Semi-batch Process Research Articles

Multi-injection microstructured reactor for intensification of fast exothermic reactions: proof of concept

Quasi-instantaneous exothermic reactions lead to the formation of unwanted hot spots even when carried out in conventional microstructured reactors (MSR) with tube diameter of 100–1000 μm. For this reason, alternative MSR designs are warranted to enable process intensification of fast reactions with characteristic reaction times <1 s. The continuous multi-injection MSR, where one of the reactants is successively added to the main flow of reactants along reactor length, may improve temperature control. The latter was studied first theoretically using numerical simulations and then experimentally with the cyclisation of pseudoionone to α- and β-ionones as a model reaction. The multi-injection MSR made of low temperature co-fired ceramics (LTCC) led to a yield of α-ionone and β-ionone >0.98 reaching a 500-fold process intensification as compared to the conventional semi-batch process. The temperature profiles monitored by quantitative infrared thermal imaging confirmed an 8-fold reduced temperature rise compared to adiabatic temperature rise, which was achieved by injecting the reactants at three different injection points.

Characterization of the Yellow Croaker Larimichthys polyactis muscle Oil Extracted with Supercritical Carbon Dioxide and an Organic Solvent

Yellow croaker Larimichthys polyactis muscle oil was extracted using an environmental friendly solvent, supercritical carbon dioxide (SC-<TEX>$CO_2$</TEX>), in a semi-batch flow extraction process. SC-<TEX>$CO_2$</TEX> was applied at temperature <TEX>$35^{\circ}C$</TEX> to <TEX>$45^{\circ}C$</TEX> and <TEX>$150^{\circ}C$</TEX> to <TEX>$250^{\circ}C$</TEX> bar of pressure. The flow rate of <TEX>$CO_2$</TEX> (27.79 g/min) was constant throughout the entire 1.5 h extraction period. The oil extraction yield was influenced by the physical properties of SC-<TEX>$CO_2$</TEX> at different temperatures and pressures. The extracted oil was analyzed by gas chromatography to determine the fatty acid composition. According to our results, the SC-<TEX>$CO_2$</TEX> extracted oil was high in eicosapentaenoic acid and docosahexaenoic acid. In addition, the SC-<TEX>$CO_2$</TEX> extracted oil showed greater stability than n-hexane extracted oil based on the peroxide value and acid value. Thus, the quality of yellow croaker oil obtained by SC-<TEX>$CO_2$</TEX> extraction was slightly higher than that of oil obtained by n-hexane extraction.

A unified mechanism to quantitatively understand silica particle formation from tetraethyl orthosilicate in batch and semi-batch processes

Factors for controlling sizes of silica particles formed in the hydrolysis and condensation of silicon alkoxides were examined in batch and semi-batch processes with our model previously proposed. Particle sizes in the particle formation were simulated for buffer systems to reduce time-variation in pH. Effectiveness of the buffer system to suppress time-variation in ionic strength was experimentally verified in a silicon alkoxide concentration range of 0.01–0.1M. Comparison of experimental particle sizes with calculated ones showed that the addition of electrolytes slightly decreased surface potential of silica particles in both batch and semi-batch processes, and the surface potential values estimated for the semi-batch process were lower than that for batch process. In simulation of the number of particles formed in the processes, the particle number had strong dependences on surface potential and Debye–Hückel parameter. The simulated number of particles formed in semi-batch process was smaller than that in batch process under the same surface potential and Debye–Hückel parameter. The combination of the low surface potential and the small number of particles revealed that the semi-batch process was suitable for producing a small number of particles, which provides enlargement of size range of silica particles formed in the method.

From Kinetic Study to Thermal Safety Assessment: Application to Peroxyformic Acid Synthesis

This article proposes a kinetic and thermal study of the formic acid perhydrolysis in a semibatch process at various hydrogen peroxide concentrations (5.32–8.21 mol/L), formic acid molar inlet flow rates (0.04–0.22 mol/min), reaction temperatures (30–60 °C), and catalyst amount (0.0–10.6 g). A cation-exchange resin, i.e., Amberlite IR-120, was used as a catalyst. Synthesis and decomposition of peroxyformic acid were modeled by coupling the energy and mass balances, and a pseudohomogeneous model for the reaction kinetics. A nonlinear regression method was used to estimate the kinetic parameters, such as rate constant, and thermal parameters, such as reaction enthalpy. The knowledge of these parameters allows the determination of maximum temperature of the synthesis reaction (MTSR), the time to maximum rate under adiabatic condition (TMRad), and the criticality classification. These safety parameters are important to properly design the industrial reactor.

Semibatch anionic ring‐opening polymerization of octamethylcyclotetrasiloxane in emulsions: effect of the amount of seed polymer particles

AbstractSemibatch anionic ring‐opening polymerization of octamethylcyclotetrasiloxane with the use of seed polymer particles in emulsions was studied. The concentration of the emulsifier was set above the critical micelle concentration. We investigated the effect of the amount of seed polymer particles on the chemical kinetics and the average particle size and distribution. During monomer starving conditions the polymerization rate strongly depended on the monomer feed rate and not on the amount of seed particles. Throughout the entire monomer feed period the average particle size increased. This increase depended on the number and the size of seed particles. In emulsions with higher particle sizes higher equilibrium conversions were obtained. In our opinion, a greater extent of backbiting reactions is responsible for lower equilibrium conversions during and at the end of the process. The seeded semibatch process seems a reasonable choice for designing emulsion products with high monomer conversion and desired particle size. © 2012 Society of Chemical Industry

Neural Network Based Multi Stage Modelling of Chylla Haase Polymerization Reactor

Abstract An accurate semi batch process model should be a nonlinear dynamic model. Neural networks are suitable for modelling nonlinear dynamics and can be used for developing empirical models of semi batch processes. Multi stage neural network based modelling of the polymerization reactor described by Chylla and Haase, is illustrated in this paper. The process is divided into three regions namely heat up period, feed period and hold period and neural model is developed for each stage. This method of multi stage modelling captures the dynamics of the process accurately for the semi batch process. At different stages respective neural model is active based on the period of operation.

Multiway Gaussian Mixture Model Based Adaptive Kernel Partial Least Squares Regression Method for Soft Sensor Estimation and Reliable Quality Prediction of Nonlinear Multiphase Batch Processes

The predictive model based soft sensor technique has become increasingly important to provide reliable online measurements, facilitate advanced process control and optimization, and improve product quality in process industries. The conventional soft sensors are normally single-model based and thus may not be appropriate for processes with shifting operating phases or conditions and the underlying changing dynamics. In this study, a multiway Gaussian mixture model (MGMM) based adaptive kernel partial least-squares (AKPLS) method is proposed to handle online quality prediction of batch or semibatch processes with multiple operating phases. The three-dimensional measurement data are first preprocessed and unfolded into two-dimensional matrix. Then, the multiway Gaussian mixture model is estimated in order to identify and isolate different operating phases. Further, the process and quality measurements are separated into multiple segments corresponding to those identified phases, and the various localized kernel PLS models are built in the high-dimensional nonlinear feature space to characterize the shifting dynamics across different operating phases. Using Bayesian inference strategy, each process measurement sample of a new batch is classified into a particular phase with the maximal posterior probability, and thus, the local kernel PLS model representing the identical phase can be adaptively chosen for online quality variable prediction. The presented soft sensor modeling method is applied to a simulated multiphase penicillin fermentation process, and the computational results demonstrate that the proposed MGMM-AKPLS approach is superior to the conventional kernel PLS model in terms of prediction accuracy and model reliability.

Toward an inherently safer design and operation of batch and semi-batch processes: The N-oxidation of alkylpyridines

This work shows an application of inherent safety principles to a reaction widely used in the pharmaceutical industry. More specifically, it incorporates the teachings of Trevor Kletz into the design of an inherently safer process for the N-oxidation of alkylpyridines. This reaction is of interest because of the hazards resulting from the undesired, gas-generating decomposition of hydrogen peroxide, the oxidizing agent. The generation of oxygen, combined with the flammability of the alkylpyridines, represents a serious fire and explosion hazard for this process. The purpose of this paper is to demonstrate how an inherently safer process can be potentially achieved by designing improved reactors and by assessing conditions that reduce or eliminate the hazards. Furthermore, it is shown that such improvement in safety increases the efficiency of the process and results in a cost reduction.

Nonlinear and Non-Gaussian Dynamic Batch Process Monitoring Using a New Multiway Kernel Independent Component Analysis and Multidimensional Mutual Information Based Dissimilarity Approach

Batch or semibatch process monitoring is a challenging task because of various factors such as strong nonlinearity, inherent time-varying dynamics, batch-to-batch variations, and multiple operating phases. In this article, a novel nonlinear and non-Gaussian dissimilarity method based on multiway kernel independent component analysis (MKICA) and multidimensional mutual information (MMI) is developed and applied to batch process monitoring and abnormal event detection. MKICA models are first built on the normal benchmark and monitored batches to characterize the nonlinear and non-Gaussian variable relationship of batch processes. Then, the kernel independent component (IC) subspaces are extracted from the benchmark and monitored batches. Further, a multidimensional mutual information based dissimilarity index is defined to quantitatively evaluate the statistical dependence between the benchmark and monitored subspaces through the moving-window strategy. With the corresponding control limit estimated from th...

Method of removal of volatile organic compounds by using wet scrubber coupled with photo-Fenton reaction – Preventing emission of by-products

The photo-Fenton reaction was applied as a novel method for the removal of volatile organic compounds (VOCs) in the gas phase, and its effectiveness was experimentally examined. In conventional VOCs removal methods using a photocatalyst or ozone, VOCs are oxidized in the gas phase. Therefore, incompletely oxidized intermediates, which may have adverse effects on health, are likely to contaminate the treated air. On the other hand, in the VOCs removal method developed in this study, because the VOCs are oxidized in the liquid phase by the photo-Fenton reaction, any incompletely oxidized intermediates produced are confined to the liquid phase. As a result, the contamination of the treated air by these harmful intermediates can be prevented. Using a semi-batch process, it was found that the removal efficiency for toluene in a one-pass test (residence time of 17s) was 61%, for an inlet toluene gas concentration of 930ppbv, an initial iron ion concentration of 20mgL−1, and an initial hydrogen peroxide concentration of 630mgL−1. The removal efficiency was almost constant as long as H2O2 was present in the solution. Proton transfer reaction mass spectrometry analysis confirmed the absence of any incompletely oxidized intermediates in the treated air.

CFD Simulation on Drying and Dust Integration in Fluidized Bed Spray Granulation

Fluidized bed spray granulation is used to produce porous granular particles from suspensions, solutions, and melts. In this work, the drying of the spray and the drying of the particles in the fluidized bed are simulated using the Two Fluid Model (TFM) with the Eulerian-Eulerian approach. Using the wetted surfaces of the particle, the dust integration is implemented. The model is used to simulate the particle growth for a semi-batch fluidized bed spray granulation process.

Detailed Microstructure Investigation of Acrylate/Methacrylate Functional Copolymers by Kinetic Monte Carlo Simulation

AbstractA kinetic Monte Carlo simulation model is developed to study the microstructure of acrylic functional copolymers, taking into account all complexities of acrylic kinetics like backbiting, β‐scission, and propagation to macromonomer. The model is used to study the bulk and solution copolymerization of butyl acrylate/hydroxyethyl methacrylate in batch and semibatch processes. The model is able to reproduce experimental findings, providing new information that might be difficult to obtain (if possible) by deterministic or experimental methods. With the simulation the influence of the polymerization conditions on the branching density and copolymer composition as a function of chain length are discussed.magnified image

PENGARUH LAJU ALIR PELARUT DAN TINGGI TUMPUKAN BAHAN TERHADAP NILAI KOEFISIEN TRANSFER MASSA VOLUMETRIS (kca) PADA PROSES EKSTRAKSI SODA KI DARI ABU KLOTOK RANDU

&lt;p&gt;&lt;strong&gt;&lt;em&gt;Abstract :&lt;/em&gt;&lt;/strong&gt;&lt;strong&gt; &lt;/strong&gt;&lt;em&gt;Kapok (Ceiba pentandra) will generate cotton fiber, cotton seed, leather cotton, fruit shell and wood. Fruit shell contains 20%-25%w of potassium. Ash residue from burned shell contain 50.78% K&lt;sub&gt;2&lt;/sub&gt;CO&lt;sub&gt;3&lt;/sub&gt;, 26.27% Na&lt;sub&gt;2&lt;/sub&gt;CO&lt;sub&gt;3&lt;/sub&gt;, and 4.37% NaOH. Hence, it has the potential to be a source of carbonates.&lt;/em&gt; &lt;em&gt;Liquid product obtained from water extraction of ash is then named as Soda Ki, that can be used as an addition material in production of cake and noodle. The aim of this study was to generate an empirical equation connecting the value of the volumetric mass transfer coefficient (k&lt;sub&gt;c&lt;/sub&gt;a) with solvent (water) flow rate and bed height of ash. Extraction process was based on semi-batch process. For a certain time (5, 10, 15, 20, 30, 40, 50 and 60 minutes) samples were taken for analysis of carbonates concentration. Datas were then used to find the value of k&lt;sub&gt;c&lt;/sub&gt;a. The generated empirical equation is as follow: &lt;/em&gt;&lt;/p&gt;&lt;p align="center"&gt; &lt;/p&gt;&lt;p&gt;&lt;em&gt;This equation is valid for Reynolds number from 9,290 to 14,010 with 3.89% average errors. At high Reynolds number, the use of the equation will give less accurate result.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;strong&gt;&lt;em&gt;Keywords : &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;Ceiba pentandra&lt;strong&gt; &lt;/strong&gt;fruit shell ash, extraction,&lt;strong&gt; &lt;/strong&gt;Soda Ki, volumetric mass transfer coeff.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;

Characterization of Lecithin Isolated from Anchovy (Engraulis japonica) Residues Deoiled by Supercritical Carbon Dioxide and Organic Solvent Extraction

Lecithin was isolated and characterized from anchovy (Engraulis japonica) deoiled residues using supercritical carbon dioxide (SC-CO(2)) at a semibatch flow extraction process and an organic solvent (hexane) extraction. SC-CO(2) extraction was carried out to extract oil from anchovy at different temperatures (35 to 45 °C) and pressures (15 to 25 MPa). Extraction yield of oil was influenced by physical properties of SC-CO(2) with temperature and pressure changes. The major phospholipids of anchovy lecithin were quantitatively analyzed by high-performance liquid chromatography. Phosphatidylcholine (PC) (68%± 1.00%) and phosphatidylethanolamine (PE) (29%± 0.50%) were the main phospholipids. Thin layer chromatography was performed to purify the individual phospholipids. The fatty acid compositions of lecithin, PC, and PE were analyzed by gas chromatography. A significant amount of eicosapentaenoic acid and docosahexaenoic acid were present in both phospholipids of PC and PE. Emulsions of lecithin in water were prepared through the use of a homogenizer. Oxidative stability of anchovy lecithin was high in spite of its high concentration of long-chain polyunsaturated fatty acids. Lecithin can be totally metabolized by humans, so is well tolerated by humans and nontoxic when ingested. Lecithin from anchovy contain higher amounts of ω-3 fatty acids especially EPA and DHA, it may have positive outcome to use in food and pharmaceutical industries.

Moisture content distribution in semibatch drying processes. I. Constant particle drying rate

Semibatch drying processes include a period of feeding wet particles during drying. This results in different residence times of particles in the dryer and thus generation of a moisture content distribution. Describing these processes in a model that takes this moisture content distribution into account can be complicated. Knowledge of minimum or maximum values of the moisture content distribution is often desired for subsequent process steps or end product quality. This article presents a model that not only describes the overall average moisture content in time during semibatch drying put also gives the evolution of the moisture content distribution in time. A novel solution strategy based on the “method of moments” and “method of characteristics” is presented that solves the resulting ordinary differential equations in a piecewise manner. Simulations for a semibatch fluidized bed drying process give results that are feasible and realistic. © 2012 American Institute of Chemical Engineers AIChE J, 2012

Moisture content distribution in semibatch drying processes, part II. Falling particle drying rate

This article describes the evolution of the moisture content distribution in a population of wet particles during a semibatch drying process. The population balance model that is defined for this process includes falling particle drying rate, that is, the drying rate of a particle depends on its moisture content. This model is solved analytically using the “method of moments” and “method of characteristics.” Simulation experiments give realistic and meaningful results. Drying experiments still have to be performed to test the validity of the assumptions made in this model. © 2012 American Institute of Chemical Engineers AIChE J, 2012

Diene-based polymer nanoparticles: Preparation and direct catalytic latex hydrogenation

The diene-based polymer nanoparticles represented by poly(butadiene-co-acrylonitrile) were prepared in the semibatch emulsion polymerization system using Gemini surfactant (GS) trimethylene-1,3-bis(dodecyldimethylammonium bromide) as the emulsifier. The nanoparticles within the range of 17–54 nm were achieved with narrow molecular weight and particle size distributions. A spherical morphology was observed for the produced nanoparticles. The effects of GS concentration on the particle size, molecular weight, polymerization conversion and solid content, and composition of copolymer were investigated. The semibatch process using monomeric and conventional surfactant sodium dodecyl sulfate (SDS) was compared. At the second stage of this study, the prepared unsaturated nanoparticles were employed as the substrates for the latex hydrogenation in the presence of Wilkinson's catalyst, that is, RhCl(P(C6H5)3)3. The effects of the particle size and catalyst concentration on the latex hydrogenation rate were investigated. The particle size is found to have a significant effect on the reaction rate. When the 17-nm nanoparticles were used as the substrates, a high conversion of 95 mol % was obtained within 18 h using only 0.1 wt % RhCl(P(C6H5)3)3. The latex hydrogenation process was completely free of organic solvents. The present synthesis and following “green” hydrogenation process can be extended to latices made from semibatch emulsion containing other diene-based polymers. This study shows great promise for decreasing the demanded quantity of expensive catalyst and eliminating the organic solvent in the hydrogenation process. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012

Thermal hazard evaluation for iso-octanol nitration with mixed acid

2-Ethylhexyl nitrate (2-EHN), an important additive to diesel fuel, is produced from the nitration of iso-octanol with HNO3–H2SO4 mixed acid. In this study, the differential scanning calorimeter (DSC), accelerating rate calorimeter (ARC) and reaction calorimeter were used to analyze the thermal stability of 2-EHN and the thermal hazard of iso-octanol nitration. Four samples with different ratios of 2-EHN to mixed acid were tested using DSC. The results indicated that more mixed acid could catalyze the decomposition of 2-EHN. Three samples were tested using ARC and the results showed that sample 4 contained the lowest onset temperatures, TD8 and TD24. This shows that there is a higher probability of triggering the decomposition of the product 2-EHN from the iso-octanol nitration process. This conclusion was verified using RC1e tests at different temperatures. The RC1e experiments also indicated that the overall heat generation of these reactions was considerably large despite the high yields of the nitration process at 45 °C and 55 °C. This heat generation makes these semi-batch processes difficult to control, especially on a pilot or plant scale. Based on the maximum temperature of the synthesis reaction (MTSR) corrected by the yield, the only acceptable semi-batch process is the nitration reaction at 10 °C.

Design of an intensified coprecipitation reactor for the treatment of liquid radioactive wastes

In the nuclear industry, important volumes of liquid wastes have to be treated to reduce their contents in radioactive contaminants. The coprecipitation is the method mostly applied to perform decontamination of liquid wastes which cannot be concentrated by evaporation. Two operating modes are typically used for an industrial scale treatment by coprecipitation: the continuous and the semi-batch process. It was proved experimentally and theoretically that the semi-batch reactor ensures decontamination efficiency much higher than the continuous stirred tank reactor. An innovative reactor with an infinite recycling ratio is therefore designed to optimize the continuous treatment: the reactor/classifier reaches the same efficiency decontamination as the semi-batch process and represents an efficient device for the coprecipitation process intensification. Hereafter is presented this new coprecipitation reactor and its experimental application to a concrete case of nuclear decontamination. Modelling of this process is totally new: it validates experimental results and also presents theoretical equations to predict decontamination efficiency.

A Multiway Gaussian Mixture Model based Adaptive Kernel Partial Least Squares Regression Approach for Inferential Quality Predictions of Batch Processes

Soft sensor technique has become increasingly important to provide reliable on-line measurements, facilitate advanced process control and improve product quality in process industries. The conventional soft sensors are normally single-model based and thus may not be appropriate for processes with shifting operating conditions or phases. In this study, a multiway Gaussian mixture model (MGMM) based kernel partial least squares (PLS) method is proposed to handle multiple operating phases in batch or semibatch processes. The measurement data are first projected onto high-dimensional kernel feature space to account for the process nonlinearity. Then the multiway Gaussian mixture model is estimated with multiple Gaussian clusters in the kernel space. Thus various localized PLS models can be built within each Gaussian cluster to characterize the dynamics in the particular operating phase. Using Bayesian inference strategy, the soft sensor models for all the test samples are adaptively selected from the multiple localized kernel PLS models representing different phases and further used for online quality predictions. The presented soft sensor method is applied to the multiphase penicillin fermentation process and the computational results demonstrate that its performance is superior to the conventional multiway kernel PLS model.