Experimental Design Methodology Research Articles

Optimization of Extraction Conditions of Polyphenols and Flavonoids from Olax subscorpioidea leaves, a Medicinal Plant Traditionally Used in Korhogo (Cote d’ivoire)

Secondary metabolites, including polyphenols and flavonoids, play a key role in the expression of the active principles of several medicinal plants from Côte d'Ivoire, such as Olax subscorpioidea Oliv. This study was initiated to help improve conditions for extracting polyphenols and flavonoids from Olax subscorpioidea Oliv leaves harvested in Korhogo. Experimental design methodology was used. The effect of four independent variables on polyphenol and flavonoid content was evaluated: extraction time (12h-24h), evaporation temperature (45°C - 55°C), plant material-solvent ratio (1/20 g/mL - 1/5 g/mL) and ethanol proportion (20% - 100%). The Central Composite Design (CCD) was used to optimize responses after factor screening using the Plackett and Burman design. Optimum extraction conditions were obtained with an ethanolic proportion of 88.29% and 17g of Olax subscorpioidea Oliv leaves dissolved in 100 mL ethanol. The experimental values (96.31 ± 5.29 mg Eq AG/g for polyphenols and 62.44 ± 4.58 mg Eq Q/g) were close to those expected (94.51 mg Eq AG/g for polyphenols and 58.22 mg Eq Q/g for flavonoids), confirming the relevance of the mathematical model used and the success of the response surface methodology in optimizing the extraction conditions of the system studied. These results show that by taking extraction conditions into account in this preliminary study, we can optimize the quantities of secondary metabolites of therapeutic interest.

Analysis of 3k Experiments Applied to Railway Braking: Influence of Contaminants and Train Speed

The presence of contaminants influences braking efficiency in the railway system because it alters the adhesion at the wheel–rail interface. It is essential to study this phenomenon, as contaminants reduce the friction between wheels and rails, which impacts braking and transport safety. In addition, these contaminants increase the risk of derailments. The objective of the research was to determine the impact of different contaminants and operating speeds on the critical braking system’s responses. Using the 3k full factorial experimental design methodology, with analysis of variance (ANOVA) and linear and quadratic regressions, visualized using surface graphs, the effects of three operating conditions were studied: clean rails, with sand and sawdust, and driving the train at three operating speeds. These conditions gave rise to variations in braking distances, maximum creep, wheel slip times, and maximum peaks of electric current when braking in each experiment. The tests were carried out on the straight section of a β-shaped track and a railway vehicle, designed at a scale of 1:20. The analysis reveals that the braking distance increases significantly with surface roughness (clean track < sawdust < sand). At 0.75 m/s, the sawdust track reduces braking distance by 21% compared with the clean track; at 1.00 m/s, the reduction is 19%; and at 1.30 m/s, it is 35%.

Assessment of simultaneous removal of salt and dye by utilizing capacitive deionization and UV-electro oxidation hybrid process in saline wastewater treatment

In this research, the goal was simultaneous elimination of salt (NaCl) and dye (C·I Acid Orange 7 or AO7) through integration of capacitive deionization (CDI) technique with UV-based electrochemical advanced oxidation process (UV-EAOP). To optimize salt adsorption capacity (SAC) of MnO2 electrode, Taguchi's experimental design methodology was employed to fine-tune synthesis parameters, including bath temperature, current density, and precursor concentrations. BiOCl was synthesized and implemented as an anode to bolster AOP's effectiveness. Several experiments were conducted to analyze the effects of applying the combined AOP and CDI. The findings revealed that parameter optimization improved SAC, and the application of UV irradiation decreased electrode's SAC. Furthermore, it was observed that AO7 could enhance SAC while lowering salt adsorption rate (SAR). More importantly, the combined application of CDI and AOP resulted in superior pollutant removal efficiency and improved SAC, despite reduced SAR. Finally, color was entirely eliminated after 90 min, and the generated species were recognized by GC–MS. Additionally, a possible pathway for AO7 degradation was suggested based on the generated species.

Pilot study protocol evaluating the impact of telerobotics interactions with autistic children during a Denver intervention on communication skills using single-case experimental design

IntroductionFor several years, studies have been conducted on the contribution of social robots as an intervention tool for children with autism spectrum disorder (ASD). One of the early intervention models...

Optimizing dry milling of stir-cast and heat-treated AZ80 magnesium alloy using multiple criteria optimization technique: an experimental study.

The primary aspects of this research are to evaluate surface roughness, cutting force, and material removal rate and optimize it with dry milling process parameters for heat-treated and stir-cast AZ80 magnesium alloy. Multiple methodologies are utilized in the research, which includes the Integration of design of experiments-response surface methodology for experimental design with the technique for order of preference by similarity to ideal solution for multi-criteria optimization. In order to evaluate the effect of process parameters on the response, the experimental design manipulates the depth of cut, feed rate, and cutting speed in a systematic manner. An evaluation of the machined surface's quality is conducted via surface roughness measurements. Likewise, insights into the forces exerted during milling can be obtained through continuous monitoring of cutting forces. The calculation of material removal rate is predicated on weight reduction. The interaction between the depth of cut and feed rate has a significant impact on the critical-to-quality characteristics of the alloy, which has contribution percentage greater than 25%. This finding validates that despite the heat-treated alloy having a similar composition to the as-cast alloy (where the closeness coefficient is 0.9843), the optimal process parameters of the former are not applicable to the latter. Nevertheless, the technique used to prepare the specimen has no bearing on the material removal rate, which is a process parameter-specific effect.

Enhancing skimmed milk powder functionalities through multicriteria optimization of outlet drying air temperature and spraying air pressure

This study investigated the effects of spraying air pressure and outlet air temperature on the physicochemical and functional properties of skimmed milk powder. Experimental design methodology showed that higher outlet air temperatures improved dry matter content, gelation ability, and flowability, but strengthened colour, moisture sensitivity, and favoured protein denaturation. Spraying air pressure primarily influenced particle size, affecting powder rheological properties and colour. This study highlights the importance of controlling drying parameters to optimize powder properties. The use of a genetic evolutionary algorithm in the optimization process allowed the simultaneous improvement of several functionalities of skimmed milk powder. The findings of this study can contribute to the development of enhanced powders with tailored properties for specific industrial applications.

Multiobjective design of automated order fulfillment systems: A case study for an existing surgical complex

We present a case study that introduces a systematic framework for designing an automated guided vehicle (AGV) order fulfillment system. The multi-stage framework integrated discrete event simulation (DES), super-efficiency data envelopment analysis (S-DEA) model, and Design of Experiments (DOE) methodologies for the design of an AGV system in an existing large-scale surgical complex within a comprehensive hospital in Singapore. Performance metrics derived from this model were consolidated into a single relative efficiency score using the S-DEA model. This efficiency score was then utilized in a DOE methodology, combined with a post-hoc model selection process, to robustly identify appropriate models for evaluating alternative system designs. The proposed framework optimizes AGV deployment by first identifying opportunities for AGVs to add value within the surgical system through a value-stream mapping approach. It then derives the optimal system design by balancing cost efficiency, manpower reallocation, and order fulfillment rates, facilitated by the S-DEA model augmented with the DOE approach and post-hoc model selection. Application of this framework to the surgical complex revealed several insights that can significantly enhance AGV efficiency prior to actual deployment. However, a key limitation of this case-study-based approach is its limited generalizability across different systems. Despite this, the methodology provides a robust foundation for AGV system design in similar healthcare environments.

Deep optimal experimental design for parameter estimation problems

Abstract Optimal experimental design is a well studied field in applied science and engineering. Techniques for estimating such a design are commonly used within the framework of parameter estimation. Nonetheless, in recent years parameter estimation techniques are changing rapidly with the introduction of deep learning techniques to replace traditional estimation methods. This in turn requires the adaptation of optimal experimental design that is associated with these new techniques. In this paper we investigate a new experimental design methodology that uses deep learning. We show that the training of a network as a Likelihood Free Estimator can be used to significantly simplify the design process and circumvent the need for the computationally expensive bi-level optimization problem that is inherent in optimal experimental design for non-linear systems. Furthermore, deep design improves the quality of the recovery process for parameter estimation problems. As proof of concept we apply our methodology to two different systems of Ordinary Differential Equations.

Factorial design methodology for synthesizing zeolites: A critical review

AbstractThis review shows an outlook about several works which have used the factorial design methodology for synthesizing zeolites and mesoporous materials, included the use of wastes as sources of silicon and aluminum. In the bibliography several interesting works were identified with a complete development of the factorial design methodology. However, there are other works that showed a limited statistical analysis of the results. In spite of these issues, their contribution in the advance of synthesis of zeolites is important. Moreover, different ways to measure the crystallinity were detected being the X‐ray diffraction (XRD) the most used technique. This work also gives a proposal of the complete factorial design methodology as a guide in future works for synthesizing zeolites or zeo‐types materials. This work presents a detailed review of the methodology of designing experiments for the synthesis of zeolite or zeo‐type materials, where it has been shown and analyzed the type of design used, because the choice of a design involves a large number of experiments or few experiments thus facilitating the production of zeolite, in addition to the factors that influence the synthesis give information of the type to obtained zeolites, also includes a guide for applying this methodology. Experiment design methodology can help to produce high quality zeolites from virgin raw material or waste that impact the economy of the zeolite industry.

Optimizing propylene production via acetone hydrodeoxygenation: Insights from catalytic studies with Cu/γ-Al2O3 and Hβ zeolite

Propylene is a crucial light olefin in the petrochemical industry and can be produced via acetone hydrodeoxygenation, which involves two sequential reactions: first, acetone undergoes hydrogenation catalyzed by metallic sites, followed by the dehydration of the resulting isopropanol catalyzed by acidic sites. In this study, propylene production through acetone hydrodeoxygenation was investigated using a physical mixture of 35 wt% Cu/γ-Al2O3 and Hβ zeolite to investigate how various reaction parameters affect acetone conversion and propylene yield. Using the experimental design methodology, empirical models were developed to correlate acetone conversion (Xacet) and propylene yield (Yprop) with the ratio of 35 wt% Cu/γ-Al2O3 to Hβ (CR), total catalyst weight (Cw), hydrogen volumetric flow rate (FH2) and reaction temperature (T). The maximum propylene yield achieved in the catalytic tests was 73.46 %. A long-term test demonstrated the catalyst's reusability, remaining active even after 22 hours of reaction with only a slight decrease in propylene yield. Analysis of the experimental data revealed that increasing T and Cw positively affected propylene yield, whereas higher CR and FH2 had negative effects. According to the Pareto chart, reaction temperature was the most influential variable for propylene yield, followed by CR, FH2 and Cw. For acetone conversion, the order of significance among the variables was T >CR >Cw >FH2.

Design of experiments investigation into the production of all cellulose composites using regenerated cellulosic textiles

All cellulose composites (ACCs) can be produced from native and man-made cellulosic fibres; use of the latter provides an additional application for waste-derived regenerated fibers. ACCs were prepared using an ionic liquid dissolution method, utilizing a regenerated cellulose (Tencel) textile, with and without an interleaf cellulosic film. A design of experiments methodology was applied to explore process-property relationships; concentration of the ionic liquid and the processing time and temperature were investigated. It was found that the film remained in-between the textile layers, rather than penetrating the fiber assembly, in contrast to our previous work on cotton-based ACCs. This is due to the structural differences between Tencel and cotton fabric. A multi-response optimization was conducted through a central composite face centered strategy, which captured the film system more strongly. Optimized processing conditions were identified, yielding a Young’s modulus and strain-to-failure of 5.3 GPa and 3.5% respectively, validated through in-lab samples.

Betulin-NLC-hydrogel for the Treatment of Psoriasis-like Skin Inflammation: Optimization, Characterisation, and In vitro and In vivo Evaluation.

Psoriasis is a chronic inflammatory skin disorder that poses significant challenges regarding effective and targeted drug delivery. Bioactive substances like betulin have shown tremendous utility in treating these conditions; however, they pose limited utility owing to their physicochemical characteristics. Here, we aimed to develop a novel topical dosage form for treating psoriasis, utilising betulin-loaded solid lipid nanoparticles (NLCs) incorporated into a hydrogel matrix. The optimization of the formulation was meticulously conducted using a design of experiments methodology, and its diverse physicochemical attributes were thoroughly examined. Evaluating betulin's in vitro release pattern from the NLC-hydrogel demonstrated consistent and regulated drug release properties. Additionally, the formulation demonstrated improved skin penetration abilities as determined by in vitro skin permeation experiments employing Franz diffusion cells- furthermore, the therapeutic effectiveness of the betulin-NLC-hydrogel was assessed by an in vivo experiment carried out using an imiquimod-induced psoriasis-like skin inflammation model in BALB/c female mice. The NLCs exhibited a pH of 5.67±0.86, particle size of 148.16±12.66 nm, and zeta potential of -22.84±2.37 mV, ensuring stability and suitability for topical use. The gel, with a pH of 6.05±0.43 and viscosity of 17550±120 cPs, showed enhanced skin hydration and lipid restoration. Drug release studies indicated a slower release from NLCs and gel, improving skin retention. Stability tests revealed that the formulations were stable at room temperature but not at elevated temperatures. The in vitro safety profile of the formulation revealed no significant adverse effects on HaCaT cell lines. The NLC gel demonstrated significant anti-psoriatic activity, reducing inflammation and cytokine levels. The betulin-NLC-hydrogel formulation exhibited promising characteristics for the topical treatment of psoriasis, showcasing optimised drug delivery, sustained release, and notable therapeutic efficacy. The findings from this study provide a foundation for the potential clinical translation of this innovative topical dosage form for improved psoriasis management.

Optimization study of methylene blue dye adsorption on Chamaerops humilis fibers biosorption using a central composite design

This research explores the effectiveness of Chamaerops humilis (CH) fibers as a biosorbent for the adsorption of Methylene Blue (MB) dye from aqueous solutions. The fibers were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR). To optimize the dye removal process, a Design of Experiments methodology, specifically Central Composite Design (CCD), was applied. Factors such as solution pH, adsorbent dosage, contact time, and temperature were varied. The CCD analysis identified the optimal conditions for maximum removal efficiency (99.87 %) of a 10 mg/L MB solution, which were: 1.06 g/L of CH fiber dosage, pH 9.6, and a contact time of 60 min. The adsorption process aligned well with a pseudo-second-order kinetic model, and the maximum adsorption capacity of CH fibers was determined to be 9.422 mg/g. Thermodynamic parameters, including Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) changes, were calculated, confirming that the adsorption is spontaneous and endothermic. The study highlights the potential of Chamaerops humilis fibers as an efficient and eco-friendly adsorbent for MB dye removal, offering a sustainable and cost-effective solution for wastewater treatment, particularly in industrial effluent management.

Understanding the deposition of multilayered hydroxyapatite-bioactive glass/hydroxyapatite/titanium dioxide coatings on PEEK substrates by plasma spray

Poly-ether-ether-ketone (PEEK) is a polymeric material that is often used in biomedical applications due to its excellent mechanical properties and radiolucency; this material is, in general, biologically inert. In recent decades, thermally sprayed biocompatible coatings have been widely employed in metallic implants to improve the osseointegration process in the human body. Thus, not surprisingly, thermally sprayed biocompatible coatings can be envisaged as an excellent alternative to improve the material's surface properties. However, there is little information in the literature about the deposition of thermally sprayed bioactive coatings on polymeric substrates. In the present study, a titanium dioxide (TiO2) powder was plasma-sprayed on PEEK substrates acting as a bond coat to further deposition of hydroxyapatite (HA)/bioactive glass multilayered coatings. The design of experiments methodology was employed to produce coatings with tailored properties. A key aspect in this work is how the experiments were carried out to understand the effect of powder features, such as chemical composition, on the deposition of the ceramic coatings on the PEEK substrate. Heating/cooling physical laws were employed to discuss the results obtained. The methodology employed in this work allowed to deposit a multilayered coating with adhesion strength of about 50 MPa on PEEK substrates measured using scratch test. The coatings' structural, morphological, chemical, thermal, and mechanical evaluation was performed using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, differential scanning calorimetry, and micro indentation test, respectively. In-vitro tests were also performed on these coatings under static simulated conditions. The results show that the PEEK's surface can be successfully functionalized, turning it from showing an inert behavior to displaying bioactivity by applying a HA-based bilayer or multilayered coating.

A multi-stage lithium-ion battery aging dataset using various experimental design methodologies

This dataset encompasses a comprehensive investigation of combined calendar and cycle aging in commercially available lithium-ion battery cells (Samsung INR21700-50E). A total of 279 cells were subjected to 71 distinct aging conditions across two stages. Stage 1 is based on a non-model-based design of experiments (DoE), including full-factorial and Latin hypercube experimental designs, to determine the degradation behavior. Stage 2 employed model-based parameter individual optimal experimental design (pi-OED) to refine specific dependencies, along with a second non-model-based approach for fair comparison of DoE methodologies. While the primary aim was to validate the benefits of optimal experimental design in lithium-ion battery aging studies, this dataset offers extensive utility for various applications. They include training of machine learning models for battery life prediction, calibrating of physics-based or (semi-)empirical models for battery performance and degradation, and numerous other investigations in battery research. Additionally, the dataset has the potential to uncover hidden dependencies and correlations in battery aging mechanisms that were not evident in previous studies, which often relied on pre-existing assumptions and limited experimental designs.

Design of experiment approach to boost volatile production from kiwi byproducts

Design of Experiments (DoE), is a tool to explore relationships between factors and responses of a system. DoE and response surface methodology are increasingly used in different fields, but their application are limited in the valorization of residual biomass and agro-industrial by-products. Agro-industrial biomass residues can be eco-friendly converted into high-value compounds through bioprocesses. This approach identified key factors and predicted optimal conditions for enhancing microbial growth and the production of specific compounds or volatile classes. Lactiplantibacillus plantarum 4193 and Lacticaseibacillus paracasei 2243, were identified as the best starters while the production of methyl heptenone is influenced by fermentation time and pH. This out-turn in the generation of aromatically rich biomass, which can be utilised as a food ingredient or for the extraction of specific volatile compounds, and employed as flavouring agents. This study underlines the potential of fermentation in maximizing the value of unripe kiwi biomass.

Temperature-Regulated Synthesis of Hyaluronic Acid-Interpenetrated Polyacrylamide/Poly(Acrylic Acid Sodium Salt) Semi-Interpenetrated Polymer Network Gel for the Removal of Methyl Violet.

An alternative synthetic pathway was proposed for the optimization of synthesis to find a better correlation between the swelling and elasticity of hyaluronic acid-interpenetrated gels via temperature regulation. An experimental design methodology was presented for the synthesis of polyacrylamide/poly(acrylic acid sodium salt)/hyaluronic acid, PAAm/PSA/HyA, gels by modifying the one-pot procedure using free radical crosslinking copolymerization of AAm with the addition of anionic linear PSA chains in the presence of various amount of HyA, ranging between 0.05% and 0.20% (w/v). Semi-interpenetrated polymer network (IPN)-structured gels were designed with tunable elasticity, in which the extent of covalent crosslinking interactions is controlled by polymerization temperature ranging between -18 and 45 °C. Depending on the HyA content added in the synthesis and the polymerization temperature, the swelling ratio could be controlled. The addition of 0.05% (w/v) HyA increased the swelling of semi-IPNs, while the elastic modulus increased with increasing HyA content and decreased with the polymerization temperature. PAAm/PSA/HyA semi-IPNs showed the typical pH-sensitive swelling of anionic gels, and the swelling reached a maximum at a pH of 11.2. PAAm/PSA/HyA gels were tested for the removal of methyl violet from wastewater. Adsorption kinetics were shown to be well-fitted with the pseudo-second-order model using linear and nonlinear regression analysis. With the clear relationship between increased modulus and composition, this study enabled the fine-tuning of semi-IPN interactions by varying the polymerization temperature.

A Non‐Linear Model for Multiple Alcohol Intakes and Optimal Designs Strategies

ABSTRACTThis study addresses the complex dynamics of alcohol elimination in the human body, very important in forensic and healthcare areas. Existing models often oversimplify with the assumption of linear elimination kinetics, limiting practical application. This study presents a novel non‐linear model for estimating blood alcohol concentration after multiple intakes. Initially developed for two different alcohol incorporations, it can be straightforwardly extended to the case of more intakes. Emphasising the significance of accurate parameter estimation, the research underscores the importance of precise experimental design, utilising optimal experimental design (OED) methodologies. Sensitivity analysis of model coefficients and the determination of D‐optimal designs, considering correlation structures among observations, reveal a strong linear relationship between support points. This relationship can be used to obtain nearly optimal designs that are highly efficient and much easier to compute.

Enhanced Air Filtration Efficiency through Electrospun PVC/PVP/MWCNTs Nanofibers: Design, Optimization, and Performance Evaluation.

This study presents a novel approach for creating an effective air filtration medium using electrospun nanofibers comprised of poly(vinyl chloride) (PVC), poly(vinylpyrrolidone) (PVP), and impregnated with multiwall carbon nanotubes (MWCNTs). The membrane production was optimized using an experimental design methodology, resulting in a hydrophobic membrane that exhibits excellent dispersion of MWCNTs. Scanning electron microscopy images illustrate the nanofibers' morphology, featuring an average diameter of approximately 240 nm, minimal bead formation, and optimal MWCNT dispersion. Air filtration tests conducted with NaCl nanoparticles (7-300 nm) demonstrated superior permeability (10-12 m2) and minimal pressure drop (approximately 780 Pa at a 5 LPM airflow rate) compared to other electrospun materials. Both MWCNT-impregnated samples and individual PVC/PVP nanofibers exhibited filtration efficiencies nearing 96%. These results underscore the potential of this developed material for air filtration, particularly in indoor environments, where MWCNTs effectively adsorb and maintain low levels of gaseous and particulate pollutants. This study emphasizes the design, optimization, and comprehensive performance evaluation of PVC/PVP/MWCNT nanofibers, showcasing significant advancements in filtration efficiency with high flux. The findings suggest promising applications for this composite material in advanced air purification systems.

Regulating the surface area increase of zero-valent iron (ZVI) during ball milling: A study of the mechanical mechanism and low-carbon milling

This study investigates the effect of milling parameters on the specific surface area (SSA) increase of zero-valent iron (ZVI) powder, which is crucial for its environmental applications. Combining experimental and orthogonal design methodologies, the research explores how the parameters modulate the SSA. The operational factors are analyzed from the perspectives of bead momentum, kinetic energy, and energy efficiency. A regression model is proposed for the precise fabrication of ZVI with predetermined SSA. Furthermore, the study identifies optimized parameters that minimize energy consumption and carbon emissions. The results suggest that the optimal milling time is 10 min, with larger beads (2.0 mm), higher quality beads (0.75 kg), and higher shaft rotational speed (2000 rpm) significantly enhancing SSA. Discrete Element Method (DEM) simulations reveal micro-mechanical interactions, supporting the parameter selection scheme for maximizing SSA. The findings contribute to optimizing the milling process of the ductile ZVI powder for environmental clean-up.