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Electrochemical CO2 reduction (ECO2R) is considered as one of the economically viable means to convert CO2 into useful products, for achieving carbon neutrality in the future. Many studies have been conducted on developing and evaluating electrochemical cells that provide high energy efficiency and conversion of CO2 for CO production via ECO2R. However, commercially feasible technologies are yet to be developed and demonstrated due to various technical limitations as well as the lack of a systematic evaluation framework. In this study, CO production performance is examined by catholyte-free electrochemical CO2 reduction (CF-ECO2R), which eliminates a large ohmic drop by removing the catholyte compartment, thus lowering the energy requirement. The CF-ECO2R shows 0.6 V lower cell voltage and 17.4% higher electrical energy conversion efficiency than a typical GDE-catholyte method using 1 M KOH as the catholyte at a current density of 240 mA cm−2. The obtained results are used to demonstrate its technical feasibility and to provide basic data for the evaluation of a scale-up process. A mathematical model is developed based on the obtained experimental data and the model is simulated along with three different options of downstream separation to provide basic mass and energy balance data. Then, techno-economic and CO2 life cycle analyses are conducted to suggest the best configuration of the overall CO production system in terms of the economics and net CO2 reduction. It is estimated that the best configuration provides a reduction in CO2 emission by 48% compared to the conventional CO production via steam methane reforming. This configuration is also assessed to be economically feasible, giving a production cost (584 USD per ton CO) that is competitive with the current market price of CO. It is also demonstrated that the operating voltage of the CF-ECO2R and regional influences such as CO2 emission intensity and cost of the mixed electricity strongly affect the cost and CO2 emission of the system.

A new supervisory training rule for a shallow fully connected neural network (SFCNN) is proposed in this present study. The proposed training rule is developed based on local linearization and analytical optimal solutions for linearized SFCNN. The cause of nonlinearity in neural network training is analyzed, and it is removed by local linearization. The optimal solution for the linearized SFCNN, which minimizes the cost function for the training, is analytically derived. Additionally, the training efficiency and model accuracy of the trained SFCNN are improved by keeping estimates within a valid range of the linearization. The superiority of the proposed approach is demonstrated by applying the proposed training rule to the modeling of a typical nonlinear pH process, Boston housing prices dataset, and automobile mileage per gallon dataset. The proposed training rule shows the smallest modeling error and the smallest iteration number required for convergence compared with several previous approaches from the literature for the case study.

This work investigates the possibility of commercialization of a recently proposed nano calcium carbonate production process as an improved process. The analyzed process uses steel slag instead of limestone as the calcium source to produce nano calcium carbonate and comprises a calcium carbonation process and a NaCl electrolysis process. CO2 reduction impact and techno-economic feasibility of the system are analyzed to investigate its feasibility. The new process is expected to reduce the CO2 emission by about 8 %, compared to the conventional process of making the nano calcium carbonate. In addition, unit cost of production for the new process is 484 USD/ton indicating that it is economically feasible. Sensitivity and scenario analyses are performed with respect to the type of electricity sources and the capital cost of the electrolysis system, which are the key contributors to the overall cost.

Heterotrophic cultivation can be a preferred option for commercial microalgal biorefinery owing to its significantly higher productivity and lipid content leading to high value products. However, l...

Microalgal biomass is considered to be a promising renewable energy source to replace fossil fuel given its simple growth mechanism and high productivity per unit area. Nevertheless, microalgal bio...

Increasing the lipid production rate stands as one of the challenges for achieving economic feasibility of microalgal biorefinery. Various bioreactor operation strategies have been considered for culturing microalgae, including batch, continuous, fed-batch, semi-batch, and two-stage operations. However, since the previous studies used different experimental criteria, it is hard to draw a conclusion about their relative performances. Motivated by this, the present study compares lipid productivity performances and capital expenditures of the various operation strategies after their operating conditions are optimized. The optimal condition for each strategy is determined by performing a model-based optimization to maximize lipid productivity, which is a good indicator of the overall economics. The two-stage operation with continuous-batch serial connection (w/ stress condition) and the semi-batch operation (w/o stress condition) show outstanding performance compared to the other types of operation. Also, start-up, initial cell concentration, and chemical consumption, which are critical factors in large-scale cultivation, are analyzed.

This study presents the synthesis of FexSn1-x alloys (0 ≤ x ≤ 1)/reduced graphene oxide (RGO) using a dry plasma reduction method. The formation of bimetallic FeSn nanoparticles on the surface of RGO was confirmed through TEM and XRD measurements. In the results, FeSn ranging from 1 to 5 nm in size is shown to be successfully immobilized on the RGO surface. The developed materials are then applied as Pt-free counter electrodes (CEs) in liquid-junction photovoltaic devices. To get efficient CEs, we have carefully controlled the chemical composition of the FexSn1-x/RGO through changing the volume ratio of the Fe and Sn precursors during synthesis. The catalytic activity of the electrodes follows the sequence of Fe0.1Sn0.9/RGO > Fe0Sn1/RGO > Fe0.3Sn0.7/RGO > Fe0.5Sn0.5/RGO > Fe0.7Sn0.3/RGO > Fe0.9Sn0.1/RGO > Fe1Sn0/RGO, with the Zw values of the developed electrodes lower than those of Sn/RGO and Fe/RGO electrodes. Accordingly, the highest efficiency was 5.0% for the device using Fe0.1Sn0.9/RGO CE, which is also higher than those of devices using Sn/RGO (4.6%) and Fe/RGO (3.8%). The proposed strategy is simple and efficient and is, therefore, promising for the fabrication of cost-effective CE materials for next-generation solar cells and lithium-ion batteries.

Previous batch control methods, such as iterative learning control (ILC) or run-to-run (R2R) control, can significantly improve the control performance of the batch process. However, to guarantee the expected good control performance, a fairly accurate process model is required for these controllers. Also, the implementation is numerically complicated so that it is difficult to be applied to real manufacturing processes. To overcome these problems, a new batch proportional-integral-derivative (PID) control method is proposed, which borrows the concept of the conventional PID control method. Simulation studies confirm that the proposed method shows acceptable performance in tracking a setpoint trajectory, rejecting disturbances, and robustness to noises and variation of process dynamics. The application to the commercial batch process of a single crystal grower verifies that the proposed method can significantly contribute to improving the control performances of real batch processes.

Microalgae is a promising biomass source for renewable fuels and chemicals production. To describe microalgal behavior and improve their cultivation, various kinetic models have been proposed. However, previous works have focused on biomass formation and lipids production only, even though carbohydrates and proteins are also important products, not only for understanding the metabolic behavior of microalgae but also for enhancing the economic viability through value-added side products. In this study, a new mathematical model is proposed to explain core biological mechanisms of growth and macromolecules syntheses based on the central metabolism of carbon and nitrogen. In the model, microalgal growth is separated as hyperplasia and hypertrophy, to describe the cell growth more precisely under nutrient-replete and -deplete conditions. Sensitivity analysis performed using the model indicates that cell state (e.g., cell death rate) has a strong effect on the lipid production explaining the difficulty of reproducing a microalgae culture experiment.

In this paper, a new model reduction method and an explicit PID tuning rule for the purpose of PID auto-tuning on the basis of a fractional order plus time delay model are proposed. The model reduction method directly fits the fractional order plus time delay model to frequency response data by solving a simple single-variable optimization problem. In addition, the optimal tuning parameters of the PID controller are obtained by solving the Integral of the Time weighted Absolute Error (ITAE) minimization problem and then, the proposed PID tuning rule in the form of an explicit formula is developed by fitting the parameters of the formula to the obtained optimal tuning parameters. The proposed tuning method provides almost the same performance as the optimal tuning parameters. Simulation study confirms that the auto-tuning strategy based on the proposed model reduction method and the PID tuning rule can successfully incorporate various types of process dynamics.

A new simulation logic and thermodynamic equilibrium analysis algorithm combined with a new model simplification technique was developed to simulate the solvent extraction process for purifying rare earth metals from chloride solution with 2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester (PC88A) as a solvent. The proposed model simplification method significantly reduces the number of the nonlinear equilibrium equations to be simultaneously solved to overcome the initial guess problem and obtain numerically stable convergence pattern in solving the equi- librium analysis problem and performing the rigorous simulation of the extraction process. A new equilibrium analysis algorithm on the basis of the simplified nonlinear equilibrium equations is also proposed to estimate the equilibrium concentrations by solving the rigorous first principle extraction model. Finally, a solvent extraction simulator is de- veloped to estimate all the concentrations of all the stages of the solvent extraction process by solving the equilibrium analysis problem at each stage in a sequential way. The proposed simulator doe not suffer from the initial guess problem and shows very robust convergence pattern without any numerical problems.

A new frequency response identification method is presented to estimate frequency responses of discrete-time processes. It provides exact frequency response data sets for any desired frequency. This method incorporates various process signal types such as both initial and final steady state, initial steady state and final cyclic steady state and both initial and final cyclic steady state. Also, the proposed algorithm completely removes the effect of static disturbances and it shows acceptable robustness to measurement noises.

Cooked pork can be easily contaminated with Staphylococcus aureus during carriage and serving after cooking. This study was performed to develop growth prediction models of S. aureus to assure the safety of cooked pork. The Baranyi and Gompertz primary predictive models were compared. These growth models for S. aureus in cooked pork were developed at storage temperatures of 5, 15, and 25 C. The specific growth rate (SGR) and lag time (LT) values were calculated. The Baranyi model, which displayed a R of 0.98 and root mean square error (RMSE) of 0.27, was more compatible than the Gompertz model, which displayed 0.84 in both R and RMSE. The Baranyi model was used to develop a response surface secondary model to indicate changes of LT and SGR values according to storage temperature. The compatibility of the developed model was confirmed by calculating R , B , A , and RMSE values as statistic parameters. At 5, 15 and 25 C, R was 0.88, 0.99 and 0.99; RMSE was 0.11, 0.24 and 0.10; B was 1.12, 1.02 and 1.03; and A was 1.17, 1.03 and 1.03, respectively. The developed predictive growth model is suitable to predict the growth of S. aureus in cooked pork, and so has potential in the .microbial risk assessment as an input value or model.

This study was designed to estimate the shelf-life of the popular chilled foods kimbab (rice rolled in dried laver), samgak kimbab (triangular rice rolled in dried laver), eomook (fish surimi, boiled fish paste) mook (acorn-starch jelly), and tofu (soybean curd) in large discount markets and convenience stores. Different types of chilled foods were stored at 5, 7, and 10 for 7 and 28 days, and changes in the total numbers of the aerobic bacteria were monitored. Values of 6 and 7 log cfu/g were used as the standard. Ready-to-eat foods stored at 5 showed a much longer shelf-life compared to storage at 10. The respective percentage increases in the shelf-life observed at both 7 and 5 were kimbab (70%, 171%), samgak kimbab (87%, 143%), soybean curd (46%, 95%), fish surimi (46%, 99%), and mook (45%, 87%). To reduce the microbiological contamination, storages at 7 and 5 are recommended for the increases of 45-88 and 87-171% in the shelf-life of these chilled foods.

Microbial contamination levels and legal preservative appropriation in child foods sampled from the neighborhood of elementary schools were investigated. Contamination levels of total aerobic bacteria in seasoned dried fish slices, bread and snacks, sausages, sugar products and dumplings were , 4.50, , and CFU/g, respectively. Coliforms in four kinds of foods except for dumplings were , 2.00, and CFU/g, respectively. Yeasts and molds in those foods were , and CFU/g, respectively. S. aureus was isolated in of seasoned dried fish slices ( CFU/g), of bread and snacks ( CFU/g), of sausages ( CFU/g), of sugar products ( CFU/g), and of dumplings B. cereus was isolated in of seasoned dried fish slices , of bread and snacks , and of sugar products . Both E. coli and Salmonella spp. were not isolated in all samples. Preservative was only labeled on four products among 15 products but preservative on 13 products including 4 products haying an indication of preservative were not detected. Moreover, of sorbic acid was detected in one of Squid products . The results of this study indicated that the hygienic level of child foods in Gyeonggi and Incheon was very poor and need to be improved.

One of the factors contributing to foodborne illnesses is improper cleaning and sanitization of food contact surfaces. This study aimed to investigate the influence of various factors on Staphylococcus aureus attachment and biofilm formation on food contact materials and to determine sanitizing efficacy. The factors examined were contact materials (stainless steel, SUS; glass, GL; polypropylene, PP; and polyethylene, PE), surface conditions (smooth vs. scratched and with vs. without biofilms), and chemical sanitizers (70% ethanol and 200 ppm chlorine). Sanitization more efficiently lowered S. aureus counts on SUS and GL than on PP and PE. Sanitization efficacy of ethanol was better than that of chlorine. Surfaces with scratches and biofilms were the most resistant to sanitization methods. The use of low-adherent materials in food facilities, the selection of effective sanitizing methods, and the application of proper cleaning and disinfection procedures for food contact surfaces are essential for ensuring food safety. Practical applications Control of S. aureus on food contact surface is important to reduce cross-contamination in the foodservice industry. Hydrophobic and rough food contact surfaces promote S. aureus adherence and biofilm formation. Ethanol can be an effective chemical sanitizer against S. aureus biofilm, regardless of the material or roughness of the food contact surfaces. The use of hydrophilic materials, frequent replacement of equipment, and selection of proper sanitizing methods are recommended to prevent foodborne illnesses.