Influence of Interposed Graphene Sheets on Mechanic...

Jo Jun 27, 2025

Graphene has extraordinary mechanical strength and excellent thermal and electrical conductivity. With these merits, graphene has been an ideal reinforcement for high-performance metal matrix composites, attracting a great deal of attention.

In particular, graphene-reinforced Al matrix composites (AMCs) are superior to Cu-based composites and other various Al alloys due to their advantages such as high strength, high conductivity, light weight and low cost. In accordance with the desired terms, the optimal properties of graphene-reinforced AMCs are obtained by manipulating the content and dispersion of graphene layers. However, it still remains difficult to determine the optimal content and realize the uniform dispersion of graphene in the Al metal matrix.

Jon Sin Hyok, a researcher at the Faculty of Materials Science and Technology, in cooperation with some other researchers, has conducted a first-principles study of the interface binding nature, mechanical strength, and electronic properties of aluminum/graphene (Al/G) composites, using superlattice models with varying graphene content.

Their calculations have revealed the weak binding between Al and graphene layers with no new chemical bonding at the interface and the gradual decrease in binding strength with increasing graphene content.

You can find the details in his paper “Influence of interposed graphene sheets on mechanical and electronic properties of Al/graphene superlattice” in “Applied Physics Letters” (SCI).

Magnetic Nanocomposite-modified Graphite-epoxy Comp...

Jo Jun 26, 2025

Accurate determination of blood glucose concentration has a great significance in the prevention and treatment of diabetes as well as in the food processing and fermentation.

Glucose oxidase (GOx) modified electrodes play an important role in blood glucose detection by electrochemical methods. Enzyme-based sensors have disadvantages such as low enzyme stability and complicated immobilization.

To eliminate these disadvantages, non-enzymatic sensors with metal and metal oxide nanoparticles have been used. However, these sensors have some disadvantages such as poor sensitivity and selectivity and low catalytic activity. Some researchers eliminated these disadvantages by decorating the metal / metal oxide nanostructures on active carbon supports including carbon nanotubes (CNTs), graphene, etc.

Fe₃O₄ MNPs with good magnetic property are widely used for electrochemical biosensors and, in particular, they are also used for glucose detection as a direct non-enzymatic biosensor with no glucose oxidase.

Pak Wi Song, a section head at the Faculty of Chemical Engineering, has prepared an electrochemical sensing platform for glucose sensing by magnetic loading of Fe₃O₄/GO nanocomposites on graphite-epoxy composite electrode (GECE).

He characterized the Fe₃O₄/GO/GECE modified electrode by scanning electron microscopy (SEM), X-ray diffraction analysis (XRD) and cyclic voltammetry (CV).

The fabricated biosensor exhibited excellent electrocatalytic activity. The linear range for glucose is from 0.5 to 6.5mM with the detection limit of 268.5μM (S/N =3) and the sensitivity of 63.5mA/mM.

For more information, please refer to his paper “Magnetic Fe₃O₄/GO nanocomposite-modified graphite-epoxy composite electrode for high-performance glucose sensing” in “International Journal of Electrochemical Science” (SCI).

Estimation of Thermoelectric Performance Parameters...

Jo Jun 24, 2025

Thermoelectric phenomenon is a physical process in which electric current flows by heat diffusion when there exists a temperature gradient in thermoelectric materials such as conductors or semiconductors. Therefore, it is very important to enhance the thermoelectric performance of corresponding material in thermoelectric applications. The performance of thermoelectric material describes how much thermal energy can be directly converted into electrical energy.

Thus, semiconductors whose electrical conductivity and Seebeck coefficient are between conductors and insulators were used in thermoelectric applications. In general, as electrical conductivity and thermal conductivity are proportional to the concentration of carriers such as electrons and phonons, the better the electrical conductivity of material is, the better its thermal conductivity is. However, it is difficult to obtain materials with both high electrical conductivity and low thermal conductivity. Fortunately, the idea that thermal conductivity can be reduced by high entropy design has attracted a great deal of interest of researchers who were making efforts to develop high entropy materials (HEMs) with good thermoelectric property.

Pang Chol Ho, a researcher at the Faculty of Materials Science and Technology, has newly developed an improved residual error non-homogeneous grey model and estimated the thermoelectric performance parameters of high entropy materials (HEMs) using this model.

Firstly, by combining the non-homogeneous grey model, residual error processing method and Markov model, he improved the forecasting accuracy of the model.

Secondly, he performed a comparative analysis of several HEMs using the proposed IRENHGM (1, 1) model and other grey models. The results showed that the Mean Absolute Percentage Error (MAPE) value of the proposed model is less than 0.02, which is the highest in the forecasting accuracy.

For more details, you can refer to his paper “Estimating the Thermoelectric Performance Parameters of High Entropy Materials by the Improved Residual Error Non-homogeneous Grey Model(1, 1)” in “The Journal of Grey System” (SCI).