Manpreet S. Bhatti

Electrocoagulation removal of Cr(VI) from simulated wastewater using response surface methodology.

The present study envisages the performance of a laboratory scale electrocoagulation system for the removal of Cr(VI) from 100 mg l(-1) solution using Al-Al electrodes with an effective surface area of 100 cm(2), and placed 15 mm apart. The interaction between voltage x time, and amperage x time best explained the Cr(VI) reduction efficiency with the coefficient of determination (R(2)) being 0.8873 and 0.9270 respectively. Similarly, the square root of energy consumption in Cr(VI) reduction had a linear correlation with voltage x time (R(2)=0.8949), whereas, amperage x time better explained energy consumption (R(2)=0.9400). Response surface methodology was used for the optimization of process variables (pH, voltage and treatment time), response modeling and predictions. Maximum Cr(VI) reduction efficiency of 90.4% was achieved at pH 5, 24 V and 24 min treatment time, and the treatment consumed 137.2 KWh m(-3) of electrical energy. Multiple response optimization for maximizing Cr(VI) reduction efficiency and minimizing energy consumption showed 49.6% Cr(VI) removal at pH 5, 12.8 V and 24 min treatment time. The response models developed explained 95.2% variability for Cr(VI) reduction efficiency and 99.4% variability for energy consumption. Results of the prediction models were validated through laboratory scale batch experiments.

Screening and RSM optimization for synthesis of a Gum tragacanth–acrylic acid based device for in situ controlled cetirizine dihydrochloride release

The present research work was aimed at the development and optimization of a Gum tragacanth–acrylic acid based hydrogel for in situ release of cetirizine dihydrochloride under different pH conditions such as 2.0, 7.0 and 9.2 at 37 °C. Various process variables like solvent, temperature, pH, treatment time, initiator molar ratio, concentration of monomer and cross-linker were screened using a fractional factorial design approach. Using a half normality plot, the most significant parameters for maximizing swelling are found. These significant parameters (solvent, pH and monomer) are further optimized using center composite design. The ANOVA model predicted that the interaction between pH and monomer concentration had an antagonistic effect on percentage swelling. The sequential experimental design approach was able to optimize the reaction parameters for getting the candidate polymer with maximum swelling capacity, thereby maximizing water absorption capacity by fivefold. Characterization of the candidate hydrogel Gt-cl-poly(AA) was done using FTIR and SEM techniques. The candidate polymer with maximum water absorption capacity was found to exhibit maximum drug absorption which later on was released in a Case II diffusion manner at pH 2.0 and 7.0. However, a non-Fickian mechanism was exhibited at pH 9.2. The hydrogel has been found to show colon specific release behavior of the drug. The initial diffusion coefficient has a greater value than the later diffusion coefficient indicating a higher drug release rate during the early stage.

Response surface methodology and optimized synthesis of guar gum-based hydrogels with enhanced swelling capacity

Guar gum based hydrogel was optimally synthesized using a response surface methodology (RSM) approach for enhanced swelling capacity. Maximization of the water absorption capacity of the synthesized hydrogel was achieved through sequential experimental design based optimization. A fractional factorial screening (Resolution-IV) approach was used to screen significant process variables for maximization of percentage swelling in phase-1. Studied reaction parameters were: (i) monomer concentration, (ii) initiator concentration, (iii) cross linker concentration, (iv) polymerization time, (v) reaction temperature, (vi) vacuum level, and (vii) pH of reaction mixture. A Pareto chart indicated monomer concentration, pH and initiator concentration as significant process variables which were further optimized using full factorial design (23) in phase-2. RSM based center composite design (CCD) was applied to maximize the percentage swelling for the two most significant variables (pH and initiator concentration) in phase-3. Statistical modeling using ANOVA predicted a near neutral range for pH (∼7.0) and an initiator concentration of 21–23 × 10−6 mol L−1 as optimum operating conditions for maximizing the percentage of swelling (5307%). Hydrogels were found to be highly pH sensitive and should be kept in a narrow range for maximization of percentage swelling. Thus, the sequential experimental design was helpful in achieving two fold increases in percentage swelling in a systematic way. Synthesized super absorbent polymers can be used as effective water-saving materials for horticultural and agricultural applications.

Optimal response surface design of Gum tragacanth-based poly[(acrylic acid)-co-acrylamide] IPN hydrogel for the controlled release of the antihypertensive drug losartan potassium

The present study proposes the development and optimization of a new interpenetrating polymer network (IPN), consisting of Gum tragacanth, poly(acrylic acid) (PAA), and poly(acrylamide) (PAAm), for the in situ controlled release of losartan potassium under different pH conditions at 37 °C. Solvent amount and monomer concentration were chosen as the process variables and percentage swelling was taken as the process response. ANOVA model fits were made for the data and gave the cubic model as the best fit, with a predicted R2 = 0.976. The maximum desirability was observed to be 19.63 mL solvent and 3.28 × 10−4 mol L−1 monomer concentration, at which the percentage swelling was found to be 266. Whereas, at 23.7 mL solvent and 6.7 × 10−4 mol L−1 monomer, the percentage swelling was found to be at the minimum (139%). The model was validated at the optimal points for developing devices with the maximum swelling capacity. Drug release through the synthesized matrix was found to show non-fickian behavior at pH 2.0, 7.0, and 9.2, with an increasing trend in gel characteristic constant (k). At each pH medium, the initial diffusion coefficient (DI) was found to be higher than the lateral diffusion coefficient (DL).

Optimizing flank wear and surface roughness during hard turning of AISI D3 steel by Taguchi and RSM methods

The study attempts to investigate tool wear (flank wear) and surface roughness during finish hard turning of AISI D3 steel (58HRC) with coated carbide (TiSiN-TiAlN coated) cutting tool. Taguchi L9 (3)3 orthogonal array has been applied for experimental design. S/N ratio and ANOVA analyses were performed to identify significant parameters influencing tool wear and surface roughness. The cutting speed and feed were the most significant factors influencing tool wear (flank wear), and feed is the most significant factor influencing surface roughness (Ra). Mathematical models for both response parameters i.e. tool wear and surface roughness were obtained through regression analysis. The confirmation experiments carried out at optimal combination of parameters given by Taguchi’s analysis, predicted the response factors with less than 5% error. In addition, Desirability function module in RSM was applied to arrive at the optimal setting of input parameters to minimize tool wear and surface roughness. The optimal solution provided by desirability function optimization was compared with the optimal setting of parameters given by Taguchi analysis. The optimization results provided by both techniques are in close proximity.

A review of empirical modeling techniques to optimize machining parameters for hard turning applications

There has been a tremendous development in the field of modeling and optimization methods starting from Taylor’s tool life model. Use of costly tools such as polycrystalline cubic boron nitride, polycrystalline diamond and ceramics in high-end computer numerical control machining forces the researcher to minimize the experimental runs to achieve the best cutting conditions with minimum tool wear and overall production cost. Machining process optimization to achieve said objectives comprises selecting optimum cutting parameters by applying low-cost mathematical models. This article attempts to evaluate the applicability of various modeling and optimization methods to specific response parameters in hard turning problems. Various empirical modeling techniques such as linear regression modeling, artificial neural networks, polynomial and fuzzy modeling along with process optimization through Taguchi, response surface methodology and genetic algorithm for hard turning applications have been discussed in length to provide the production engineers a ready database to compare relative merits and suitability of these techniques for a particular machining application. Also, article discusses integration of different modeling and optimization techniques to achieve desired goals when a single optimization technique is not able to provide the acceptable solution. The last part of the article highlights the current trends in hard turning applications and research priorities for future work.

Experimental design optimization for electrochemical removal of gentamicin: toxicity evaluation and degradation pathway.

Electrochemical degradation of gentamicin was achieved using a laboratory scale electrochemical reactor by optimizing pH, current density and treatment time. A two step statistical optimization was performed as per factorial design and center composite design (CCD). A Pareto chart was used for selecting statistically significant effects and an analysis of variance (ANOVA) table indicated significant curvature. Thus adding additional experimental runs improved the model fitting through a second order model. Maximum degradation was predicted at a pH of 6.7, 70 A m(-2) and 45 min. The experimental data fitted well through a reduced quadratic model with R(2) equal to 0.945. The toxicity of degradation products as determined by disc diffusion assay employing Pseudomonas aeruginosa strain was found to be reduced by 55%. The degradation pathway of gentamicin was studied using mass spectral (MS) analysis. Pure gentamicin showed a molecular ion peak at m/z 478 ([M + 1](+)), and after addition of NaCl as electrolyte, the mass peak was observed at m/z 523. After 15 min of electrochemical treatment, a new peak appeared at m/z 316 due to the loss of one pyran moiety. After 45 min of electrochemical treatment, another peak appeared at m/z of 478 due to loss of two Na(+) from gentamicin.

RSM and ANN-GA Experimental Design Optimization for Electrocoagulation Removal of Chromium

The present study was aimed at optimizing electrocoagulation removal of hexavalent chromium using iron electrodes. Process variables investigated were chromium concentration, pH, current density (or voltage) and treatment time, and the responses measured were chromium removal efficiency and energy consumption. Using the experimental results, the treatment process was modeled by response surface methodology (RSM) and by artificial neural network-genetic algorithm (ANN-GA). The optimum current density for energy efficient chromium removal was found to be 20–40 A/m2 for treatment time of 10 min. Current density beyond the optimum range had a cascading effect on chromium removal efficiency.

Recycling of Waste Poly(ethylene terephthalate) Bottles by Alkaline Hydrolysis and Recovery of Pure Nanospindle-Shaped Terephthalic Acid

Poly(ethylene terephthalate) (PET) is a versatile engineering plastic which exhibits exceptional mechanical and thermal properties. Huge amounts of PET are consumed in various industries such as food packaging industry, textile industry, in the manufacturing of audio, video tapes and X-ray films and so on. But due to its substantial fraction by volume in water bodies and its high persistence to the atmospheric and biological agents, it could be considered as a hazard substance. Thereby chemical recycling of PET serves as a solution to solid waste problem as it transforms PET into its monomers via hydrolysis. Chemical recycling of post consumed waste PET bottles via alkaline hydrolysis is the main aim of this paper. Operating parameters such as reaction time and temperature were optimized for the conversion of PET into nanospindle-shaped terephthalic acid (TPA). Depolymerization of PET was carried out via alkaline hydrolysis by varying reaction time and temperature and maximum yield of 92% was obtained at 200 °C with reaction time of 25 minutes. The formed TPA nanospindles were further characterized in detail which exhibited high crystallinity, purity and fascinating thermal and surface properties.

Performance Evaluation of Milling of Inconel-625 Under Minimum Quantity Lubrication

Abstract In the present investigation an attempt has been made to explore the potential of MQL milling of Inconel-625 with coated carbide tool. The performance is compared in terms of surface roughness and tool flank wear in MQL milling with dry and wet milling operation of Inconel-625. The milling under MQL condition gives superior results over wet and dry milling operations. Factorial design of experiments ANOVA analysis was applied to investigate the statistically significant parameters. RSM-Desirability function optimization was applied to find out optimal setting of parameters to minimize tool wear and surface roughness in MQL machining of Inconel-625.