Freeze drying process: real time model and optimization

Freeze drying is a separation process based on the sublimation phenomenon. This process has the following advantages compared to the conventional drying process: the material structure is maintained, moisture is removed at low temperature (reduced transport rates), product stability during the storage is increased, the fast transition of the moisturized product to be dehydrated minimizes several degradation reactions. Freeze drying process has not been studied well enough. In order to put it to practice, a mathematical model based on fundamental mass and energy balance equations has been developed, based on a deterministic mathematical model proposed by Liapis and Sadikoglu [Drying Technol. 15 (3–4) (1997) 791], and used to calculate the amount of removed water and amount of residual water. The proposed model contains the freeze drying equations, which are solved by the orthogonal collocation and polynomial approximation—Jacobi method. The results show that the dynamic mathematical model represents well the process and is especially well suited for real time optimization. As a case study to illustrate the model utilization in a real time optimization procedure, the freeze drying process was optimized by the method of Successive Quadratic Programming (SQP) used for solution of non-linear equations, for skimmed milk and soluble coffee. The optimization procedure showed to be an important tool to improve the process performance since lower energy consumption and hence lower cost has been achieved to obtain the product with the same quality.     

New Hybrid Nanomaterial Based on Self-Assembly of Cyclodextrins and Cobalt Prussian Blue Analogue Nanocubes

Supramolecular self-assembly has been demonstrated to be a useful approach to developing new functional nanomaterials. In this work, we used a cobalt Prussian blue analogue (PBA, Co₃[Co(CN)₆]₂) compound and a β-cyclodextrin (CD) macrocycle to develop a novel host-guest PBA-CD nanomaterial. The preparation of the functional magnetic material involved the self-assembly of CD molecules onto a PBA surface by a co-precipitation method. According to transmission electronic microscopy results, PBA-CD exhibited a polydisperse structure composed of 3D nanocubes with a mean edge length of 85 nm, which became shorter after CD incorporation. The supramolecular arrangement and structural, crystalline and thermal properties of the hybrid material were studied in detail by vibrational and electronic spectroscopies and X-ray diffraction. The cyclic voltammogram of the hybrid material in a 0.1 mol·L⁻¹ NaCl supporting electrolyte exhibited a quasi-reversible redox process, attributed to Co²⁺/Co³⁺ conversion, with an E_1/2 value of 0.46 V (vs. SCE), with higher reversibility observed for the system in the presence of CD. The standard rate constants for PBA and PBA-CD were determined to be 0.07 and 0.13 s⁻¹, respectively, which suggests that the interaction between the nanocubes and CD at the supramolecular level improves electron transfer. We expect that the properties observed for the hybrid material make it a potential candidate for (bio)sensing designs with a desirable capability for drug delivery.     

Fluid catalytic cracking optimisation using factorial design and genetic algorithm techniques

Statistical techniques coupled with genetic algorithm (GA) were used to identify optimal values of key operational variables in fluid catalytic cracking (FCC) process. A Kellog Orthoflow F fluid catalytic cracking process model was considered. It is known as a highly nonlinear process with a large number of variables with strong interactions among them. A reduced process model was obtained through factorial design technique to be used as a process function in the optimisation work giving as result the operational conditions that maximise conversion without infringing operational restrictions with savings in computational burden and time. An increase of 8.71% in process conversion was achieved applying GA as optimisation technique. © 2012 Canadian Society for Chemical Engineering     

Recovery of carbon dioxide from sugarcane fermentation broth in the ethanol industry

Ethanol is one alternative to the use of petroleum-based fuels. It is produced on a large scale in Brazil from sugarcane to the magnitude of billions of liters per year. During the ethanol production step, a considerable amount of byproducts is obtained and treated as waste. Carbon dioxide is one of these byproducts and a substance of interest especially for food industries. Because the production of 1000 kg of ethanol generates approximately 950 kg of CO₂, this work intends to analyze a cryogenic distillation process for the production of CO₂ by means of computational simulations. The results obtained were in agreement with real operational conditions, achieving CO₂ concentrations up to 100% (v/v). With an initial CO₂ concentration of 95% (v/v), 7 separation stages were obtained, achieving the limit of 5 stages for higher CO₂ concentrations in the raw gas. The effect of initial CO₂ concentrations on the final product and the concentration profiles along the column are also presented. In order to optimize the process, it was observed that, for a maximum feed flow of 3333 kg/h (CO₂ concentration of 99%), the plant was able to obtain 10.48 kgCO₂/kW, recovering about 2828 kgCO₂/h at a final product concentration of 99.90% (v/v) at ?25 °C.     

Evaluation of optimisation techniques and control variable formulations for a batch cooling crystallization process

The mathematical optimisation of a batch cooling crystallization process is considered in this work. The objective is to minimize the standard deviation of the final crystal size distribution (CSD), which is an important feature in many industrial processes. The results with the problem written as a nonlinear programming and solved with the successive quadratic programming (SQP) coupled with the discretization of the control variable are compared with those obtained when SQP coupled with the parameterisation of the control variable is applied. Also it is proposed the implementation of the genetic algorithm (GA) coupled with parameterisation of the control variable. Extensive evaluations show that the SQP method is sensitive both to the parameterisation formulation and to the initial estimate. The solution with GA provided the control variable profile that leads to the minimum standard deviation of the final CSD. Nevertheless, it is a very time-consuming technique, which hampers its utilization in real time applications. However, its feature of global searching suggests its suitability in solving offline problems, in order to provide initial setup profiles. Bearing this in mind, it is proposed an algorithm which allows for the implementation of GA solution in a real time fashion, taking advantage of its robustness to find out the optimal solution.     

Off-line optimization and control for real time integration of a three-phase hydrogenation catalytic reactor

In order to develop and test the integration procedure, in this paper a real time process integration involving the optimization and control of the process is presented, in this case, with the two-layer approach. The used optimization algorithms were Levenberg–Marquardt and SQP that solve a non-linear least square problem subject to bounds on the variables. The two-layer approach is a hierarchical control structure where an optimization layer calculates the set points and manipulated variables to the advanced controller, which is based on the dynamic matrix control with constraints (QDMC). The non-isothermal dynamic model of the three-phase slurry catalytic reactor with appropriate solution procedure was utilized in this work (Vasco de Toledo, E. C., Santana, P. L., Maciel, M. R. W., & Maciel Filho, R. (2001). Dynamic modeling of a three-phase catalytic slurry reactor. Chemical Engineering Science, 56, 6055–6061). The model consists on mass and heat balance equations for the catalyst particles as well as for the bulk phases of gas and liquid. The model was used to describe the dynamic behavior of hydrogenation reaction of o-cresol to obtain 2-methil-cyclohexanol, in the presence of a catalyst Ni/SiO₂.     

Thermodynamic Analyses on Nanoarchitectonics of Perovskite from Lead Iodide: Arrhenius Activation Energy

Amongst the different perovskites being investigated for application in solar cells, one of the most frequently scrutinized is methylammonium lead iodide CH₃NH₃PbI₃ (or MAPbI₃), which is usually obtained by the reaction of lead iodide (PbI₂) with methylammonium iodide (MAI). Although this perovskite has been extensively studied and utilized in the manufacture of high-efficiency solar cells, its formation chemistry is still not well understood. Reliable experimental determination of the activation energy between PbI₂ and MAI has been difficult due to the rapid reaction at room temperature. In this work, we determined the activation energy by adopting the Arrhenius equation. This was possible by controlling the reaction using MAI vapor, instead of liquid solution. This procedure allowed the reaction to be carried out at temperatures of up to 150 °C. The formation of MAPbI₃ films was obtained by a two-step process: deposition of thin PbI₂ film by thermal evaporation and subsequent conversion into perovskite by exposure to MAI vapor. The conversion of PbI₂ to MAPbI₃ as a function of temperature was probed by X-ray diffraction. An activation energy of 0.12?±?0.02 eV was obtained. This low value explains the ease of MAPbI₃ formation at low temperatures, and partially explains its instability in environmental conditions.

     

Characterization of Crude and Partially Purified Lipase from Geotrichum candidum Obtained with Different Nitrogen Sources

Lipases from Geotrichum candidum were produced in two different medium: A = 12 % (w/v) clarified corn steep liquor (CCSL) + 0.6 % (w/v) soybean oil (SO) and B = 3.5 % (w/v) yeast hydrolysate (YH) + 0.7 % (w/v) SO. Lipases were partially purified from both media by hydrophobic interaction chromatography using 3.0 mol L^?1 of NaCl as mobile phase, and they were characterized in the crude and partially purified forms. The recovery of lipase activity from CCSL and YH via HIC were 96 and 94.3 %, and the purification factors were 44.3 and 86.7‐fold, respectively. All evaluated lipases had similar optimum pH (7.0–7.7), but, for the CCSL crude lipase, optimum temperature (47 °C) was 10 °C higher than others lipases evaluated. CCSL crude lipase possessed a higher thermo stability than YH crude lipase, e.g., at 37 °C (pH 7.0) the half‐life of CCSL crude lipase was 19.25 h and at pH 8.0 (30 °C) the half‐life was 48 h, which are five and ten times higher than with YH crude lipase, respectively. On the other hand, the YH crude lipase possessed a higher catalytic constant (k_cat = 2.3 min^?1) but with almost the same catalytic efficiency (K_m/k_cat = 32.12 mg mL min^?1) in relation to CCSL crude lipase. The lipases differ in biocatalytic properties between substrates, suggesting that the two lipases can be employed for different applications.     

Toward the prediction of porous membrane permeability from morphological data

One of the challenges in membrane technology is predicting permeability in porous membranes for liquid applications in an easy and inexpensive way. This is the aim of this work. To achieve this objective, several techniques can be considered. In this study, a morphological approach from two‐dimensional scanning electron micrographs is proposed. First, numerical membrane morphological parameters have been determined from micrographs by using the QUANTS tool, which applies a texture recognition process. Second, the obtained data have been fit to the Darcy's and Hagen–Poiseuille models to calculate permeations. The QUANTS results have also been compared with the ones obtained through a mercury porosimeter, which is a classic and well‐known methodology. Each parameter of the Hagen–Poiseuille model has been analyzed. A comparison between experimentally measured permeations and calculated ones has been performed. An even easier approach is proposed to predict flow rate with the only knowledge of membrane surface mean pore size. This method is based on cross‐section pore size interpolation by using function fits from surface mean pore sizes. The obtained results show a reasonable agreement between measured and computed results, making this technique a valid approach for predicting membrane permeability. POLYM. ENG. SCI., 56:118–124, 2016. © 2015 Society of Plastics Engineers