Fractional Factorial Experimental Design Research Articles

In vitro evaluation of the osteogenic and antimicrobial potential of porous wollastonite scaffolds impregnated with ethanolic extracts of propolis.

Context: The development of porous devices using materials modified with various natural agents has become a priority for bone healing processes in the oral and maxillofacial field. There must be a balance between the proliferation of eukaryotic and the inhibition of prokaryotic cells to achieve proper bone health. Infections might inhibit the formation of new alveolar bone during bone graft augmentation. Objective: This study aimed to evaluate the in vitro osteogenic behavior of human bone marrow stem cells and assess the antimicrobial response to 3D-printed porous scaffolds using propolis-modified wollastonite. Methodology: A fractional factorial design of experiments was used to obtain a 3D printing paste for developing scaffolds with a triply periodic minimal surface (TPMS) gyroid geometry based on wollastonite and modified with an ethanolic propolis extract. The antioxidant activity of the extracts was characterized using free radical scavenging methods (DPPH and ABTS). Cell proliferation and osteogenic potential using Human Bone Marrow Stem Cells (bmMSCs) were assessed at different culture time points up to 28days. MIC and inhibition zones were studied from single strain cultures, and biofilm formation was evaluated on the scaffolds under co-culture conditions. The mechanical strength of the scaffolds was evaluated. Results: Through statistical design of experiments, a paste suitable for printing scaffolds with the desired geometry was obtained. Propolis extracts modifying the TPMS gyroid scaffolds showed favorable cell proliferation and metabolic activity with osteogenic potential after 21days. Additionally, propolis exhibited antioxidant activity, which may be related to the antimicrobial effectiveness of the scaffolds against S. aureus and S. epidermidis cultures. The mechanical properties of the scaffolds were not affected by propolis impregnation. Conclusion: These results demonstrate that propolis-impregnated porous wollastonite scaffolds might have the potential to stimulate bone repair in maxillofacial tissue engineering applications.

Exploring the relationship between sputter-deposition conditions and electrochemical response of ZrO2 films on biodegradable MgZnCa alloy

In this work, we investigated the enhancement of corrosion resistance in a biodegradable Mg-0.7Zn-0.6Ca (wt. %) alloy (MgZnCa) by applying ZrO2 thin films deposited via reactive magnetron sputtering. We employed a fractional factorial experimental design to systematically examine the influence of the deposition power, deposition time, and O2 fraction on the effectiveness of the ZrO2 thin film in preventing corrosion of the Mg alloy. Our analysis revealed that the ZrO2 thin films exhibited a monoclinic crystal phase and maintained stoichiometry across various O2 fractions. Interestingly, we observed a 78% roughness reduction when using the lowest O2 fraction, while roughness increased with the deposition power and time. The corrosion response of bare and ZrO2-coated MgZnCa alloy was assessed by electrochemical techniques and detection of H2 production during the Mg corrosion via gas chromatography. The optimal set of deposition conditions, essential for enhancing the short-term corrosion resistance of magnetron-sputtered ZrO2 coatings, involves maximizing thickness through high power (400 W) and extended deposition time (90 min). It is crucial to balance these factors while maintaining an appropriate O2 fraction (20%) to ensure the formation of a stoichiometric film. Avoiding excess oxygen is imperative, as it can lead to undesirable intergranular porosity and surface roughness. This optimization resulted in a 46% reduction in the evolution of H2 gas compared to the bare MgZnCa alloy. Overall, this work sheds light on the potential of ZrO2 thin films as effective corrosion-resistant coatings for MgZnCa alloys, emphasizing the critical role of deposition parameters in achieving superior protection against corrosion.

Tourist choice of sustainable hot springs tourism under post‐COVID‐19 pandemic period: A case in Colorado

AbstractHot springs tourism has increasingly attracted tourists who pursue wellness and harmony with the natural environment. This paper investigates how four sustainability‐related attributes influence tourist choice and estimates their marginal willingness to pay for Colorado hot springs tourism under the post‐COVID‐19 pandemic period. A fractional factorial choice experiment design and conditional logit model were used to analyze the choice data of 303 retained respondents collected from the online surveys. The results show the importance of sustainability‐related attributes on tourist choice and suggest the hot springs tourism sector improves destination sustainability to maintain market competitiveness under the post‐COVID‐19 pandemic period.

Insights into isotherms, kinetics, and thermodynamics of adsorption of acid blue 113 from an aqueous solution of nutraceutical industrial fennel seed spent

Research studies have been carried out to accentuate Fennel Seed Spent, a by-product of the Nutraceutical Industry, as an inexpensive, recyclable and operational biosorbent for bioremediation of Acid Blue 113 (AB113) in simulated water-dye samples and textile industrial effluent (TIE). The physical process of adhesion of AB113 on the surface of the biosorbent depends on various parameters, such as the initial amount of the dye, amount and expanse of the biosorbent particles, pH of the solution and temperature of the medium. The data obtained was analyzed using three two-parameter and five three-parameter adsorption isotherm models to glean the adsorbent affinities and interaction mechanism of the adsorbate molecules and adsorbent surface. The adsorption feature study is conducted employing models of Weber-Morris, pseudo 1st and 2nd order, diffusion film model, Dumwald-Wagner and Avrami model. The study through 2nd order pseudo and Avrami models produced complementary results for the authentication of experimental data. The thermodynamic features, ΔG0, ΔH0, and ΔS0 of the adsorption process are acclaimed to be almost spontaneous, physical in nature and endothermic in their manifestation. Surface characterization was carried out using Scanner Electron Microscopy, and identification and determination of chemical species and molecular structure was performed using Infrared Spectroscopy (IR). Maximum adsorption evaluated using statistical optimization with different combinations of five independent variables to study the individual as well as combined effects by Fractional Factorial Experimental Design (FFED) was 236.18 mg g−1 under optimized conditions; pH of 2, adsorbent dosage of 0.500 g L−1, and an initial dye concentration of 209.47 mg L−1 for an adsorption time of 126.62 min with orbital shaking of 165 rpm at temperature 49.95 °C.

Performance of membrane distillation assisted crystallization and crystal characteristics for resource recovery from desalination brine

Membrane distillation crystallization (MDC) has been widely studied in recent year for its potential for resource recovery from desalination brine with high concentrations. In this study, crystal samples produced from a bench-scale MDC system have been analysed for crystal morphology, crystal purity and crystal size distribution (CSD). In addition, orthogonal fractional factorial (OFF) experimental design has been introduced to evaluate the influence of various operating conditions on the crystal size and CSD. Feed temperature (40 to 60 °C), crystallization time (60 to 180 min) and the feed composition have been used as the control factors. The results show that the MD in the MDC system maintains a consistent flux of 1.32 to 4.2 kg/m2·h across various feed compositions; higher feed temperatures led to the formation of larger crystal clusters, while longer crystallization time yielded more cubic-shaped crystals; an overall NaCl purity exceeding 99.08 % has been achieved throughout all the experiments; and the increased feed temperature and prolonged crystallization time results in a narrower CSD. The result of OFF experimental design identifies feed temperature as the dominant factor affecting crystal size and CSD. However, the presence of impurities in the feed water could pose challenge to the thermal stability and longevity of the membrane.

Conversion of lignite fly ash into synthetic zeolite by hydrothermal, fusion‐hydrothermal, and hydrothermal‐sonochemical processes

AbstractOBJECTIVEThe purpose of this study was the conversion of calcareous lignite fly ash (LFA) into synthetic zeolite by hydrothermal, fusion‐hydrothermal, and hydrothermal‐sonochemical processes.METHODExperiments were carried out using raw and washed (5 N HCl) fly ash. Initially, the fractional factorial experimental design was used to plan the hydrothermal experiments and assess the process parameters, such as solid to liquid ratio (S/L), silica to aluminum oxide ratio (SiO2/Al2O3), calcium oxide content (% CaO), time, and temperature of the hydrothermal process. The optimized conditions were then applied to a two‐stage fusion‐hydrothermal process, while the influence of sonication on the conversion efficiency was tested before and after the hydrothermal process. Mineralogical analysis was performed by x‐ray diffractometer (XRD) to detect zeolite formation. Further characterization was conducted by x‐ray fluorescence (XRF), specific surface area, and laser particle analysis to assess process efficiency.RESULTS AND DISCUSIONThe results indicated the formation of four types of zeolite crystals. The washed LFA (wLFA) yielded the maximum zeolite yield when it was hydrothermally treated for 6 h at 150 °C, S/L = 1:2, and SiO2/Al2O3 = 6.3. In such conditions, phillipsite was synthesized at 27%. The yield of phillipsite zeolite was improved to 32% when the hydrothermal process was followed by a 30 min sonication process. At the same processing conditions, the use of raw LFA produced 72% crystalline tobermorite. The hydrothermal‐late sonication process can effectively convert waste fly ash into valuable products. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).

Olive mill wastewater treatment using natural adsorbents: phytotoxicity on durum wheat (Triticum turgidum L. var. durum) and white bean (Phaseolus vulgaris L.) seed germination.

This research was undertaken to optimize the phenolic compound removal from Olive Mill Wastewater (OMW) by sawdust and red clay as natural adsorbents. Fractional factorial experimental design at 25-1 was used in order to optimize the experimental conditions for high removal efficiency. Statistics ANOVA analysis, Fisher's test, and Student's test suggested that the adsorbent dose has the most significant influence on polyphenol removal for both adsorbents. The maximum removal of polyphenols by sawdust reached 49.6% at 60 °C by using 60 g/L of adsorbent dose, pH 2, reaction time of 24 h, and agitation speed of 80 rpm. Whereas, for red clay, 48.08% of polyphenols removal was observed under the same conditions for sawdust except the temperature of 25 °C instead of 60 °C. In addition, the thermodynamic parameters suggested spontaneous process for both adsorbents, endothermic for the sawdust and exothermic for red clay. Furthermore, the phytotoxicity effect of OMW on durum wheat (Triticum turgidum L. var. durum) and white bean (Phaseolus vulgaris L.) seed germination was investigated. The obtained results showed that the untreated OMW inhibited the seed germination of T. turgidum and P. vulgaris seeds. OMW treatment with red clay followed by dilution (95% water) resulted in 87 and 30% germination of P. vulgaris and T. turgidum, respectively. While, the treatment of OMW with sawdust and dilution at 95% resulted in 51 and 26% germination of P. vulgaris and T. turgidum, respectively.

Abstract P1129: Directing Revascularization In Vivo With Local Controlled Release Of An Optimized Angiogenic Growth Factor Cocktail

Reduced vascular perfusion due to aging, ischemia, or injury impedes healing and tissue function in conditions like skin ulcers and myocardial infarction, motivating development of therapies to restore vasculature locally in target tissues. We hypothesize that specific combinations of signaling molecules stimulate angiogenesis and vascular remodeling in the local tissue environment to increase perfused vessel density. Using a vascular tissue engineering approach with a fractional factorial design of experiments (DOE), we evaluated in vivo angiogenesis of combinations of ten growth factors, cytokines and/or enzymes including VEGF, bFGF, Shh, PDGF, IGF-1, EGF, TGF-β1, Ang-1, MCP-1 and MMP-9 in a subcutaneous gel plug assay in the WT immune competent rat. Our initial assessment with Matrigel identified 5 factors that maximized CD31+ vessel lumen density and aSMA+ encoated vessels at 7 days, warranting further evaluation. We developed a fully defined biomaterial system with covalently bound heparin to alginate mixed with collagen type 1 as an injectable gel. This defined biomaterial prolonged protein release up to 14 days in vitro versus Matrigel and unmodified alginate (2-4 days). The defined biomaterial was used for a second round DOE to deliver high (2 μg) and low (0.5 μg) doses of VEGF, bFGF, Shh, PDGF, and/or IGF-1. The defined biomaterial alone enhanced average lumen diameter 15-fold and endothelial cell infiltration 12-fold versus Matrigel. Perfused lumen density increased 16-fold with high Shh; aSMA-positive lumen wall area increased 4-fold with high VEGF, PDGF, and IGF-1; perfused vessel size increased 3-fold with high VEGF, bFGF, and Shh; and endothelial cell recruitment increased 2-fold with high IGF-1 relative to unloaded controls after 7 days in vivo. Empirical testing of 2- to 5-factor combinations showed that cocktail potency required initiation of angiogenic sprouting by VEGF or bFGF and vascularization responses were strongest in the presence of Shh and IGF-1. In conclusion, we identified sets of highly potent cocktails and leveraged controlled release from a defined biomaterial as a tailored revascularization therapy for local angiogenesis, vascular remodeling, and tissue regeneration.

Growth of Fe3C-VACNT surfaces by metal dusting under plasma carburizing: Fractional factorial study and correlation with morphological and structural aspects

This study investigates the development of surfaces that combine wear-resistance and solid lubrication properties using single low-temperature plasma carburizing treatments associated with the metal dusting phenomenon. The surfaces consisted of a regular cementite (Fe3C) layer and a film composed by vertically aligned carbon nanotubes (VACNT) grown over the carburized layer. For that, specimens of AISI 1005 steel were used as a substrate. A fractional factorial design of experiments was conducted to identify the best processing conditions to achieve the required Fe3C-VACNT surfaces. Morphological and structural aspects of the surfaces were assessed by scanning and transmission electron microscopy, X-ray diffraction, and Raman spectroscopy. The results show that the carburizing performed between 600 and 700 °C and with plasma power densities ≥0.30 W/cm2 were effective for developing the bilayer surfaces. A signature of that process was a temporal increase of the plasma current. According to a created statistical model, the most influential experimental parameters in the average power plasma density were output voltage, %CH4 in the gas mixture, and duty cycle. The surfaces were able to reduce the friction coefficient to values down to 0.08 and decrease the wear rate by 25 to 70 %, depending on their characteristics.

Screening autism-associated environmental factors in differentiating human neural progenitors with fractional factorial design-based transcriptomics

Research continues to identify genetic variation, environmental exposures, and their mixtures underlying different diseases and conditions. There is a need for screening methods to understand the molecular outcomes of such factors. Here, we investigate a highly efficient and multiplexable, fractional factorial experimental design (FFED) to study six environmental factors (lead, valproic acid, bisphenol A, ethanol, fluoxetine hydrochloride and zinc deficiency) and four human induced pluripotent stem cell line derived differentiating human neural progenitors. We showcase the FFED coupled with RNA-sequencing to identify the effects of low-grade exposures to these environmental factors and analyse the results in the context of autism spectrum disorder (ASD). We performed this after 5-day exposures on differentiating human neural progenitors accompanied by a layered analytical approach and detected several convergent and divergent, gene and pathway level responses. We revealed significant upregulation of pathways related to synaptic function and lipid metabolism following lead and fluoxetine exposure, respectively. Moreover, fluoxetine exposure elevated several fatty acids when validated using mass spectrometry-based metabolomics. Our study demonstrates that the FFED can be used for multiplexed transcriptomic analyses to detect relevant pathway-level changes in human neural development caused by low-grade environmental risk factors. Future studies will require multiple cell lines with different genetic backgrounds for characterising the effects of environmental exposures in ASD.

Factorial Design Statistical Analysis and Optimization of the Adsorptive Removal of COD from Olive Mill Wastewater Using Sugarcane Bagasse as a Low-Cost Adsorbent

This work highlights the elimination of chemical oxygen demand (COD) from olive mill wastewater using sugarcane bagasse. A 25−1 fractional factorial design of experiments was used to obtain the optimum conditions for each parameter that influence the adsorption process. The influence of the concentration of sugarcane bagasse, solution pH, reaction time, temperature, and agitation speed on the percent of COD removal were considered. The design experiment describes a highly significant second-order quadratic model that provided a high removal rate of 55.07% by employing optimized factors, i.e., a temperature of 60 °C, an adsorbent dose of 10 g/L, a pH of 12, a contact time of 1 h, and a stirring speed of 80 rpm. The experimental data acquired at optimal conditions were confirmed using several isotherms and kinetic models to assess the solute interaction behavior and kind of adsorption. The results indicated that the experimental data were properly fitted with the pseudo-first-order kinetic model, whereas the Langmuir model was the best model for explaining the adsorption equilibrium.

Flow virometry for water-quality assessment: protocol optimization for a model virus and automation of data analysis

Flow virometry (FVM) can support advanced water treatment and reuse by delivering near-real-time information about viral water quality. But maximizing the potential of FVM in water treatment and reuse applications requires protocols to facilitate data validation and interlaboratory comparison—as well as approaches to protocol design to extend the suite of viruses that FVM can feasibly and efficiently monitor. We address these needs herein. First, we optimize a sample-preparation protocol for a model virus using a fractional factorial experimental design. The final protocol for FVM-based detection of T4—an environmentally relevant viral surrogate—blends and improves on existing protocols developed using a traditional pipeline-style optimization approach. Second, we test whether density-based clustering can aid and improve analysis of viral surrogates in complex matrices relative to manual gating. We compare manual gating with results obtained through algorithmic clustering: specifically, by leveraging the OPTICS (Ordering Points to Identify Cluster Structure) ordering algorithm. We demonstrate that OPTICS-assisted clustering can work as well or better than manual gating of FVM data, and can identify features in FVM data difficult to detect through manual gating. We demonstrate our combined sample-preparation and automated data-analysis pipeline on wastewater samples augmented with viral surrogates. We recommend use of this protocol to validate instrument performance prior to and alongside application of FVM on environmental samples. Adoption of a consistent, optimized analytical approach that (i) centers on a widely available, easy-to-use viral target, and (ii) includes automated data analysis will bolster confidence in FVM for microbial water-quality monitoring.

Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars

Fiber-reinforced polymer (FRP) composites are increasingly used in concrete structures owing to their superior corrosion resistance. However, FRP-reinforced concrete (RC) structures exhibit less ductile response compared to steel RC structures. Recently, the use of basalt fiber reinforced concrete (BFRC) reinforced with BFRP bars was investigated to achieve a reasonable level of ductility in BFRC-BFRP one-way slabs. The shear behavior of such a slab depends on different design parameters. This paper aims to identify the impact of each design parameter on the shear behavior of BFRC-BFRP one-way slabs using a fractional factorial design of experiment (DOE). A 3D finite element model was first developed and validated against available experimental results. The developed model is then used to conduct a sensitivity analysis considering five significant factors that influence the shear behavior of BFRC-BFRP one-way slabs. These factors are the longitudinal reinforcement ratio, shear span-to-depth ratio, effective depth, concrete compressive strength, and volume fraction of BMF. Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean Vpred/Vexp of 0.97 and a COV of 17.91%.

A Parametric Study of Optimum Road Modular Hinged Frames by Hybrid Metaheuristics.

This paper addresses a study of cost-optimal road modular hinged frames. The performance of three hybrid metaheuristics is assessed through a fractional factorial design of experiments. The results allow for selecting and calibrating the hybrid simulated annealing to solve the combinatorial optimization problem. By varying the horizontal span from 8 to 16 meters and the earth cover from 1 to 5 meters, 25 different structural configurations are studied. The calibrated methodology is applied to obtain nine different frames with optimal costs for each configuration. The study of the economic, environmental and geometrical characteristics of the 225 optimum structures allows for the development of a regression analysis. With R2 correlation coefficients close to the unit, the expressions form a valuable tool for calculating the final cost, associated emissions, embodied energy and particular geometric characteristics. The optimum structures present slender and densely reinforced designs. In addition, some structures show considerable reductions in the shear reinforcement, something solved by localized increases in longitudinal reinforcement.

Optimization of Grinding Parameters of Tool Steel by the Soft Computing Technique.

Grinding is one of the most complex and accurate machining processes, and the efficiency of the grinding wheel depends significantly on its surface properties. This work aims to propose an algorithmic manner that reduces the cost and time to conduct grinding of an optimized DIN 1.2080 tool steel (SPK) using a soft computing technique to obtain the best combination of input parameters including depth of cut (20, 40, 60 μm), wheel speed (15, 20, 25 m/s), feed rate (100, 300, 500 mm/s), and incidence angle (0, 30, 45 de grees) with respect to output parameters consisting of average surface roughness and specific grinding energy. According to the input parameters and their levels, an experiment using fractional factorial design of experiment (RFDOE) was designed. Later on, two parallel feed-forward backpropagation (FFBPNN) networks with similar topology made up of 4, 11, and 1 units in their input, hidden, and output layers are trained, respectively. After sensitivity analyses of networks for determination of the relative importance of input variables, a genetic algorithm (GA) adopting linear programming (LP) based on Euclidean distance is coupled to networks to seek out the best combinations of input parameters that result in minimum average surface roughness and minimum specific grinding energy. The findings revealed that RFDOE provides valid data for training FFBP networks with a total goodness value of more than 1.99 in both cases. The sensitivity analyses showed that feed rate (38.97%) and incidence angle (33.94%) contribute the most in the case of average surface roughness and specific grinding energy networks, respectively. Despite the similar surface quality based on scanning electron microscopy (SEM), the optimization resulted in an optimized condition of the depth of cut of 25.23 μm, wheel speed of 15.02 mm/s, feed rate of 369.45 mm/s, and incidence angle of 44.98 de grees, which had a lower cost value (0.0146) than the optimum one (0.0953). Thus, this study highlights that RFDOE with a hybrid optimization using FFBP networks-GA/LP can effectively minimize both average surface roughness and specific grinding energy of SPK.

Dissolution Assay of Bupropion/Naltrexone Hydrochloride Salts of Bilayer Composition Tablets Following the Development and Validation of a Novel HPLC Method

Compounded medicinal products containing bupropion hydrochloride (BUP·HCl) and naltrexone hydrochloride (NTX·HCl) are available as adjunct therapy for the management of weight in obese/overweight adults. The present work describes the development and validation of a novel RP-HPLC method for a simultaneous quantitation during the dissolution of both drugs from compounded bilayer composition tablets. The method involves a Nucleosil 100-3 C-18 column (4.6 × 150 mm) and a mobile phase of a 70%/30% v/v ACN/KH2PO4·H2O aqueous solution of a 5 mM concentration. The flow rate was set at 1.35 mL/min and the detection was conducted using UV spectrophotometry (λmax 214 nm). The method was validated according to the ICH guidelines and fulfilled the specifications for the specificity, linearity, accuracy, precision and stability for both the sample and standard solutions. Furthermore, the robustness of the method was evaluated by applying a fractional factorial experimental design and by utilizing both graphical and statistical approaches to identify the HPLC factors that should be strictly controlled during the analysis. The method proved to be suitable for the analysis of the dissolution samples and, consequently, the release of BUP·HCl and NTX·HCl from the formulations.

Development of QuEChERS-based multiresidue analytical methods to determine pesticides in corn, grapes and alfalfa

Analytical methods based on QuEChERS and liquid chromatography-tandem mass spectrometry were developed for the determination of 42 polar and semi-polar pesticides in three representative vegetable matrices, viz. corn, grapes and alfalfa. A 26-2 fractional factorial experimental design was used to cost-effectively optimize the extraction procedure. The optimal analytical approaches were validated in terms of linearity, sensitivity, trueness, and precision. Most of the target pesticides showed a relative recovery of 70–120 %. Moreover, limits of detection (between 0.01 ng/g and 20 ng/g) were below the maximum residue levels set for the target analytes in nearly all cases. Analysis of real samples showed the presence of five pesticides in grapes and alfalfa at concentrations between the method LOQs and 40 ng/g. To the authors’ knowledge, these methods are the first ever described for the determination of 6, 13 and 24 of the 42 target pesticides measured in corn, grapes and alfalfa, respectively.

Unraveling the Seedless Growth of Gold Nanostars through Fractional Factorial Design

Gold nanostars (AuNSs) are anisotropic nanoparticles that display morphology-tunable optical properties. Most AuNS synthetic methods require a two-step procedure and the use of cytotoxic and/or strongly bound surfactants, which complicate biomedical application. The seedless synthesis of AuNSs overcomes those limitations by using biocompatible Good’s buffers, such as HEPES, as reducing and stabilizing agents. However, the simplicity of this one-pot protocol (i.e., two reagents and one solution) can result in high batch-to-batch variability, as several factors are thought to affect the growth of the nanostars. In this paper, we used a fractional factorial design of experiments to identify five factors (i.e., HEPES concentration, Au3+ concentration, temperature, pH, and stirring) that control the growth, morphology, and optical properties of AuNSs. Notably, we identified several secondary interactions, most prominently, temperature–Au3+ concentration and pH–HEPES concentration, for which simultaneous changes of both factors induced larger effects than the sum of effects of each factor alone. These results provide new insights into the growth of AuNSs, explaining some of the discrepancies in the literature regarding the impact of certain factors and highlighting the importance of characterizing secondary interaction effects to improve the synthesis of gold nanoparticles with desired properties.

PFSA Membrane Thickness Impact on Chemical Degradation Rates

As the large-scale commercialization of proton exchange membrane fuel cells (PEMFC) for numerous applications, including heavy-duty trucks draws nearer, there is increasing interest in optimizing fuel cell membranes for both improved efficiency and durability. One of the major membrane attributes being considered for optimization is thickness. The current range of (perfluorosulfonic acid) PFSA membrane thicknesses employed for commercial applications range from 8 -25 µm. As with most adjustable materials parameters, there are a host of properties (cost, gas permeability, proton conductivity, etc.) that require co-optimization to provide the overall preferred position. For example, thin membranes will minimize proton resistance, facilitating high power densities, but will simultaneously allow increased gas crossover fluxes that can contribute to both reduced fuel efficiency and increased oxidative stress. On the other end of the spectrum, thick membranes will decrease gas crossover fluxes, offering improved fuel efficiency while simultaneously decreasing power density. A major question surrounding the tradeoffs of membrane thickness involves the chemical durability impact. Here, we report our investigations of PFSA membrane chemical durability as a function of thickness. For the studies reported here, a thickness series (8, 12 and 20 µm) of ePTFE reinforced Nafion®-like PFSA standalone membranes (SAMs) were prepared.A two-pronged approach was taken for this study. The first involves investigation of intrinsic chemical stability of the ionomer as a function of membrane thickness using an ex-situ H2O2 vapor test. The second investigative mode, which targets the oxidative stress generated by crossover gas flux, employs OCV durability tests of full MEAs. In addition to membrane thickness, gas crossover rates are known to be functions of membrane hydration and gas pressures.1,2 Accordingly, a 3(4-1) fractional factorial experimental design was executed to probe the role of membrane thickness as well as the other factors known to affect gas crossover. The fractional factorial design allows all main effects to be determined and further allows estimation of two factor interactions, if present.References T. Sakai, H. Tanenaka, E, Torikai, “Gas Diffusion in Dried and Hydrated Nations” J. Electrochem. Soc., 1986, 133, 88-92R. Jiang, T. Fuller, S. Brawn, C. Gittleman, “Perfluorocyclobutane and poly(vinylidene fluoride) blend membranes for fuel cells” Electrochimica, Acta, 2013, 110, 306-315

Optimization of chitin demineralization from shrimp shells waste by Response Surface Methodology (RSM)

The solubilization of chitosan is a very important parameter for its use in various fields. The ash content of chitosan is an important parameter because it can affect its solubility and viscosity, as well as other important characteristics. The objective of the present study is to optimize the demineralization step in the production of chitosan, using a fractional factorial experimental design, where the concentration of Hcl, the reaction time, the temperature, the size particles and the solid-liquid ratio varied. The results showed that a quadratic model was suggested for the demineralization yield and the ash rate showing high accuracy with R2 = 0.99 and 0.97, respectively. The developed models indicated a significant effect of the five studied factors except the temperature (B), and the solid-liquid ratio (E) have insignificant effects on the reaction yield. Optimal selectivity was 39.77% and 0.14% for yield and ash content respectively, reached for HCl concentration of 2N, reaction time of 0.5 h, reaction temperature of 50° C, a solid/liquid ratio (1/10 g/l) and a particle size of 1 mm. In conclusion, the conditions optimized for the demineralization process could be used for the industrial scale production of chitin for agricultural, biomedical and biotechnological purposes.