPE plastic waste as a binding agent in paver tile production. This aligns with global sustainability goals by promoting resource efficiency and reducing waste generation. The investigation aims to address the environmental impact of plastic waste by finding sustainable solutions for its management. This includes exploring the feasibility and viability of using LDPE plastic waste in paver tile production as a means of recycling and reusing locally collected waste. The LDPE waste plastic collection, identification, milling, and melting at 170 °C. Subsequently, the sampled sand, sieved to a size of ≤0.75 mm, was blended with molten plastic in a specified proportion and then molded to create paving tiles using a hydraulic press machine. The researchers utilized response surface methodology (RSM) combined with Box-Benken designs (BBD) to optimize three key experimental parameters (plastic-to-sand ratio: 10 %, 25 %, 40 %; time: 2, 5, 8 min, pressure: 1, 3, 5 MPa) influencing mechanical properties of paver tiles, including water absorption (WA), flexural strength (FS), and compressive strength (CS). The result revealed that the optimal combination of 25 % waste plastic, 5 min, and 3 MPa of pressure resulted in a maximum flexural strength (FS) of 3.689 MPa and compressive strength (CS) of 4.141 MPa, with an average water absorption (WA) of 0.322 %. Therefore, the mechanical properties of the developed tiles met the desired standard. In conclusion, the mechanical qualities of the tiles were promising, indicating that reusing waste LDPE plastic to create paver tiles presents an appealing option for plastic waste disposal. The composite paver tiles exhibited promising attributes for outdoor applications, such as park pavement and outdoor public spaces, owing to their favorable mechanical properties and low water absorption.

Utilizing response surface methodology for the microstructural examination of CeO2/GNP composite coating applied via air plasma spraying and post-treated with spark plasma sintering

CeO2/GNP coatings were fabricated using a three-step process: high-energy ball milling, spray-drying, and air plasma spray (APS) deposition. Spark plasma sintering (SPS) was employed for post-treatment to densify the coatings. Response surface methodology (RSM) was employed to optimize SPS processing parameters, including temperature, pressure, and holding time, for minimizing porosity. A quadratic model was developed and validated using analysis of variance (ANOVA) to determine the influence of the independent variables. A regression equation was derived to predict porosity based on the process parameters. Scanning elctron microscopy(SEM) measurements revealed a significant 16 % porosity reduction in the densified coating. Interlamellar cracks and microcracks were significantly reduced, improving coating integrity and interface bonding. Enhancement of SPS parameters indicated that higher temperature and pressure combined with shorter holding times yielded minimal porosity. The study demonstrated that higher pressures exhibited a stronger impact on porosity at higher temperatures, while the effect of temperature was more pronounced at a holding time of 4 min. The interaction between pressure and holding time highlighted the importance of considering both parameters for effective porosity control in SPS. The constraints for each parameter have been defined through the optimization process. The set temperature is 950 °C, the pressure is established at 30 MPA, and the duration of the holding time is 4 min.

Optimization of microalgae protein extraction from Scenedesmus obliquus and investigating its functional properties

The objective of this work was to evaluate alkaline treatment with enzymatic approaches for the optimal extraction of proteins from Scenedesmus obliquus microalgae. The experiments were designed with an emphasis on the alkaline treatment period and the enzyme-to-substrate ratio utilizing response surface methodology (RSM) with central composite design (CCD). Higher enzyme concentrations led to better extraction rates and efficiency, according to the findings. Cellulase demonstrated extraction efficiencies between 16.88% and 21.42%, but the multi-enzyme complex had efficiencies ranging from 15.28% to 27.87%. With an extraction rate of 19.13%, alkaline treatment was less advantageous than enzymatic treatment due to its longer procedure. Microalgal proteins' functional characteristics were also looked at. These proteins demonstrated foaming capacity, oil absorption, and emulsification ability, making them suitable alternatives to animal proteins in food systems such as egg white and soybean. Although microalgal protein powder had lower foam capacity (20%), stability (25%), fat absorption capacity (124%), and emulsification ability compared to egg white powder, it still exhibited favorable functional properties, highlighting its potential for various food applications. Further enhancement of the functional properties can be achieved by optimizing the environmental conditions during extraction.

Amputation of Remazol brilliant blue dye on crosslinked chitosan hydrogel: Statistical treatment and experimental evaluation

The primary aim of this research is to comprehensively assess the applicability of chitosan biopolymer towards water treatment application and to enhance its adsorption capacity towards Remazol brilliant blue R-19 dye. This has been achieved through physical modification to obtain the material in hydrogel form and chemical modification by crosslinking it with barbituric acid. The characterization of the resulting Chitosan-barbituric acid hydrogel (CBH) was carried out using various analytical techniques such as SEM-EDX, FT-IR, TGA-DTA, XRD, and BET. CBH was employed as the adsorbent to eliminate R-19 dye from aqueous media. Utilizing response surface methodology (RSM), the parameters were fine-tuned, leading to the achievement of more than a 95% removal for R-19 dye. The adsorption behavior closely adhered to the Langmuir isotherm and pseudo-second-order kinetics. An interesting observation indicated that the rise in temperature leads to rise in adsorption capacity of CBH. The maximum adsorption capacities evaluated at 301.15 K, 313.15 K, 318.15 K, and 323.15 K were 566.6 mg g−1, 624.7 mg g−1, 671.3 mg g−1, and 713.5 mg g−1 respectively, in accordance with the Langmuir isotherm model. Examining the thermodynamics of the adsorption process revealed its spontaneous nature (ΔG = −21.14 to −27.09 kJ mol−1) across the entire temperature range. Furthermore, the assessment of the isosteric heat of adsorption (ΔHads) was conducted using the Clausius–Clapeyron equation, with results indicating an increase in ΔHads from 1.85 to 2.16 kJ mol−1 with temperature rise from 301.15 K to 323.15 K due to augmented surface loading. This suggested the existence of lateral interactions between the adsorbed dye molecules. The potential of adsorbent for regeneration was investigated, demonstrating the ability to reuse the material. Sustainability parameter calculated for synthesis process reflected a notably low E-factor value of 0.32 demonstrated the synthesis is environment friendly.

Utilization of response surface methodology to optimize the mechanical behaviour of flax/nano TiO2/Epoxy based hybrid composites under liquid nitrogen environment

Linum usitatissimum commonly known as flax fibers, emerges as a promising reinforcement phase for artificial polymer resins, boasting ecological benefits, low density, and easy accessibility. However, the mechanical behavior of such composites hinges crucially on factors such as fiber mat thickness, nanoTiO2 filler content, and the application of cryogenic treatment. Addressing this complex interplay, this study employs a hand lay-up technique for composite construction, subjecting nanocomposite plates to the challenging liquid nitrogen conditions at 77 K post-manufacture. Recognizing the need for an optimized approach, Response Surface Methodology (RSM) based on Box-Benhken designs is employed to enhance the mixing features of linum usitatissimum polymer composites. The study calculates anticipated mechanical strength values through rigorous ANOVA inferential analysis, uncovering the pivotal roles played by fiber mat thickness, nanofiller content, and cryogenic treatment in the two feature interactions (2FI) model components. The methodology proves robust with high R2 values (0.9670 for tensile, 0.9845 for flexural, and 0.9670 for interlaminar shear strength) consistently aligning with experimental findings. The study culminates in identifying optimized parameters for maximal mechanical properties—300 gsm flax fiber thickness, 5 wt.% nano TiO2 concentration, and a 15-min cryogenic treatment—a result that advances our understanding of fundamental factors influencing composite performance and provides practical guidelines for applications in fields requiring superior mechanical strength in challenging environments.

Valorization of sesame (Sesamum indicum L.) seed coats: Optimization of polyphenols’ extraction using Ired-Irrad® and assessment of their biological activities

Sesame (Sesamum indicum L.) seed coat (SSC) is a by-product generated during the production of sesame paste, known as tahini. Research has demonstrated that this by-product is abundant in valuable nutritional compounds. Various extraction methods are employed to enhance the value of industrial waste by recovering its bioactive compounds. The study aims to optimize the extraction of polyphenols utilizing an infrared technique Ired-Irrad® (IR), in comparison to the water bath (WB) extraction. To optimize the extraction of polyphenols from SSC using both the IR and WB extraction methods, the study utilized Response Surface Methodology (RSM). Under optimal conditions, IR extraction resulted in an improved polyphenol yield, which was 20% higher than that obtained using WB extraction. Similarly, the antiradical activity, quantified as mg of Trolox equivalent per milliliter, increased from 0.58 mg TE/mL in the WB extract to 0.68 mg TE/mL in the IR extract. The phytochemical profile of the IR and WB extracts was examined through High-Performance Liquid Chromatography (HPLC). The major polyphenols identified in both extracts were the flavonoids rutin (3.87 mg/L in IR, 1.72 mg/L in WB) and catechin (3.05 mg/L in IR, 1.32 mg/L in WB). The IR extract revealed the highest yield of polyphenols among the majority of compounds, compared to WB. The lyophilized SSC extracts obtained through both the IR and WB methods demonstrated the most effective antibacterial activity against Listeria monocytogenes, with a minimal bactericidal concentration (MBC) value exceeding 100 mg/mL. However, minor antibacterial effects were detected against the Gram-negative strains, Salmonella Typhimurium and Escherichia coli O157:H7, for extracts obtained with both the IR and WB methods.

Numerical modeling and optimization of tube flattening impacts on the cooling performance of the photovoltaic thermal system integrated with phase change material

In this research, a computational fluid dynamics-based numerical simulation is performed to evaluate the influence of tube flattening on the cooling performance of a photovoltaic thermal system integrated with phase change material. Such a study is executed to obtain the four evaluation parameters, including average photovoltaic panel temperature, phase change material melting percentage, tube pressure drops, and the difference between the highest and lowest temperature points on the photovoltaic panel. To obtain the optimum percentage of tube flattening to optimize the cooling performance of the systems, multi-objective optimization by utilizing response surface methodology is done by considering some design requirements, including minimizing average photovoltaic panel temperature, maximizing phase change material melting percentage, minimizing tube pressure drops, and minimizing the difference between the highest and lowest temperature points on the photovoltaic panel. Finally, a parametric analysis is done to explore how certain critical factors (solar radiation, fluid mass flow rate, phase change material thermal conductivity, phase change material enthalpy of fusion, and phase change material melting point) affect the efficiency of the systems. The findings indicate that as tube flattening rises from 0 % to 75 %, the average photovoltaic panel temperature and the difference between the highest and lowest temperature points on the photovoltaic panel decrease which is a positive effect. Conversely, increasing the tube flattening results in an increase in the tube pressure drops and a reduction in the phase change material melting percentage. These changes adversely affect the cooling performance. Considering these impacts and conducting an optimization process, the ideal tube flattening value is 54.78 %. In this optimized state, the average photovoltaic panel temperature reaches 55.21 ˚C, phase change material melting percentage comprises 42.54 %, tube pressure drops is 184.8 Pa, and the difference between the highest and lowest temperature points on the photovoltaic panel is 33.42 ˚C.

Experimental investigation of ultrasonic assisted coating on three-point bending behavior of 3D printed polymeric bone plates for biomedical applications

3D printed Poly Lactic Acid (PLA) bone plates exhibit limited three-point bending strength, restricting their viability in biomedical applications. The application of polydopamine (PDM) enhances the three-point bending strength by undergoing covalent interactions with PLA molecular structure. However, the heavy nature of PDM particles leads to settling at the container base at higher coating solution concentrations. This study investigates the impact of ultrasonic-assisted coating parameters on the three-point bending strength. Utilizing Response Surface Methodology (RSM) for statistical modeling, the study examines the influence of ultrasonic vibration power (UP), coating solution concentration (CC), and submersion time (TIME). RSM optimization recommended 100 % UP, 6 mg/ml CC, and 150 min TIME, resulting in maximum three-point bending strength of 83.295 MPa. Microscopic images from the comparative analysis revealed non-uniform coating deposition with mean thickness of 6.153 µm under normal coating. In contrast, ultrasonic-assisted coating promoted uniform deposition with mean thickness of 18.05 µm. The results demonstrate that ultrasonic-assisted coating induces PDM particle collision, preventing settling at the container base, and enhances three-point bending strength by 7.27 % to 23.24 % compared to the normal coating condition. This study emphasizes on the potential of ultrasonic-assisted coating to overcome the limitations of direct immersion coating technique.

Machine learning optimization of bio-sandcrete brick modelling using response surface methodology

In this study, raw grinded groundnut shell (RGGNS) was used as a fine aggregate in the brick industry to reuse agricultural waste in building materials. In this study, an experimental approach was used to examine a new cement brick with raw groundnut shells integrated with compressive strength, water absorption and dry density optimization utilizing response surface methodology (RSM). The raw ground-nut shell content improved the fine aggregate performance of the 40%, 50%, and 60% samples. The 28-day high compressive strength with the raw ground-nut shell was 6.1 N/mm2 maximum, as needed by the technical standard. Samples made from 40%, 50%, and 60% raw groundnut shells yielded densities of 1.7, 2.2, and 1.9 kg/cm3 for groundnut shell (GNS) brick, respectively. A product's mechanical properties meet the IS code standard’s minimum requirements. RSM was then utilized to develop a model for the addition of raw groundnut shell to concrete. R-square and Adeq precision values indicated that the results are highly significant, and equations for predicting compressive strength, water absorption, and dry density have been developed. In addition, optimization was performed on the RSM findings to determine the efficiency optimization of the model. Following the optimization results, experiments were conducted to determine the applicability of the optimized model.

Aspergillus niger fermentation of cocoa pod husk for increased total crude protein utilizing response surface methodology

Aspergillus niger fermentation of cocoa pod husk for increased total crude protein utilizing response surface methodology

Modeling and optimization of engineering parameters for the treatment of textile wastewater using modified clay/TiO2/ZnO

Abstract The objective of this project was to develop a new hybrid nanocomposite that would maximize chemical oxygen demand (COD) and color removal from effluent from the actual textile industry to overcome the water crisis brought on by increasing industrialization and urbanization. This study is the first to use modified clay/TiO2/ZnO nanocomposites for adsorbing actual textile wastewater treatment. The adsorption capacity from the dye removal was evaluated to optimize the three engineering parameters (pH, adsorbent dose, and time) utilizing response surface methodology. An isotherm kinetic intra-particle diffusion model was developed to study the sorption phenomena. The best fit for sorption was provided by Langmuir isotherms, with an R2 of better than 0.99. The sorption process follows the pseudo-second-order kinetics that favors chemisorption, following kinetic theory. The sorption process is endothermic, viable, and spontaneous in nature, according to a thermodynamic study. At the optimal pH (5.5), adsorbent dose (0.55 g), and time (75 min), the maximum COD and color removal were achieved to be 94 and 91% with a maximum sorption capacity of 660 mg/g. In this optimization, the adj. R2 and R2 correlation coefficients were calculated as 0.7213 and 0.7653, respectively. The hybrid composite seems to be effective for treating real effluents.

Optimization and Characterization of Liquid Smoke Produced by Terminalia catappa Wood Pyrolysis and its In Vitro Antifungal Activity

This research utilized response surface methodology (RSM) to explore how the yield of liquid smoke obtained from ketapang wood (Terminalia catappa) is influenced by the size of wood particles and the temperature of pyrolysis. Gas chromatography-mass spectrometry (GC-MS) was used to characterize the liquid smoke. To assess liquid smoke’s antifungal effects, a petri dish bioassay was conducted using 1.0-4.0% (v/v) concentrations against Schizophyllum commune. RSM was applied to optimize vinegar from T. catappa by varying the wood particle size and the pyrolysis temperature. The optimal yield, 24.67%, was obtained with a 3.22 mm particle size and a 425°C pyrolysis temperature. The liquid smoke produced at 400-450°C completely inhibited of S. commune growth at 2.0-4.0%. The primary components of the liquid smoke at 400°C were 2-methoxy- phenol (24.85%), creosol (8.39%), 4-ethyl-2-methoxy- phenol (7.21%), 2-5-methyl-furancarboxaldehyde (4.55%), and 4-ethyl-2-methoxy-phenol (3.74%). The primary components at 425°C were 2-methoxy-phenol (25.60%), creosol (15.15%), 5-methyl-2 furancarboxaldehyde (12.75%), and 2,6-dimethoxy-phenol (9.31%). At 450°C, the main components were 2-methoxy-phenol (25.26%), 4-ethyl-2-methoxy-phenol (8.46%), creosol (8.40%), 5-methyl-2-furancarboxaldehyde (4.02%), and 4-ethyl-2-methoxy-phenol (3.98%).

Modeling Tetracycline Adsorption onto Blast Furnace Slag Using Statistical and Machine Learning Approaches

Ground granulated blast furnace slag (GGBS) is a primary industrial waste product of iron production, and its improper disposal has been a serious environmental problem. This study aims to modify the GGBS using oxalic acid (GGBS-Ox) for the adsorption of tetracycline (TC) from an aqueous solution. GGBS-Ox was synthesized and characterized via FTIR, XRD SEM, XPS, BET, and DLS. The effects of process parameters, involving initial solution pH, stirring speed, and contact time, are evaluated by utilizing response surface methodology (RSM), artificial neural network (ANN), and random forest (RF) based models. The experimental results indicate that the removal efficiency of TC is significantly affected by the initial pH of the solution. The RSM, ANN, and RF models accurately simulated the experimental data, as indicated by the high coefficient of determination (R2), which was 0.98, 0.95, and 0.98, respectively. Additionally, kinetics, isotherm, and thermodynamic models were evaluated for the adsorption of TC onto GGBS-Ox. The findings of this study demonstrated the utilization of GGBS-Ox as an efficient and sustainable adsorbent for the treatment of TC and can be considered as a potential adsorbent for wastewater treatment.

Effect of Sulfide and Chloride Ions on Pitting Corrosion of Type 316 Austenitic Stainless Steel in Groundwater Conditions Using Response Surface Methodology.

This study investigates the corrosion resistance of Type 316 stainless steel as a candidate material for radioactive waste disposal canisters. The viability of stainless steel is examined under groundwater conditions with variations in pH, bisulfide ions (HS-), and chloride ions (Cl-) concentrations. Utilizing response surface methodology, correlations between corrosion factors and two crucial response variables, passive film breakdown potential and protection potential, are established. Cyclic potentiodynamic polarization tests and advanced analytical techniques provide detailed insights into the material's behavior. This research goes beyond, deriving an equation through response surface methodology that elucidates the relationship between the factors and breakdown potential. HS- weakens the passive film and reduces the pitting corrosion resistance of the stainless steel. However, this study highlights the inhibitory effect of HS- on pitting corrosion when Cl- concentrations are below 0.001 M and at equivalent concentrations of HS-. Under these conditions, immediate re-passivation occurs from the destroyed passive film to metal sulfides such as FeS2, MoS2, and MoS3. As a result, no hysteresis loop occurs in the cyclic polarization curve in these conditions. This research contributes to the understanding of Type 316 stainless-steel corrosion behavior, offering implications for the disposal of radioactive waste in geological repositories.

Encapsulation of Bioactive Compounds from Germinated Mung Bean by Freeze-Drying, Release Kinetics, and Storage Stability.

This research explores the application of germinated mung bean extract, rich in GABA (Gamma-aminobutyric acid) and polyphenols, in enhancing human health. Recognizing the instability of these bioactive compounds in environmental conditions, encapsulation emerges as a pivotal technique to broaden their applications in food and pharmaceuticals. Utilizing response surface methodology and Box-Behnken design, the freeze-drying formulation for encapsulating the aqueous extract was optimized. Second-order polynomial models were developed, exhibiting statistical adequacy in predicting key variables such as encapsulation efficiency for GABA (EE-GABA) and total polyphenol content (EE-TPC), as well as encapsulation yield for GABA (EY-GABA) and total polyphenol content (EY-TPC). The established optimal formulation was validated, resulting in predicted values for EE-GABA, EE-TPC, EY-GABA, and EY-TPC. The release kinetics of encapsulated particles were investigated, highlighting the suitability of the Korsmeyer-Peppas and Higuchi models. Assessing the stability of the encapsulated powder under varying temperatures and humidities revealed degradation rates, half-life, and activation energy, with moisture equilibrium established at 4.70%, indicative of long-term stability. In conclusion, the encapsulated germinated mung bean powder demonstrates high stability, making it a promising candidate for integration into food products and functional ingredients.

Optimization of dissipative-magneto highly reactive Casson nanoliquid flow with an electric field utilizing response surface methodology

ABSTRACT The studies of a first-order chemical reaction have been presented in various published investigations, while the nth chemical reaction should be examined. Also, optimizing the effect of process variables is important for a clear understanding of the heat transfer mechanism. Therefore, this paper presents an optimization and sensitivity analysis for the heat transfer and shear rate utilizing response surface methodology (RSM) for dissipative-magneto highly reactive Casson nanoliquid flow with an electric field. The irreversibility property is disclosed, and both active and passively controlled cases are assumed. The governing system is transformed into similar forms and solved using the Blottner technique together with the Finite Difference Method (FDM). The main attraction of the current investigation is to optimize the rate of heat transfer as well as the shear rate by utilizing robust statistical approaches. Further, sensitivity analysis for the significant factors is, also, demonstrated for the proposed responses. The major outcomes revealed that the skin fraction is enhanced as the magnetic parameter is altered, while the electrical coefficient causes a reduction in the velocity gradients. In the active-controlled case, the power index of the chemical reaction reduces the mass transfer rate.