• Membrane Journal
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• v.25 no.5
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• pp.373-384
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• 2015

In the past few decades, polymeric membrane has played an important role in gas separation applications. For the separation of $CO_2$, one of greenhouse gases, high permselectivity, long-term stability and scale-up are needed. However, conventional polymeric membranes have shown a trade-off relation between permeability and selectivity while inorganic materials are highly permeable but expensive. Mixed matrix membranes (MMMs) combining the advantages of both polymeric and inorganic materials have become a possible breakthrough for the next-generation gas separation membranes. The MMMs could be either symmetric or asymmetric but the latter is more preferred to improve the permeance. Important factors influencing the MMM fabrication include homogeneous distribution of inorganic particles and good interfacial contact between inorganic filler and organic matrix. Recently, metal organic frameworks (MOFs) have received much attention as a new class of porous crystalline materials and a potential candidate for $CO_2$ separation. Zeolitic imidazolate frameworks (ZIFs), a sub-branch of MOFs, are the most widely used in MMMs due to small particle size and appropriate pore size for $CO_2$ separation. One of the major issues associated with the incorporation of porous particles in a polymeric membrane is to control the microstructure of the porous particle materials such as particle size, orientation, and boundary conditions etc. In this review, major challenges surrounding MMMs and the strategies to tackle these challenges are given in detail.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.421-428
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• 2022

This study analyzes emerging earthquake and space use technologies from the latest Korean and Japanese scientific and technological foresights in 2022 and 2019, respectively. Unlike the earthquake prediction and early warning technologies presented in the 2017 study, the emerging earthquake technologies in 2022 in Korea was described as an earthquake/complex disaster information technology and public data platform. Many detailed future technologies were presented in Japan's 2019 survey, which includes largescale earthquake prediction, induced earthquake, national liquefaction risk, wide-scale stress measurement; and monitoring by Internet of Things (IoT) or artificial intelligence (AI) observation & analysis. The latest emerging space use technology in Korea and Japan were presented in more detail as robotic mining technology for water/ice, Helium-3, and rare earth metals, and manned station technology that utilizes local resources on the moon and Mars. The technological realization year forecasting in 2019 was delayed by 4-10 years from the prediction in 2015, which could be greater due to the Corona 19 epidemic, the declaration of carbon neutrality in Korea and Japan in 2020 and the Russo-Ukrainian War in 2022. However, it is required to more active research on earthquake and space technologies linked to information technology.

• Membrane Journal
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• v.33 no.4
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• pp.149-157
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• 2023

Covalent organic frameworks (COFs) have shown promise in various applications, including molecular separation, dye separation, gas separation, filtration, and desalination. Integrating COFs into membranes enhances permeability, selectivity, and stability, improving separation processes. Combining COFs with single-walled carbon nanotubes (SWCNT) creates nanocomposite membranes with high permeability and stability, ideal for dye separation. Incorporating COFs into polyamide (PA) membranes improves permeability and selectivity through a synthetic interfacial strategy. Three-dimensional COF fillers in mixed-matrix membranes (MMMs) enhance CO₂/CH₄ separation, making them suitable for biogas upgrading. All-nanoporous composite (ANC) membranes, which combine COFs and metal-organic framework (MOF) membranes, overcome permeance-selectivity trade-offs, significantly improving gas permeance. Computational simulations using hypothetical COFs (hypoCOFs) demonstrate superior CO₂ selectivity and working capacity relevant for CO₂ separation and H₂ purification. COFs integrated into thin-film composite (TFC) and polysulfonamide (PSA) membranes enhance rejection performance for organic contaminants, salt contaminants, and heavy metal ions, improving separation capabilities. TpPa-SO₃H/PAN covalent organic framework membranes (COFMs) exhibited superior desalination performance compared to traditional polyamide membranes by utilizing charged groups to enable efficient desalination through electrostatic repulsion, suggesting their potential for ionic and molecular separations. These findings highlight COFs' potential in membrane technology for enhanced separation processes by improving permeability, selectivity, and stability. In this review, COF applied for the separation process is discussed.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.213-220
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• 2023

Mixed-matrix membranes (MMMs), which are composed of a polymer matrix filled with high-performance fillers as a dispersed phase, have been intensively studied for gas separations for the past 30 years. It has been demonstrated that MMMs exhibit superior gas separation performance compared to polymer membranes and are more scalable than polycrystalline membranes. Despite their potential, the commercialization of MMMs has yet to be reported due to several challenging issues. One of the major challenges of MMMs is the non-ideal interface between the continuous polymer phase and dispersed phase, which can result in defect formation (i.e., interfacial voids, etc.). With respect, many MMM studies have focused on addressing the issues through scientific approaches. The engineering approaches for facile and effective large-scale fabrication of MMMs, however, have been relatively underestimated. In this review paper, a novel strategy for fabricating MMMs in a facile and scalable manner using in situ metal-organic framework (MOF) formation is introduced. This new MMM fabrication methodology can effectively address the issues facing current MMMs, likely facilitating the commercialization of MMMs.

• Korea Trade Review
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• v.43 no.5
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• pp.47-66
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• 2018

This study analyzes the potential economic effects of a trade war between the U.S. and China. The CGE model is used to estimate the macroeconomic variables of each country and the change in imports/exports by industry by considering three different scenarios: (i) the US imposes a 25% of tariff on China; (ii) the US and China impose a 25% tariff bilaterally; (iii) the United States expands protection in vehicles and metals to Korea, Japan, and the EU. According to the results of the study, when the US and China initiate a trade war, GDP and welfare of both countries decline. China's decline in GDP and welfare are larger than those of the United States, which implies a trade war is more favorable to the U.S. than to China. In the long run, China's GDP and welfare decline widens further. While the trade volumes of the US and China are greatly reduced, the trade volumes of other countries does not significantly fluctuate. Finally, if the US extends protection policy to Korea, Japan and the EU, it creates undesirable effects on the US. In particular, damage to the US jeopardizes its advantageous position in a trade war with China. In order to emphasize the unfairness of protectionist policy and the damage to Korean industry, Korea needs to establish a strategy to counter US protectionist policy.

• Resources Recycling
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• v.33 no.3
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• pp.21-29
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• 2024

Globally, the demand for electric vehicles (EVs) is surging due to carbon-neutral strategies aimed at decarbonization. Consequently, the demand for lithium-ion batteries, which are essential components of EVs, is also rising, leading to an increase in the generation of spent batteries. This has prompted research into the recycling of spent batteries to recover valuable metals. In this study, we aimed to selectively leach and recover lithium from the cathode material of spent LFP batteries. To enhance the reaction surface area and reactivity, the binder in the cathode material powder was removed, and the material was subjected to heat treatment in both atmospheric and nitrogen environments across various temperature ranges. This was followed by a mechanochemical process for aqueous leaching. Initially, after heat treatment, the powder was converted into a soluble lithium compound using sodium persulfate (Na₂S₂O₈) in a mechanochemical reaction. Subsequently, aqueous leaching was performed using distilled water. This study confirmed the changes in the characteristics of the cathode material powder due to heat treatment. The final heat treatment in a nitrogen atmosphere resulted in a lithium leaching efficiency of approximately 100% across all temperature ranges.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.152-168
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• 2019

The element arsenic, which is abundant in the Earth's crust, is used for various industrial purposes including materials for disease treatment and household goods. Various human activities, such as the disposal of soil waste, metal mining and smelting, and combustion of fossil fuels, have caused the pollution of the environment with arsenic. Recently, guidelines for arsenic in rice have been adopted by the Korean ministry of food and drug safety to prevent health risks based on rice consumption. Because of the exposure to arsenic and its accumulation in the human body through various channels, such as air inhalation, skin contact, ingestion of drinking water, and food consumption, integrated multimedia risk assessment is required to adopt appropriate risk management policies. Therefore, integrated human health risk assessment was carried out in this study using integrated exposure assessment based on multimedia (e.g., air, water, and soil) and multi-route (e.g., oral, inhalation, and dermal) scenarios. The results show that oral uptake via drinking water is the most common pathway of arsenic into the human body, accounting for 57%-96% of the total arsenic exposure. Among various age groups, the highest exposures to arsenic were observed in infants because the body weight of infants is low and the surface areas of infant bodies are large. Based on the results of the exposure assessment, the cancer and non-cancer risks were calculated. The cancer risk for CTE and RME is in the range of 2.3E-05 to 6.7E-05 and thus is negligible because it does not exceed the cancer probability of 1.0E-04 for all age groups. On the other hand, the cancer risk for RME varies from 6.4E-05 to 1.8E-04 and from 1.3E-04 to 1.8E-04 for infants and preschool children, exceeding the excess cancer risk of 1.0E-04. The non-cancer risks range from 5.4E-02 to 1.9E-01 and from 1.5E-01 to 6.8E-01, respectively. They do not exceed the hazard index 1 for all scenarios and all ages.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.847-870
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• 2023

The safe disposal of high-level radioactive waste requires accurate predictions of the long-term geochemical behavior of radionuclides. To achieve this, the present study was conducted to model geochemical behaviors of uranium (U), plutonium (Pu), and palladium (Pd) under different hydrogeochemical conditions that represent deep groundwater in Korea. Geochemical modeling was performed for five types of South Korean deep groundwater environment: high-TDS saline groundwater (G1), low-pH CO₂-rich groundwater (G2), high-pH alkaline groundwater (G3), sulfate-rich groundwater (G4), and dilute (fresh) groundwater (G5). Under the pH and Eh (redox potential) ranges of 3 to 12 and ±0.2 V, respectively, the solubility and speciation of U, Pu, and Pd in deep groundwater were predicted. The result reveals that U(IV) exhibits high solubility within the neutral to alkaline pH range, even in reducing environment with Eh down to -0.2 V. Such high solubility of U is primarily attributed to the formation of Ca-U-CO₃ complexes, which is important in both G2 located along fault zones and G3 occurring in granitic bedrocks. On the other hand, the solubility of Pu is found to be highly dependent on pH, with the lowest solubility in neutral to alkaline conditions. The predominant species are Pu(IV) and Pu(III) and their removal is predicted to occur by sorption. Considering the migration by colloids, however, the role of colloid formation and migration are expected to promote the Pu mobility, especially in deep groundwater of G3 and G5 which have low ionic strengths. Palladium (Pd) exhibits the low solubility due to the precipitation as sulfides in reducing conditions. In oxidizing condition, anionic complexes such as Pd(OH)₃^-, PdCl₃(OH)₂^-, PdCl₄^2-, and Pd(CO₃)₂^2- would be removed by sorption onto metal (hydro)oxides. This study will improve the understanding of the fate and transport of radionuclides in deep groundwater conditions of South Korea and therefore contributes to develop strategies for safe high-level radioactive waste disposal.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.605-622
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• 2007

Elemental, Rock-Eval pyrolysis and isotopic analysis of the core sediments from the northwestern and eastern Ulleung Basin of the East were carried out to identify their geochemical characteristics, spatial and vertical variation and origin of organic matter in Upper Quaternary sediments from the northwestern and eastern Ulleung Basin of the East Sea. TOC, m and TS did not show spatial variation between the sampling locations whereas they showed systematic vertical variation associated with MIS stages related to the sea-level change of the East Sea. It is suggested that these past changes of sea-level influenced the sedimentary depositional environments and/or diagenesis which resulted the patterns observed in this study. Based on the results of TOC/N, TS/TOC, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ analysis, organic matters in the study area appears to be predominantly originated from the marine algae rather than land plant and deposited under normal marine oxic condition during MIS I and MIS III period, and under euxinic/anoxic condition during MIS II period. TOC/N, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ have a relatively constant value irrespective of MIS stages, implying that the organic matter source does not change by the sea-level fluctuations. However, the results of Rock-Eval pyrolysis indicates that the organic matter is in immature stage and originated from land-plant (Type III), locating in the immature stage land plant (Type III). Similar differences were reported from other areas such as the Atlantic Ocean, Iberia Abyssal Plain, Mediterranean Sea, suggesting that Rock-Eval method does not exactly reflect the characteristic of immature organic matters. Accordingly, the application of Rock-Eval pyrolysis for delineating the source of immature organic matters should be approached with caution and all other geochemical proxies should be considered altogether at the same time.