Experimental Design Tools Research Articles

Comparative Analysis of PEDOT and ITO Under Thermal Bending and Cycling Stresses: Implications for Flexible Solar Cells

Poly(3,4-ethylenedioxythiophene) (PEDOT) and Indium Tin Oxide (ITO) are widely used in electronic devices, but their stability under thermal stress is a concern. Both PEDOT and ITO are susceptible to thermal stress, but their stability depends on the temperature and duration of exposure. To ensure long-term stability, it is essential to use appropriate thermal management techniques and stable materials. ITO has good mechanical stability under stretching and bending, while PEDOT can withstand high strains. Flexible solar cells are exposed to heating-cooling cycles, and when the thin film and substrate expand at different rates, residual strains caused by the thermal mismatch occur. ITO is heavily used in flexible solar cells, but indium is scarce and expected to run out within 50 years. PEDOT is a candidate to replace ITO and is currently under intensive research. This paper compares the thermal stability of PEDOT and ITO under thermal bending and cycling stress. In order to investigate the significance of different factors on thin film electrical characteristics, the DOE (design of experiments) tool was used for data collection and analysis of variance was used to analyze the data. The results showed that PEDOT is better than ITO under cyclic bending loading, while ITO is slightly more stable than PEDOT under thermal stress. These findings provide new insights into the behavior of PEDOT and ITO under thermal stress and their potential applications in electronic devices.

Optimization of biomass saccharification processes with experimental design tools for2Gethanol production: a review

AbstractThe current energy scenario has encouraged the replacement of carbon sources with renewable sources. Second‐generation (2G) ethanol production from lignocellulosic material or agroindustrial biomass involves a three‐step process consisting of pretreatment, saccharification and fermentation. Enzymatic saccharification is the most critical step for recovering fermentable sugars from biomass. Many factors such as pretreatment, enzyme load, pH, temperature, substrate and surfactant concentrations, and reaction time, among others, can affect biomass saccharification. In this sense, different design of experiment (DoE) tools together with response surface methodology (RSM) have been used as a viable strategy to determine how factors influence saccharification and to optimize this process. The strategy involves fewer experiments, less time and lower cost. This review summarizes how DoE and RSM tools have been used to optimize biomass saccharification. Moreover, an overview of the main experimental design tools used in this field is provided.

Bioprocess intensification with model-assisted DoE-strategies for the production of biopharmaceuticals

Abstract The demand for highly effective biopharmaceuticals and the need to reduce manufacturing costs are increasing the pressure to develop productive and efficient bioprocesses. For this purpose, model-based process design concepts have been developed. Although first approaches were proposed, model-based process designs are still not state-of-the-art for cell culture processes during development or manufacturing. This highlights a need for improved methods and tools for optimal experimental design, optimal and robust process design and process optimization for the purposes of monitoring and control during manufacturing. In this review, an overview of the state of the art of model-based methods, their applications, further challenges, possible solutions and specific case studies for intensification of process development for production of biopharmaceuticals is presented. As a special focus, problems related to data generation (culture systems, process mode, specifically designed experiments) will be addressed.

Critical evaluation of MS acquisition conditions and identification process in LC-Q-Orbitrap-MS for non-targeted analysis: pesticide residues as case of study.

In routine measurements, the length of analysis time and the number of samples analysed during a given time unit are crucial. Additionally, the analytical method used has to provide reliable results and be able to identify and quantify any compound present in the matrix. High-resolution equipment, including Orbitrap analysers, is commonly used for non-targeted determinations. However, researchers still rely on trial and error to achieve the best acquisition conditions on the mass spectrometer, which is a tedious and time-consuming process that can lead to errors. Moreover, tentative compound identification, particularly when using a non-targeted approach, heavily depends on commercial databases. All of these issues can ultimately result in incomplete identification of compounds in the study matrix. In this framework, the study presented here has a dual objective: to use the experimental design tool to optimise critical parameters in mass spectrometry using LC-Q-Orbitrap-MS equipment when working in a non-targeted approach and to compare the mzCloud™ and ChemSpider™ commercial databases included in Compound Discoverer software with TraceFinder home-made databases generated to evaluate the ability to identify compounds. The study's noteworthy findings reveal that employing an experimental design has facilitated rapid optimisation of the mass spectrometer's multiplexing and loop parameters. Furthermore, the study highlights that the lack of harmonisation in commercial databases poses a disadvantage in the identification of compounds, leading to superior results when using home-made databases. In the latter databases, around 80% of the compounds were identified, which is approximately twice the number identified in commercial databases (around 40% in the best case with ChemSpider™).

Experimental and computational design tools for industrial drying processes: Challenges in process‐limit prediction

AbstractThe coating and drying of inks and slurries are important steps to manufacture a plethora of products. Drying processes, particularly, comprise energy‐intensive steps that affect product cost and quality. Prior work has highlighted failures of various multicomponent diffusivity models to conserve mass in dryer modeling and challenges in predicting process limits given variability in published values of key thermodynamic parameters. Herein, we develop a computational model and benchtop drying experiments to investigate these concerns for drying polymer‐laden coatings. Model predictions of process limits in a single‐zone drying oven demonstrate that published variability in Flory–Huggins parameter yields large variations in predicted operating temperatures above which blistering occurs. This indicates that caution should be exercised when choosing approaches to obtain or predict the Flory–Huggins parameter, and that both benchtop drying experiments and a set of additional experiments, such as sorption experiments, are needed to fully characterize and optimize a given drying process.

A novel optimized polyoxometalate-modified silver nanocomposite. Application to the development of antibacterial textiles

Antimicrobial textiles are used in various settings ranging from households to different industries, health areas, and shops. These materials are used in the manufacture of air filters, food packaging, sportswear; and hygiene, medical, storage, ventilation, and water purification systems. In healthcare medical centers, textiles like bed sheets and curtains are surfaces prone to contamination with microorganisms. The growth of microbes on the surface of textile materials can be inhibited by biocidal and biostatic compounds to prevent the spread of microbes. This work describes the development and characterization of a new antibacterial nanocomposite composed of silver nanoparticles functionalized with polyoxometalates. The experimental conditions for the synthesis were optimized using design of experiment tools. The resulting nanocomposite (formulation) was extensively characterized by UV-Vis spectroscopy, Fourier-transformed infrared spectroscopy, cyclic voltammetry, dynamic light scattering, X-ray diffraction, and transmission electron microscopy, and the bioactivity of the material was tested against Gram-positive and Gram-negative models. The novel formulation was supported in an eco-friendly fabric to obtain a textile material with broad applicability and lasting antibacterial properties.

Green nanoemulsion-based treatment to remove sulfamethoxazole from a contaminated water solution

Sulfamethoxazole (SUX) is a common pharmaceutical, but represents a potential global threat to human health due to its exhaustive use and consequent outflow in the environment. This situation calls for development of a cost-effective approach to remove SUX present in contaminated released from various sources. In this study, we developed green nanoemulsions to remove SUX from contaminated water samples. Parameters predicted by Hansen solubility (HSPiP software) were used to select excipients. Several trial batches (SN1–SN12) of green nanoemulsions were developed and characterized for size, zeta potential, polydispersity (PDI), and removal efficiency (%RE) to determine the input parameters (factors, levels, and responses) for an experimental design tool (Design-Expert) to identify the most critical variables controlling %RE and to optimize the nanoemulsion composition under set constraints. Transmission electron microscopy (TEM) confirmed the morphological behavior after 30 min of dispersion. Finally, the inductively coupled plasma-optical emission spectroscopy (ICP-OES) technique was used to confirm the absence of SUX in water treated with the optimized nanoemulsion. Results showed that SUX and eugenol closely interact based on Hansen solubility parameters and the experimental solubility data corroborated the predicted outcomes. Pseudo ternary-phase diagrams suggested various ratios of surfactant to co-surfactant (Smix) based on SN1–SN12 and that SN10 was the most suitable nanoemulsion for input parameters (Smix of 1:3, desired size 78 nm, lowest PDI 0.118, highest %RE 78%, and highest zeta potential +23 mV) in the experimental design program. In addition, Design-Expert identified the prime factors responsible to control %RE. OSEN1 was the most robust and optimized nanoemulsion with high overall desirability (0.94). Composition, globular size, viscosity, and contact time emerged as prime critical variables with a significant impact on the %RE of SUX from contaminated water using the green nanoemulsion. ICP-OES confirmed the absence of SUX from treated water. Overall, our results demonstrate that green nanoemulsions represent a promising and cost-effective approach to remove SUX from environmental water samples and alleviate safety concerns.

Sustainability improvement by utilizing polymer waste as an energy source for a diesel engine with alcohol additives

Energy and fossil fuel supplies have been threatened by the depletion of fossil fuels on a global scale, as well as by the constant rise in oil prices and the continual increase in environmental degradation. On the other hand, polymer waste has increased due to its usage in a daily lifestyle because of its cheap cost, ease of production, and adaptability. Indirectly, these polymer wastes are causing some major problems for the ecosystem and other living things. By transforming waste polymers into usable energy, can address for both the non-biodegradability of polymers and the need for an alternative fuel. This research paper aims to evaluate the performance of fuel produced by the pyrolysis of polyethylene polymer. Three distinct alcohol additive blends with polymer fuel were investigated in a single-cylinder direct injection diesel engine for their performance and emission characteristics. The engine efficiency of pentanol was found to be about 3.4% higher than that of base diesel, and with 7% better fuel consumption. Additionally, alcohol additives reduced CO emissions by 3.6%–3.8% and HC emissions by 3.5%–3.8%. The results were further analysed using the design of experiment tool, "Full Factorial Design" to determine the most optimal running condition with fuel consumption of 0.4508 kg/kWh, hydrocarbon of 49 ppm and carbon monoxide 0.265% at half load conditions.

Development and optimization of a LC-MS/MS compatible method for quantification of losartan, hydrochlorothiazide and their impurities using AQbD approach and measurement uncertainty evaluation

The concept of Analytical Quality by Design (AQbD) comes as a more robust, economical, and scientifically based alternative for analytical development, to the detriment of OFAT (one factor at a time). This new understanding applicable to analytical development is recommended since regulatory flexibility can be achieved and ensure more reliable results throughout the life of the product. This new approach was applied to develop an analytical procedure indicative of stability for a pharmaceutical product of association of Losartan Potassium and Hydrochlorothiazide, considered a potential first line for the treatment of hypertension. The first stage of the analytical development consisted of defining analytical target profile (ATP), follow by a bibliographic survey of the physicochemical properties of the molecules in question to define an initial method. After defining the initial analytical conditions, statistical tools for design of experiments (DoE) were used for the screening and optimization steps. In the screening stage, the Plackett-Burman design was chosen, using 11 factors and 2 levels, through which it was possible to evaluate numerous variables and determine their significance in relation to the responses. Next, optimization was carried out with the experimental design of a central composite with 4 factors and 5 levels, which allowed modeling a complex response surface and evaluating the phenomena of interactions between the factors. Thus, the optimized analytical conditions were defined, considering a 0.3% formic acid gradient as eluent A and a mixture of acetonitrile and methanol (80:20) as eluent B, X-Bridge C18 chromatographic column (150 mm × 4 .6 mm × 3.5 μm), column temperature of 40°C, flow rate of 1.3 mL/min, injection volume of 10 μL. Through this methodology, it was possible to identify an unknown degradation product of Hydrochlorothiazide, formed by the reaction with lactose (excipient present in the drug formulation), proving that the method can be applicable both to DAD detectors and to spectrometry and mass detectors. It was also proven through the forced degradation study that the method is indicative of stability, in addition to being validated and robust for its purpose.

Analysis of ideal models of real nonlocal acoustic and elastic metamaterials

Nonlocal coupling in acoustic and elastic systems has received growing attention for its potential to expand the capabilities of active metamaterials. Previously, we have shown experimentally how nonlocality imposed through action at a distance, where signals from disturbances at one location are used to drive actuators at separate locations, gives rise to unique scattering characteristics, namely highly nonreciprocal transmission. We showed how the mathematical models for these experimental systems were excellent predictors for real system behavior, and as such, represented powerful experimental design tools. However, these models were elaborate, incorporating the characteristics of real sensors and actuators, electronic controllers, and material properties and geometries, consequently obscuring the underlying nonlocal physics responsible for their unique behavior. Here, we present simplified models of these real systems that feature closed form expressions for system scattering characteristics, allowing for the identification of relevant dimensionless quantities and revealing how the interactions of those quantities affect both system performance and stability. We compare and contrast ideal models for both acoustic and elastodynamic nonlocal systems, highlighting how each ideal model is qualitatively representative of its real counterpart, thus providing a pathway to a deeper understanding and further exploration of nonlocality in wave-bearing systems.

MULTI-RESPONSE OPTIMIZATION OF METFORMIN -HYDROCHLORIDE DRUG VIA EXPERIMENTAL DESIGN TECHNIQUES APPLIED ON THE ADAPTIVE LOCAL LINEAR REGRESSION MODEL FOR RESPONSE SURFACE METHODOLOGY

The challenge encountered by industrial statisticians and engineers during statistical process control in other to build-up and formulates pharmaceutical optimization of drugs have prompted several choices of experimental design tool and regression models. The most commonly applied regression model is the second-order polynomial which may perform poorly due to model misspecification. In this paper, we present two experimental design methods namely; the Full Factorial Design (FFD) and the Circumscribed Central Composite Design (CCCD) applied to an existing Adaptive Local Linear Regression ( model to ameliorate the problem of boundary bias for a multi-response problem. The FFD do not make reference to the star points and as such could not address variability in the data, hence we also applied the CCCD to accommodate the star points in order to maintain rotatability and curvature in the data. In the application, we minimized Metformin Hydrochloride (Met-HCL) drug usage via FFD on and CCCD on and the results from the goodness-of-fit statistics, residual plots and optimization were obtained and analyzed. The that utilized CCCD outperformed that uses FFD in terms of the goodness-of-fit statistics, minimum residual plots as it relates to the zero residual line and optimization of Met-HCL for Response Surface Methodology (RSM) data.

A sDOE (Simple Design-of-Experiment) Approach for Parameter Optimization in Mass Spectrometry. Part 1. Parameter Selection and Interference Effects in Top-Down ETD Fragmentation of Proteins in a UHR-QTOF Instrument

Design-of-experiment (DOE) approaches, originally conceived by Fischer, are widely applied in industry, particularly in the context of production for which they have been greatly expended. In a research and development context, DOE can be of great use for method development. Specifically, DOE can greatly speed up instrument parameter optimization by first identifying parameters that are critical to a given outcome, showing parameter interdependency where it occurs and accelerating optimization of said parameters using matrices of experimental conditions. While DOE approaches have been applied in mass spectrometry experiments, they have so far failed to gain widespread adoption. This could be attributed to the fact that DOE can get quite complex and daunting to the everyday user. Here we make the case that a subset of DOE tools, hereafter called SimpleDOE (sDOE), can make DOE accessible and useful to the Mass Spectrometry community at large. We illustrate the progressive gains from a purely manual approach to sDOE through a stepwise optimization of parameters affecting the efficiency of top-down ETD fragmentation of proteins on a high-resolution Q-TOF mass spectrometer, where the aim is to maximize sequence coverage of fragmentation events.

Complex architectural control of ice-templated collagen scaffolds using a predictive model

The architectural and physiomechanical properties of regenerative scaffolds have been shown to improve engineered tissue function at both a cellular and tissue level. The fabrication of regenerative three-dimensional scaffolds that precisely replicate the complex hierarchical structure of native tissue, however, remains a challenge. The aim of this work is therefore two-fold: i) demonstrate an innovative multidirectional freeze-casting system to afford precise architectural control of ice-templated collagen scaffolds; and ii) present a predictive simulation as an experimental design tool for bespoke scaffold architecture. We used embedded heat sources within the freeze-casting mold to manipulate the local thermal environment during solidification of ice-templated collagen scaffolds. The resultant scaffolds comprised complex and spatially varied lamellar orientations that correlated with the imposed thermal environment and could be readily controlled by varying the geometry and power of the heat sources. The complex macro-architecture did not interrupt the hierarchical features characteristic of ice-templated scaffolds, but pore orientation had a significant impact on the stiffness of resultant structures under compression. Furthermore, our finite element model (FEM) accurately predicted the thermal environment and illustrated the freezing front topography within the mold during solidification. The lamellar orientation of freeze-cast scaffolds was also predicted using thermal gradient vector direction immediately prior to phase change. In combination our FEM and bespoke freeze-casting system present an exciting opportunity for tailored architectural design of ice-templated regenerative scaffolds that mimic the complex hierarchical environment of the native extracellular matrix. Statement of significanceBiomimetic scaffold structure improves engineered tissue function, but the fabrication of three-dimensional scaffolds that precisely replicate the complex hierarchical structure of native tissue remains a challenge. Here, we leverage the robust relationship between thermal gradients and lamellar orientation of ice-templated collagen scaffolds to develop a multidirectional freeze-casting system with precise control of the thermal environment and consequently the complex lamellar structure of resultant scaffolds. Demonstrating the diversity of our approach, we identify heat source geometry and power as control parameters for complex lamellar orientations. We simultaneously present a finite element model (FEM) that describes the three-dimensional thermal environment during solidification and accurately predicts lamellar structure of resultant scaffolds. The model serves as a design tool for bespoke regenerative scaffolds.

Development of a new green microextraction technique, switchable hydrophilicity solvent-based homogenous liquid–liquid microextraction, to analyze synthetic cannabinoids in plasma

Synthetic cannabinoid receptor agonists (SCRA) are currently the most popular class of new psychoactive substances (NPS) in several countries, including Brazil. Notwithstanding that, they pose a threat to public health, as little of their toxicological properties is known. Moreover, these SCRAs have different presentations compared to classic cannabinoids and are not usually detected by conventional analytical methods due to their chemical variety. Thus, the development of new methodologies fit to analyze SCRAs is extremely warranted. In that regard, the use of environmentally benign or green approaches has been a trend in the last decades and has gained attention in Forensic Toxicology – so much so that guidelines have been established for that purpose, e.g. green analytical toxicology (GAT). With that in mind, the aim of this work was to develop and validate a quantitative method to analyze SCRAs in plasma by a novel green technique that agrees with the principles of GAT. A switchable hydrophilicity solvent-based homogenous liquid–liquid microextraction (SHS-HLLME) was developed and statistical tools were used to optimize it. Analysis of Variance (ANOVA) was chosen to find the best switchable hydrophilicity solvent (SHS) and Full Factorial and Central Composite design to study the following variables: volume of SHS:HCl 6 M mixture (200–500 μL) and NaOH 10 M (200–500 μL), salting-out effect, and time of extraction (1–5 min). The ANSI/ASB Standard 036, 1st edition 2019 guidelines were used for method validation. All analyses were performed using a UPLC-MS/MS with the multiple reaction monitoring approach. Ethical Committee approval No. 46404121.8.3001.0067. Funded by CNPq 142056/2020-0, CAPES/INSPEQT 16/2020, and FAPESP 21/09857-8. ANOVA showed that between two SHS tested, N,N-dimethylcyclohexylamine and dipropylamine, the latter yielded higher analyte recovery ( P < 0.05). Moreover, the Design of Experiment tools herein used showed that the salting-out effect and time of extraction had no major impact on analyte recovery; in contrast, 500 μL of both SHS:HCl mixture and NaOH yielded higher analyte recovery ( P < 0.05). Once optimized, the proposed technique was successfully validated according to international guidelines with the following parameters: limits of detection: 0.01–0.08 ng/mL; limit of quantitation: 0.1 ng/mL; linearity: 0.1–10 ng/mL; bias and precision < 15%; no carryover was observed and the method proved to be selective for the aimed SCRAs. The matrix effect, recovery efficiency, and process efficiency studies are being currently carried out. The microextraction technique herein developed is based on an acid-base neutralization between HCl and NaOH, making it an approach significantly more sustainable when compared to conventional choices that rely entirely on organic solvents. In that regard, only 250 μL of dipropylamine was required–an organic solvent considerably less toxic than those used in common extractions, organochlorides for example. In addition, a small volume was used compared to more conventional techniques in forensic analyses, such as solid-phase extraction (> 500 μL). Hence, we were able to successfully detect and quantitate 31 SCRAs at extremely low concentrations (0.01–0.1 ng/mL, respectively) using only 300 μL of plasma, showing that the SHS-HLLME can be used for the analysis of multiple SCRAs in a single run, thus could be a valuable tool in forensic cases. We demonstrated for the first time the application of the novel SHS-HLLME for synthetic cannabinoids. The microextraction technique herein developed has promising applications in Forensic Toxicology, as it consists of a simple and fast procedure that yields high sensitivity with only a few microliters of a biological sample. Also, it avoids the use of highly toxic chemicals and generates less residue, thus it fits the growing trend of using sustainable analytical methodologies, established by GAT and other similar guidelines.

Solvent screening, optimization and kinetic parameters of the biocatalytic epoxidation reaction of β-pinene mediated by Novozym®435.

Monoterpenes, such as beta-pinene, are secondary metabolites widely used in the flavors and fragrance industries and can have their structure altered to enhance their applicability, such as producing epoxides, which are used as intermediaries for pharmaceuticals. Epoxides are commonly synthesized by the use of inorganic acids as catalysts, although the acid medium induces epoxide degradation. To overcome these limitations biocatalysis is shown as an alternative. Related to, this work aimed to perform the synthesis of β-Pinene epoxide using Pseudozyma antarctica lipase B (Novozym®435) as a biocatalyst, while determining the independent variables that influence the reaction using experimental design tools. Different solvent systems were evaluated (cyclohexane, acetonitrile, ethyl acetate, and dichloromethane) until 72h reaction time, from which ethyl acetate showed higher conversion into the epoxidized product (40% in 24h). Under the other solvents systems, several oxidized by-products were obtained, such as ketones and aldehydes. Moreover, applying metrics of green chemistry, ethyl acetate was also corroborated as the most promising solvent, with a higher atom economy (66.8%) in comparison to the others (41.3%), and a smaller E-value (1.19). Ethyl acetate was the solvent/acyl donor of choice and had the molar ratio and percentage of biocatalyst increased, which resulted in 80% of the product after 3h of reaction. To obtain an optimized model, four independent variables (temperature, stirring, molar ratio, percentage of biocatalyst) were evaluated using experimental design tools, Fractional Factorial Design and Central Composite Rotatable Design, with conversions ranging from 23 to 95% after 3h. All the independent variables were statistically significant (p < 0.05) and had different degrees of impact on the conversion. Kinetic parameters of the reaction were determined using the Lineweaver-Burk model (results under 30.1mmol for Km and 10.7mmol.min-1 for Vmax). In conclusion, the combination of two different tools of experimental design provided the development of an optimized model for beta-Pinene epoxidation, achieving high conversion to the epoxidized product after 3h.

Stability analysis of real time hybrid simulation under coupled actuator delay and nonlinear behavior

AbstractStability of real time hybrid simulation (RTHS) has attracted considerable attention since actuator delay would deviate experiment results or even destabilize the real‐time test. Previous studies have extensively investigated stability of RTHS for linear systems, while stability of RTHS for nonlinear system remains unclear. This study introduces the Takagi‐Sugeno (T‐S) method to describe the nonlinear behavior in a piecewise linear way, then investigates the stability of nonlinear system with time delay through the Lyapunov‐Krasovskii (L‐K) theory. Such approach successfully solves the stability problem of RTHS with coupled bilinear‐hysteresis substructure and actuator delay, and proposes a stability criterion in the form of linear matrix inequality (LMI). It proves that the stability of RTHS is determined by the most unfavorable state of nonlinear system. In the SDOF case with stiffness softening, the initial elastic state is the most unfavorable; while for the MDOF case with multiple delays, the stability is determined by the overlap part of stable region of each nonlinear state. The computational simulation and experimental results show that the difference between linear‐ and nonlinear hysteretic system with time delay is that when instability occurs, latter could remain energy balanced since the time‐delay energy is dissipated by hysteresis behavior, while energy accumulates in the former leading to unbounded responses. The proposed approach provides a potential tool for experimental design of RTHS before the test, the time‐delay control during the test and error evaluation after the test.

Optimized design of droplet micro-mixer with sinusoidal structure based on Pareto genetic algorithm

Mixing is one of the important steps in biological and chemical reactions and assays. In this paper, we numerically simulate the droplet generation and dynamic mixing in a double T-junction microchannel and optimize the geometry of the sinusoidal microchannel using a Pareto multi-objective genetic algorithm to provide important reference values for the design of efficient and integrated microfluidic chips. We choose two parameters related to the geometry of the sinusoidal microchannel as design variables, and use the average concentration difference within the droplet and the average pressure drop within the microchannel as two objective functions to explore the effects of design variables on the objective functions. The Latin hypercube sampling approach is used as an experimental design tool for parametric studies in design space, and it is used to choose design points in the design space. We employ proxy modeling of response surface functions to approximate the objective function. The Pareto optimal frontier of the micro-mixer is obtained using the Pareto genetic algorithm and the optimal solution set is classified using K-means clustering, from which representative design variables are chosen. The optimal set of solutions optimized with the Pareto genetic algorithm ensures the mixing quality while taking into account the pressure drop inside the microchannel. We also found two important factors affecting the mixing quality. (1) The contraction of the channel cross-section leads to alternating deformation of the droplets and enhances the mixing inside the droplets. When the droplet moves inside the microchannel, the channel cross-section alternately contracts and expands, changing the droplet to undergo alternate deformation, which changes the original internal circulation within the droplet and enhances the mixing inside the droplet. (2) Under the action of centrifugal force, the Dean vortex is generated, which enhances the mixing inside the droplet. The Dean vortex is generated when droplets move inside the curved channel. The Dean vortex causes asymmetric circulating flow inside the droplet, which increases the contact area of the fluid and thus significantly improves the mixing efficiency.

Utilizing response surface methodology to evaluate the process parameters of indigenous cucumber fermentation.

Commercial pickled cucumbers are produced in variety of salt concentrations including brines up to 15% sodium chloride due to the preventive nature of the salt towards microbial growth. Although it is deemed necessary for manufacturers to utilize high amounts of salts to prolong shelf life, the high content creates a burden for the growth of beneficial microorganisms including probiotics. In this study, the production of naturally fermented cucumbers and their microbial viability were tested with the help of an experimental design tool, Box-Behnken Design (BBD), to evaluate the optimal conditions for the production process and to maintain the highest viability of potential beneficial microorganisms during storage. Accordingly, the operational conditions including salt concentration (2, 5, or 8%), fermentation temperature (20, 25, or 30°C), and brine filling (pretreatment) temperature (80, 85, or 90°C) were optimized with a significant fit to a quadratic model (p<0.05). The trends for sugar consumption and total acid production were monitored to demonstrate the correlation between the above-mentioned operational parameters for the fermentation process of pickled cucumbers with indigenous microorganisms. Overall, 5% salt content, 70°C filling temperature and 25°C fermentation medium was determined to maintain over 6logcfu/mL viability. The results represent a valuable contribution to the pickle industry including a know-how of process parameters.

Improvement of competitiveness through the application of analytic hierarchy process, game theory, decision trees and design of experiments tools

Competitiveness is important for all companies. Because qualitative and quantitative factors are associated with it, strategic decisions must be supported by different analytical tools. In this work, we describe the application of specific tools to improve the expansion strategy for a food supplements company which is facing strong competitors. Two main alternatives were considered: increasing the production of the current products, and extending the company’s portfolio by adding new products. In contrast to other works, the competitors’ key features and likely response were considered as determinant factors for the assessment of these alternatives. These were addressed through analytic hierarchy process and game theory tools. Then, economic assessment and optimization of the new products’ features were addressed through decision tree and design of experiments tools. The results of this approach corroborate its suitability for other companies where appropriate strategic actions must be formulated in advance of the possible competitors’ response to increase competitiveness.

Assessment of factors influencing the transfer efficiency in electrostatic spray coating process

The electrostatic spray is one of the advanced coating methods that provide uniform and effective coating on the surfaces of the components. This method can reduce the limitations observed in conventional spray painting. The uniform layer of paint depends on various input parameters such as paint flow rate, disc air pressure, paint viscosity, and applied voltage. The design of experiment (DOE) tool optimizes the process parameters to achieve the expected or best coating combinations. The transfer efficiency is an essential factor that determines the quality of the surface coating. In this work, the DOE tool was used to increase the transfer efficiency and reduce the time taken for the coating process with optimized process parameters. The experimental test found that the combined effect of input responses has increased the efficiency of the coating up to 70 %. The determined Transfer efficiency is higher than the conventional method.