Jo Sep 9, 2026
Water is indispensable for human life and economic development, and therefore, water treatment is one of the primary technical processes essential for people’s living and the overall sectors of the national economy.
Desalination by electrosorption is a novel water treatment technique, which is a combination of electrochemical method and adsorption method of separation. It is employed to purify water by removing salts and other substances dissolved in water by using the adsorption of ions and charged particles in water when an electric field is applied to an electrode made of conductive adsorbent material.
The core of electrosorption technology is the selection of electrode material and the design of electrode structure. Carbon adsorbent materials such as activated carbon, activated carbon fibers, graphene, carbon nanotubes and carbon aerogels are used as electrode material.
Kim Chang Sok, a researcher at the School of Science and Engineering, calculated the desalination rate by electrosorption of activated carbon electrodes from the electrical double layer phenomena at the liquid interface and the characteristics of activated carbon, and investigated the main factors i.e. voltage, interelectrode distance, water flow rate and treatment time, influencing the desalination of groundwater by electrosorption using electrodes. On this basis, he determined the optimum electrosorption conditions.
When the voltage was 2V, the interelectrode distance 15mm, the water flow rate 4m3/(kg·h) and the time 45min, the electrical conductivity and the hardness decreased by 43.8% and 33.5%, respectively.
The results confirmed that water treatment by electrosorption is an effective method with high desalination and softening efficiency, low power consumption and no environmental pollution.
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Jo Sep 8, 2026
Running accuracy and stiffness of spindle units in a machine tool have a crucial influence on the accuracy and reliability of the whole machine. Fatigue life calculation of bearings in spindle units is important to ensure the good performance of spindle units and to design machine tools scientifically.
In order to predict the fatigue life of rolling bearings used in machine tools, the stresses generated at the contact surface of interface are needed. This stress distribution is mainly determined by the pressure acting on the contact surface. Accurate calculation of pressure distribution can be done by FEM, which considers not only the generator shape but also the length in the contact state. The calculation of pressure distribution requires great computational efforts, which is more important in the case of repeating the calculation of many contacts in complex rolling pairs than in the case of simple contacts.
In the previous studies, several methods were used for the fatigue life of bearings, but they failed to analyze the effect of the roll profile and ring misalignment on the bearing fatigue life in a direct way.
Having developed a mathematical model for the fatigue life calculation of cylindrical roller bearings widely used in machine tool spindles, Kim Myong Il, a researcher at the Faculty of Mechanical Science and Technology, proposed a reasonable roller profile by calculating the fatigue life of bearings of three roller profiles and comparing them by FEM.
The results showed that the stress distribution is significantly lower for circular or logarithmic correction than for rectilinear roller generators, but the stress distribution is higher for circular correction, and the overall logarithmic correction significantly improves the fatigue life by 4.5 times.
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Jo Sep 7, 2026
High-grade copper-bearing ores have been increasingly depleted and instead, low-grade and complex ores have now become dominant in copper production. The existing production process for low-grade copper molybdenum ore has the disadvantage of high cost and high energy consumption. Therefore, a great deal of attention is being paid to the simple and environmentally-friendly bioleaching. Without proper heap bioleaching technology, millions of tonnes of low-grade copper ore might be left as waste.
While many studies have been carried out on the bioleaching of chalcopyrite, which is the main copper-bearing material, few studies have been reported on the direct bioleaching of complex minerals containing chalcopyrite.
Cha Kwang Chon, a post-graduate student at the Faculty of Mining Engineering, investigated the feasibility of bioleaching for copper recovery from low-grade, complex chalcopyrite in a column reactor.
The ore mainly contains pyrite and chalcopyrite as sulphide minerals and quartz as the main gangue minerals.
He carried out the tests in a column reactor using a mixture of inoculums used for bioleaching of pyrite.
The results showed that the dissolution of copper reached 85% after 120 days at 35-45℃.
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Jo Sep 4, 2026
The water electrolysis technology using proton exchange membranes (PEM) has now become more widespread in its use due to its simple operation and maintenance and high productivity per unit volume as an intensive and high-efficiency water electrolysis technology that can directly produce high-purity, high-pressure hydrogen without special ancillary devices. Despite these advantages over alkali water electrolysis technology, which is widely industrialized across the world now, its disadvantage is high cost. It is attributable to the high cost of proton exchange membranes and electrode catalysts for them.
Ho Kuk Chol, a post-graduate student at the Institute of Nano Science and Technology, prepared ATO-supported IrO2-RuO2 composite catalysts as anodic catalysts in PEMWE by using the Adams method and investigated their electrochemical and water electrolytic properties.
When the Ir content was 30% for the IrO2-RuO2 composite catalyst and 80% for the supported catalyst, the catalysts had current density of 77.5mA/cm2 at the voltage of 1.5V in 0.5mol/L H2SO4 solution. The stability experiments in the same solution showed that the supported composite catalyst had almost the same stability as IrO2. It was concluded that the prepared catalyst showed almost the same performance with 60% reduction in cost compared to IrO2 catalysts.
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Jo Aug 28, 2026
UN and many countries are calling for urgent measures because air pollution caused by air pollutants seriously threatens human health and causes premature death. Many investigations and studies have revealed that PM2.5 is a main pollutant that destroys the environment of ecosystems and harms human health, and that air pollutants containing PM 2.5 cause various diseases such as respiratory, lung and heart diseases.
In the air pollution concentration prediction task, it was reported that the artificial neural network (ANN) model improves prediction performance while avoiding the complexity and annoyance of modeling, compared to the deterministic method which has lack in representing the heterogeneity and nonlinearity of many factors related to pollutant formation.
Therefore, many researchers have begun to apply artificial neural networks extensively to air pollution prediction, and since then they have ensured the accurate prediction performance by combining deep neural networks with several other optimization techniques that have shown dramatic effectiveness in the prediction of large time series data. In a word, their research results show that deep learning models significantly improve their performance when combined with several other effective analytical methods on time series data rather than being used as a single model.
Based on this analysis, Pak Un Jin, a researcher at the Faculty of Automatics, proposed a hybrid model consisting of convolutional neural network (CNN)-long short-term (LSTM) with multifractal detrended fluctuation analysis (MF-DFA) for air pollution and meteorological time series data, and used it to predict the next day’s 24-h average PM2.5 concentration in Beijing City.
The comparison of the performance indexes of the proposed model with MLP and LSTM models showed that the proposed model provides higher prediction accuracy.
For further details, please refer to his paper “A deep learning approach via multifractal detrended fluctuation analysis for PM2.5 prediction” in “Journal of Atmospheric and Solar-Terrestrial Physics” (SCI).
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Jo Aug 27, 2026
The evacuated tube solar collector (ETSC) shows superior performance over the flat-plate collector (FPC) as it can reduce convective and radiation heat loss, and the thermal efficiency of ETSC has a linear relationship with the difference between the fluid inlet temperature and the ambient temperature divided by the solar radiation incident on the collector.
Under steady-state operating conditions, the useful output power of FPC is a function of many parameters, and one of them is the overall heat loss coefficient of FPC.
WGETSC (water-in-glass evacuated tube solar collector), unlike FPC, typically consists of 16-28 flooded solar tubes in direct connection to a horizontal water tank, so it is difficult to use the single overall heat loss coefficient as in FPC.
Having considered the solar tube and the water tank respectively in WGETSC, Jong Hyon Il, a section head at the Faculty of Thermal Engineering, derived a formula to determine the thermal performance of WGETSC and compared the calculated value with measured one.
The mean relative error between the measured and calculated values was 9.8%.
For more information, you can refer to his paper “On evaluating thermal performance of water-in-glass evacuated tube solar collector” in “International Journal of Research in Engineering”.
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