Issues: Kỹ thuật và Công nghệ cho Phát triển bền vững Vol 34.2 (04/2024)
1. Study on Structure and Reducibility of Iron Ore Sinter Containing Basic Oxygen Furnace Slag

Nguyen Cao Son*, Bui Anh Hoa, Tran Trung Duc

Basic Oxygen Furnace (BOF) slag is a byproduct in the steelmaking process. The amount of slag produced in steel production lines is substantial, not only in Vietnam but also worldwide. Reusing this large amount of slag is an essential requirement, and this study assesses a solution for reusing BOF slag by incorporating it into the sintering process. Experiments were conducted using iron ore, coal, and the slag as raw materials for the sintering process using a suction fan apparatus. The sintered product was analyzed for its microstructure, reduction degree, and softening property. The results indicate that the reducibility of the sinter containing the slag is equivalent to that without slag. The yield of sintered ore decreases by approximately 1 % compared to when thel slag from steelmaking is used as a flux. The results show that the yield of sintered product meeting standards (size and strength) has values ranging from 59.5 to 71.9 %. Besides, the highest reduction degree was achieved with a 24 % slag at a basicity of 1.6 and a temperature of 1100 °C. In contrast, the reduction degree of the sintered ore was lower at 1000 °C. The initial softening temperature was determined to be 1200 °C. The microstructure of the sintered ore revealed the formation of a liquid bonding phase. It can be concluded that the main bonding phase is calcium ferrite. The liquid phase showed an even distribution of calcium, silicon, oxygen, and iron elements.

Article Code:23071

# BOF slag, iron sinter, reducibility, microstructure

Page: 1-8

Field: Materials Science and Engineering
2. Nanomaterial SnS2-Based Sensor for VOC Gas Detection at Room Temperature

To Thi Nguyet, Dang Thanh Binh, Chu Manh Hung, Jian Zhen Ou, Nguyen Duc Hoa*

Real-time indoor hazardous gases monitoring has gained interest in ensuring human health. An effort to design gas sensing devices, which are compact in size, flexible, and low power consumption, providing high-performance sensing plays a crucial role in precise sensing of the indoor environment. Here, we have fabricated 2D SnS2 flakes for gas sensor. The 2D ultra-thin SnS2, including a few layers, shows fascinating sensing toward VOCs under room temperature with high response and fast reaction speed. The short-term stability versus time of the SnS2 sensor is investigated. Due to the great adsorption of gaseous molecules, the SnS2-gas sensor operates at room temperature without external heating sources. The Schottky junction-based sensor is one of the key factors, contributing to the higher performance of the sensor. Furthermore, its VOC-sensing mechanism is explained obviously through the energy band diagram. The SnS2-layer is considered a promising candidate in indoor VOCs monitoring and respiratory biomarker analysis in the future.

Article Code:24004

# SnS2 flakes, VOCs gas, room temperature, 2D materials

Page: 9-16

Field: Materials Science and Engineering
3. Synthesis of Cobalt Ferrite Nanocomposite Coated with Aluminum Oxide, Application in Protein Removal Process in Natural Rubber

Vu Thi Thuy, Le Thi Thu Trang, Dao Ngoc Thi, Nguyen Nhat Trang, Le Thi Hong Nhung, Nguyen Thai Huy, Phan Trung Nghia*

Proteins in latex are the main cause of unwanted effects for users, such as skin allergies and unpleasant odors. Therefore, it is necessary to remove protein from rubber latex before putting it into production. The study presents a method and process for synthesizing CoFe2O4 (CFO) magnetic nanoparticles coated on the surface with an Al2O3 coating. Then, based on the surface adsorption mechanism of the Al2O3 coating, the protein in the latex is adsorbed and recovered from the solution by the magnetism of the CFO magnetic core. The CFO material synthesized by the co-precipitation method has an evenly distributed spherical shape, size 27.3 nm, from a saturation of 53.9 emu/g. The synthesized CFO@Al2O3 has an evenly distributed spherical shape, size 56.2 nm, from a saturation of 39.07 emu/g, and a surface area of 216.75 m2/g. The CFO@Al2O3 nanoparticles have the ability to separate proteins up to 96.71% and have been researched and proven by the Kjeldahl method.

Article Code:23066

# Aluminum oxide, Cobalt ferrite, Nanocomposite, Natural rubber, Protein

Page: 17-23

Field: Chemical Engineering
4. Non-enzymatic glucose sensor based on Ni(OH)2/NF materials using different pulse voltammetry technique

Do Trinh Xuan Minh, Dinh Hieu Trung, Tran Vu Diem Ngoc, Chu Van Tuan, Nguyen Hai Ha, Le Tri Quang, Luc Nhu Quynh, Chu Thi Xuan*, Dang Thi Thanh Le, Nguyen Duc Hoa

Non-enzymatic glucose sensors have gained significant attention owing to their potential for accurate and cost-effective glucose detection. Nanomaterials play a pivotal role in enhancing performance of non-enzymatic glucose sensor. In this study, we introduce a novel non-enzymatic glucose sensor based on Ni(OH)2/NF (nickel hydroxide/nickel foam) materials using different pulse voltammetry technique. Chemical precipitation methods have been used to grow Ni(OH)2 nanostructures directly on a nickel foam electrode. The characterization of the synthesized materials was performed through field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDX), and X-ray diffraction (XRD). The performance of the Ni(OH)2/NF-based glucose sensor was evaluated through electrochemical measurements. Nanoscale hive-like structures of Ni(OH)2 with a diameter ranging from 450 to 530 μm and a thickness of 20 nm were formed on the NF surface. The sensor exhibited good performance, displaying a high sensitivity of 8.42 mA mM-1 cm-2 with a low detection limit of 0.84 μM. These results position the synthesized electrode as a promising contender for non-enzymatic electrochemical glucose sensors.

Article Code:23078

# Ni(OH)2 nanostructures, Ni foam, non-enzymatic glucose sensing, electrochemical sensor, direct growth.

Page: 24-30

Field: Materials Science and Engineering
5. An IoT-Based Smart Electronic Nose System for Non-Destructive Meat Freshness Monitoring

Thanh Huong Nguyen*, Minh Hoang Le

In recent years, food hygiene and safety violations have become a painful problem, especially in developing countries. It is essential to have tools or systems that can both monitor food quality and promptly warn users. Sensor technology as well as wireless communication technology pave the way to build a system that meets the above needs. In this paper, an electronic nose system based on the Internet of Things platform is proposed to monitor the freshness of food without changing the test sample. To evaluate the effectiveness of the proposed system, samples of three types of meat including pork, chicken and fish were collected and processed. In addition, the system also develops an application platform on smartphone devices to notify users about assessment results in real time. The system has been practically built and tested on product samples under many different testing conditions. The results show that the electronic nose system can effectively assess the freshness of meat through appropriate sensor parameters and provide timely warnings to the desired users.

Article Code:23072

# IoT system, electronic nose, meat freshness, non-destructive, food monitoring, food hygiene and safety

Page: 31-39

Field: Electrical Engineering
6. Rice Leaf Diseases Detection Using YOLOv8

Trinh Cong Dong, Mac Tuan Anh, Giap Van Khanh, Nguyen Thanh Huong, Bui Dang Thanh*

The development of rice plants holds immense importance today as it impacts crucial aspects of life such as food security, agricultural advancement, and the economy of nations. Consequently, research on disease detection in rice plants, particularly using machine learning, is gaining popularity. Several diseases pose a threat to rice leaves, with Blast leaf, leaf folder, and brown spot being the most common ones, directly affecting crop cultivation and causing yield loss. In this study, we propose the utilization of deep learning, the state-of-the-art image processing solution, to address this issue. Our proposed method consists of two steps: first, collecting reliable dataset by approaching and capturing direct images of rice leaf diseases in the fields, and second, designing and training an Artificial Intelligence (AI) model using the YOLOv8 algorithm to detect and classify the three aforementioned diseases. The data set used in this study includes 3175 images, divided into three parts, of which the training part is 2608 images, the validation part is 326 images and the test part is 241 images. Our experimental results demonstrate an accuracy up to 88.9% for the proposed model.

Article Code:23069

# Blast leaf, leaf folder, brown spot, YOLOv8, deep learning

Page: 40-47

Field: Electrical Engineering
7. Research and Manufacture of Hydraulic Butt Fusion Welding Machine for Different Plastic Material Pipes

Nguyen Tien Duong*

This paper introduces the research and manufacture of a hydraulic butt fusion welding machine that permits to weld dissimilar plastic pipes. In welding of dissimilar plastic pipes, the welding parameters at two pipe ends will be different. The butt fusion welding cycle of two dissimilar plastic pipes is established. The fabricated welding machine consists of the following basic components: machine body, two heating plates, four movable clamp rings, hydraulic movement mechanism to move the heater plate, hydraulic system to control the pressure and also to move the pipe ends during welding process. The pressed system has four movable cylinder tubes that move on four fixed pistons. At each side (left and right), a pair of two clamp rings is mounted on two movable cylinder tubes to provide forward and backward movement of a pipe during welding process. Two heater plates heat the two plastic pipe ends at different temperatures depending on the welding temperature of each plastic pipe material. The welding process is built in order to weld two dissimilar plastic pipes. The fabricated hydraulic butt fusion welding machine and the established welding process ensure accuracy and quality for the welding joint of dissimilar plastic pipes.

Article Code:23080

# Butt fusion, dissimilar plastic, pipe welding, plastic pipe, welding machine

Page: 48-57

Field: Mechanical Engineering
8. Numerical Study of Unsteady Flow Separation on Small Scale Wings Using Vortex Identification Methods

Viet Dung Duong*, Viet Anh Duong

The goal of this work is to develop vortex identification methods for better understanding the unsteady separation using particle-based direct numerical simulation for the unsteady incompressible flow past small wings. It is shown that in flows with Reynolds number 1000, the first vortex identification method, vorticity contour, is used to capture the vortical region behind the surface in which the package of unsteady votex bubbles is observed in different angle of attacks. The second vortex identification method, Q-criterion, has shown the advantages in order to capture the vortical region and track the near-wall separation by recording the vortex strengths of leading edge vortex and trailing edge vortex at high angle of attacks. The time history of the strengths has shown a good agreement to the time history of drag coefficient. The third vortex identification method, Lagrangian coherent structure, has shown its strength to record the most stretching, attracting, and shearing material surfaces that form the skeletons of Lagrangian particle dynamics in the far-field wake region. Accordingly, the tracking of particles in high shear surfaces, which is very important to determine the roadmap of unsteadiness, is well captured

Article Code:23065

# Unsteady Laminar Separation, Vortex Method, Vortex Identification, Lagrangian Coherent Structure

Page: 58-63

Field: Mechanical Engineering