Optimal design of experiments for parameter identification in electrodialysis models

Current status and future prospects of membrane separation processes for value recovery from wastewater

Resource constraints and deteriorating environment have made it necessary to look for intensification of the industrial processes, to recover value from spent streams for reuse. The development of reverse osmosis has already established that water can be recovered from aqueous streams in a cost-effective and beneficial manner to the industries. With the development of several membrane processes and membrane materials, the possibility of recovering value from the effluents looks like a workable proposition. In this context, the potentialities of the different membrane processes in value recovery are presented. Among the pressure-driven processes, reverse osmosis can be used for the recovery of water as value. Nanofiltration has been used for the recovery of several dyes including crystal violet, congo red, methyl blue, etc., while ultrafiltration has been used in the fractionation of different solute species using membranes of different pore-size characteristics. Diffusion dialysis is found useful in the separation of acids from its salt solutions. Bipolar membrane electrodialysis has the potential to regenerate acid and base from salt solutions. Thermally driven membrane distillation can provide desalinated water, besides reducing the temperature of hot discharge streams. Passive membrane processes such as supported liquid membranes and membrane-assisted solvent extraction have been found useful in separating minor components from the wastewater streams. The details are discussed to drive home that membrane processes can be useful to achieve the objectives of value recovery, in a cost-effective manner through process intensification, as they are more compact and individual streams can be treated and value used seamlessly.

Bayesian based reaction optimization for complex continuous gas–liquid–solid reactions

In recent years, self-optimization strategies have been gradually utilized for the determination of optimal reaction conditions owing to their high convenience and independence from researchers' experience.

Characteristics of heavy metal separation and determination of limiting current density in a pilot-scale electrodialysis process for plating wastewater treatment

Recent development in industry has led to increased water usage, while intensifying water shortage. Electrodialysis has been proposed as a technique for minimizing the generation of secondary environmental pollution problems and effectively treating harmful substances such as heavy metals in industrial wastewater. As electrodialysis is affected by several factors, it is crucial to provide necessary information about the operating elements. This study investigates the effect of linear flow velocity on the removal of heavy metals in an electrodialysis pilot plant. The results of the experiment showed that increasing the linear flow velocity from 0.6 to 5.1 cm/min increased the voltage from 17.3 to 40 V. In addition, the limiting current density (LCD) showed a linear relationship with the linear flow velocity, increasing from 1.4 to 5.9 A/m2 as the linear flow velocity increased proportionally in the same voltage range. The empirical correlation coefficients a and b for the mass transfer coefficient K, which can be expressed as a nonlinear function of the linear flow velocity, were estimated to be 1.8519 and 0.7016, respectively. In the batch operation, the ion-separation rate in the electrodialysis process was estimated with the shift order kinetics of the first-order and zero-order constants via regression analysis of experimental data. The ion separation rate in the diluate and the ion concentration rate in the concentrate decrease as the experiment number increase. This may be due to the reverse diffusion of ions transferring to the diluate owing to the high concentration of ions in the concentrate. Therefore, ion concentration in the concentrate has to be maintained at an appropriate level. Copper ions are deposited on the cathode electrode surface, although not uniformly.

Application of the Design of Experiments and Computational Fluid Dynamics to Bow Design Improvement

Techniques of the design of experiments (DOE) and computational fluid dynamics (CFD) were applied for improving the bow shape of a tanker hull. Through this, a hull that could reduce the added resistance in waves was derived. The key design elements of the bow shape were selected as parameters for design optimization and added resistance in the short-wavelength region was interpreted through CFD considering the operational condition of the full scale ship. For design parameter changes, the number of analyses was minimized by applying DOE. The regression equation for calculating added resistance was derived using bow-shape design parameters by applying the response surface method and regression analysis to obtain the optimal hull with minimal added resistance was derived. The methodology was applied to an Aframax tanker hull form, and the derived added resistance regression equation and the added resistance value obtained through CFD analysis showed a difference of approximately 1%. The model test results of the improved hull form showed that the added resistance was reduced by 52% in comparison to that obtained for the original hull form.

Design, synthesis and biological evaluation of novel α-aminophosphonate oxadiazoles via optimized iron triflate catalyzed reaction as apoptotic inducers

α-aminophosphonate oxadiazoles (5a-m) were prepared in high yields by reacting of 1,3,4-oxadiazole acetohydrazide (3) with appropriate aldehydes and diethyl phosphite under Kabachnik-Fields conditions using Iron triflate as a catalyst. The reaction conditions were optimized using D-optimal experimental design. Possible reaction mechanisms were considered, and structures of the new products were based upon compatible elementary and spectroscopic evidence. In vitro antitumor activities of these compounds were evaluated against human cancer cell lines of colon (HCT116), breast (MCF7) and liver (HepG2) and compared with anticancer drug, Doxorubicin, employing standard MTT assay. Compounds 5i and 5l demonstrated good antiproliferative activities against HCT116 tumor cells comparable to doxorubicin with low cytotoxicity towards normal fetal colon cell (FHC). Additionally, their capacity to activate apoptosis cascade was studied in HCT116 cell line by investigating the activation of proteolytic caspases cascade, the levels of Cytochrome C, Bax and Bcl-2. Active caspase-3 level was enhanced by 6-8-folds in HCT116 cell line when stimulated with compounds 5i and 5l compared to the control. The level of Caspases 8 & 9 was also increased signifying that intrinsic and extrinsic pathways are both activated. They also induced Bax and down regulated Bcl-2 protein level in addition to over-expressing Cytochrome C level in HCT116 cell line. Also, HCT116 cell cycle was mainly arrested at the Pre-G1 and G2/M phases when treated with compounds 5i and 5l.

The Impact of Global Sensitivities and Design Measures in Model-Based Optimal Experimental Design

In the field of chemical engineering, mathematical models have been proven to be an indispensable tool for process analysis, process design, and condition monitoring. To gain the most benefit from model-based approaches, the implemented mathematical models have to be based on sound principles, and they need to be calibrated to the process under study with suitable model parameter estimates. Often, the model parameters identified by experimental data, however, pose severe uncertainties leading to incorrect or biased inferences. This applies in particular in the field of pharmaceutical manufacturing, where usually the measurement data are limited in quantity and quality when analyzing novel active pharmaceutical ingredients. Optimally designed experiments, in turn, aim to increase the quality of the gathered data in the most efficient way. Any improvement in data quality results in more precise parameter estimates and more reliable model candidates. The applied methods for parameter sensitivity analyses and design criteria are crucial for the effectiveness of the optimal experimental design. In this work, different design measures based on global parameter sensitivities are critically compared with state-of-the-art concepts that follow simplifying linearization principles. The efficient implementation of the proposed sensitivity measures is explicitly addressed to be applicable to complex chemical engineering problems of practical relevance. As a case study, the homogeneous synthesis of 3,4-dihydro-1H-1-benzazepine-2,5-dione, a scaffold for the preparation of various protein kinase inhibitors, is analyzed followed by a more complex model of biochemical reactions. In both studies, the model-based optimal experimental design benefits from global parameter sensitivities combined with proper design measures.