Editor-in-Chief
Takao Tsukada (Tohoku University)

Associate (Editor-in-Cheifs)
Manabu Shimada (Hiroshima University)
Masahiro Shishido (Yamagata University)

Editors
Ryuichi Egashira (Tokyo Institute of Technology)
Jun Fukai (Kyushu University)
Choji Fukuhara (Shizuoka University)
Toshitaka Funazukuri (Chuo University)
Takayuki Hirai (Osaka University)
Jun-ichi Horiuchi (Kitami Institute of Technology)
Eiji Iritani (Nagoya University)
Yoshinori Itaya (Gifu University)
Noriho Kamiya (Kyushu University)
In-Beum Lee (Pohang University of Science and Technology (POSTEC))
Kouji Maeda (University of Hyogo)
Hideyuki Matsumoto (Tokyo Institute of Technology)
Nobuyoshi Nakagawa (Gunma University)
Masaru Noda (Fukuoka University)
Hiroyasu Ogino (Osaka Prefecture University)
Mitsuhiro Ohta (The University of Tokushima)
Eika (W. Qian Tokyo University of Agriculture and Technology)
Yuji Sakai (Kogakuin University)
Noriaki Sano (Kyoto University)
Naomi Shibasaki-Kitakawa (Tohoku University)
Ken-Ichiro Sotowa (The University of Tokushima)
Hiroshi Suzuki (Kobe University)
Nobuhide Takahashi (Shinshu University)
Shigeki Takishima (Hiroshima University)
Yoshifumi Tsuge (Kyushu University)
Tomoya Tsuji (Nihon University)
Da-Ming Wang (National Taiwan University)
Takuji Yamamoto (University of Hyogo)
Yoshiyuki Yamashita (Tokyo University of Agriculture and Technology)
Miki Yoshimune (National Institute of Advanced Industrial Science and Technology (AIST))

Editorial office:
The Society of Chemical Engineers, Japan
Kyoritsu Building, 4-6-19, Kohinata, Bunkyo-ku
Tokyo 112-0006, Japan
journal@scej.org

AIMS AND SCOPE:

Journal of Chemical Engineering of Japan, an official publication of the Society of Chemical Engineers, Japan, is dedicated to providing timely original research results in the broad field of chemical engineering ranging from fundamental principles to practical applications. Subject areas of this journal are listed below. Research works presented in the journal are considered to have significant and lasting value in chemical engineering.

Physical Properties and Physical Chemistry
Transport Phenomena and Fluid Engineering
Particle Engineering
Separation Engineering
Thermal Engineering
Chemical Reaction Engineering
Process Systems Engineering and Safety
Biochemical Food and Medical Engineering
Micro and Nano Systems
Materials Engineering and Interfacial Phenomena
Energy
Environment
Engineering Education

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In systems biology, computer simulation of the biochemical networks of a microbial cell is a powerful method to predict their function and phenotype under different culture conditions and genetic modifications. Construction of a virtual microbe, a generic mathematical model of cell growth and metabolism, can be an ambitious but realistic project. It would enable the rational design of a biochemical network to enhance the production of useful metabolites and proteins. However, there exist critical problems, such as parameter uncertainty, mechanism complexity and high dimensionality of the model. We would like to review the dynamic models of the biochemical networks with their problems, providing insight into developing a virtual microbe.

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A simple method GC-W for estimating the Wilson parameters from pure-component properties alone has been adopted to predict the vapor–liquid equilibria of binary systems at reduced pressures. The various binary systems containing non-polar and polar molecules have been studied. The prediction performances obtained are examined and discussed in comparison with UNIFAC.

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The steam reforming of bio-ethanol has been carried out to compare with reagent ethanol using a palladium membrane at several reaction conditions (673 or 873 K, ΔP=0.10 MPa and steam-to-carbon ratio (S/C)=4–10). The raw material of these experiments was surplus bio-ethanol, which is one of the by-products in fermentation with sulfuring process in cornstarch production. As a result, the amount of total H₂ formation for bio-ethanol was comparable to that obtained with reagent ethanol under the same conditions. However, for bio-ethanol, the values of hydrogen permeate flow and hydrogen purity were smaller than that of reagent ethanol. In contrast, the amount of CO formed from bio-ethanol was greater than that from reagent ethanol. It is considered that carbon, which has a negative influence on the hydrogen-permeability of the palladium membrane, was produced from CO. The amount of CO was significantly decreased by lowering the temperature from 873 to 673 K. Moreover, CO was also decreased by increasing S/C and was not detected over S/C of 8. However, the amount of total hydrogen production and hydrogen permeate flow decreased by increasing the S/C ratio. Therefore, the best condition for hydrogen production from bio-ethanol using the palladium membrane reactor was at 673 K and S/C=8.

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The thermal stability of oxygen-containing functional groups on activated carbon surfaces in a thermal oxidative environment was studied. The raw activated carbon (AC0) was first treated with nitric acid, and the resulting nitric acid-treated activated carbon (ACn) was further oxidized under 2.5% O₂ (in N₂) atmosphere at different temperatures. The types and the amount of oxygen-containing functional groups were analyzed by thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Boehm titration, and X-ray photoelectron spectroscopy (XPS). Both oxygen- and nitrogen-containing functional groups were introduced onto the ACn surface. Under thermal oxidative conditions, hydroxyl was oxidized to the corresponding carboxyl group in the temperature range of 378–473 K, and epoxy groups and lactones were generated between 573 to 773 K via oxidation reactions between graphitized carbon and oxygen. In contrast, carboxyl decomposition occurred at around 573 K. Lactones, ketones, and quinones exhibited better thermal stability,  undergoing decomposition between 773 to 973 K. Ether and epoxy groups exhibited the best thermal stability, decomposing only at temperatures above 973 K.

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Synthesis of multi-walled carbon nanotubes (MWCNTs) was accomplished by catalytic chemical vapor deposition of ethylene over Co/Al₂O₃ in a fluidized-bed. The reaction temperature and ethylene concentration, as the molar percentage (mol%), were both found to be crucial factors determining the solid carbon conversion level and selectivity of MWCNT formation, but had no significant effect on the size distribution of the obtained MWCNTs. Amorphous carbon and carbon nanofibers (CNFs) were the main products obtained at a reaction temperature of 550°C. Amorphous carbon was also formed when using ethylene at a high concentration (62.5 mol%), which possibly deactivated the catalyst. Increasing the reaction temperature from 550 to 650°C resulted in better graphitized MWCNTs. The average diameters of the synthesized MWCNTs were in the range of 7–8 nm independent of the reaction temperature or ethylene concentration. The selectivity of alkane production decreased considerably at reaction temperatures above 675°C, resulting in a higher productivity of MWCNTs. The activation energy for MWCNT formation was found to be 65.3 kJ/mol, which matched well with that previously reported for carbon diffusion in liquid cobalt.

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When the fault detection or fault diagnosis problem is considered as a binary or multiple class classification problem, there are some challenges, i.e., highly dimensional input variables, high correlation among some input variables, overlap among the input variable spaces of different fault classes and invisible distribution of fault classes. To tackle the above problems, a novel chemical process monitoring and fault diagnosis approach, which integrates canonical variate analysis (CVA) with multiple self-organizing map (multi SOM), is proposed. CVA is employed to extract fault classification feature information as much as possible, to reduce dimension and to eliminate correlation via CVA features. Based on CVA features, multi SOM, whose structure is similar as a tree structure, is employed to distinguish all fault classes clearly. The output plane of the root SOM is obtained based on the CVA features of all fault classes. According to the root plane, each mixing region is distinguished and the output plane of one second layer SOM is further employed to partition fault classes within the mixing region. In this way, each mixing region in father plane is further partitioned by one his son plane until there is no mixing region on the output planes of all leaf SOMs. A case study on the Tennessee Eastman process benchmark shows the effectiveness and feasibility of the proposed fault diagnosis and process monitoring approach.

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In this study, a modified monotone kernel regression (MonKR) method is proposed that integrates monotonicity knowledge with kernel regression. In MonKR, monotonicity knowledge is described by the first order difference inequality constraints on the kernel expansion, which are added directly to the kernel regression formulation to obtain a convex optimization problem. MonKR is solved by quadratic programming. An analysis of the number of added constraints showed that MonKR is monotonic provided that a small finite set of constraints on some discrete points is added to the kernel regression (KR) formulation, and the step length value of MonKR is suggested. MonKR is simple to use and it readily obtains monotonicity. A function approximation problem was used to demonstrate the monotonicity of MonKR and its predictive performance was better than or equal to some state-of-art methods. Furthermore, MonKR was used to determine the true boiling point curve of crude oil. The results demonstrated that monotonicity was obtained by MonKR and that the overall predictive performance of MonKR was better than that of some previous methods.

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A novel method which integrates mutual information (MI) with weighted independent component analysis (MI-WICA) is proposed to highlight useful information for non-Gaussian process monitoring. Since the traditional independent component analysis (ICA) may not function well for non-Gaussian process monitoring, the MI-WICA uses MI technology to evaluate the importance of each independent component (IC) within a moving window, and then set different weighting values on the selected ICs to highlight the fault information for fault detection. The proposed method is applied to a simple multivariate process and the Tennessee Eastman benchmark process, and process simulation results demonstrate that the method is superior to those of the regular principal component analysis, ICA methods.

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A novel decoupling control method based on singular value decomposition (SVD) is proposed for multi-input-multi-output (MIMO) processes with time delays in this paper. A control scheme with Smith delay compensator is employed, where PI controllers are designed via internal model control (IMC) criteria. PI controllers are disposed with two unitary matrices derived from SVD, and then decoupling controllers are obtained. Noteworthy improvements of the proposed method include not only wide adaptability, i.e., square system and non-square system, but also its convenience of quantitatively regulating response performance. Moreover, the method overcomes the effect of model error caused by approximation and parameter perturbation. Two illustrative examples are provided to demonstrate the effectiveness of the proposed method, the improvement of dynamic quality and resistance to model error. The integral of squared error (ISE) performance criterion is applied to evaluate the design method.

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To develop a new industrial crystallization operation or crystallizer capable of realizing a higher crystal growth rate, a method of enhancing apparent crystal growth through the use of fine-crystal adhesion was examined using a classified bed-type crystallizer. We were able to clarify the effects of incorporating a pump for applying shear stress to a supersaturated mother solution along the path between the supersaturating section and the crystal growth section of the apparatus. A fine-generator pump was found to be effective at creating a discharge flow from the path, stimulating nucleation by impeller-based agitation, and recycling the solution back into the path. We found that the number of fine crystals could not be increased significantly with crystallization in a normal classified bed-type crystallizer that excludes the use of a fine-generator pump, whereas these parameters were controllable using the fine-generator pump. As an indicator of the output of the fine-generator pump, we defined the agitation rate m³/m³, which is expressed as the ratio of the flow rates between the fine-generator pump and the circulation pump. The fine-generator pump is effective at enhancing crystal growth rates at agitation rates of less than 1 m³/m³ and at an operational degree of saturation of less than 1.4 g/L. The most effective agitation rate was found to be 0.5 m³/m³, and it was independent of the degree of saturation. The maximum crystal growth rate was found to be 160 µm/h at a degree of saturation of 1.4 g/L, which was about three times greater than the maximum crystal growth rate without the use of the fine generator. These results are effective for the actual method of enhancing apparent crystal growth, although elucidation of the mechanism based on the phenomenological model is necessary.

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