Vietnam Academy of Science and Technology

Susilo S.H., Yudiyanto E., Rohman F., Wirawan W., Adiwidodo S., Nur Huda M.A., Pebrianti D., Bin Abas M.F.

The object of research is the axial flux BLDC (Brushless DC) motor, widely used in electric vehicles and industrial applications due to its compact design and high efficiency. One of the most problematic areas is optimizing the stator slot configuration and coil diameter to enhance efficiency and stability. Previous studies show that these parameters significantly affect magnetic field distribution, losses, and overall performance. However, a systematic investigation is still needed. Therefore, this study aims to identify optimal parameters to improve BLDC motor efficiency and stability. In the course of the study, an experimental setup with a BLDC motor, controller, power supply, and measurement tool were used. The motor was tested with different stator slots (12 and 24) and coil diameters (0.2 mm, 0.5 mm, 0.7 mm). Measurements included power, current, speed, and temperature. Data analysis assessed the impact on efficiency and stability, supported by numerical simulations for validation and optimization. Received results show that increasing stator slots from 12 to 24 improves magnetic field distribution and motor efficiency, with power output reaching 3060 W in the optimal configuration. This is due to the proposed stator slot variation, which reduces magnetic losses and enhances thermal efficiency. In particular, motors with 24 slots and a 0.5 mm coil diameter achieved the highest efficiency, while a 0.7 mm coil led to performance decline due to increased resistance. The findings highlight the need for an optimal balance between coil diameter and stator slot configuration for stable and efficient operation. This ensures the development of high-performance BLDC motors with improved efficiency and stability. Compared to similar configurations, it offers higher power output, lower magnetic losses, and better thermal regulation. These findings support the advancement of reliable, energy-efficient BLDC motors for electric vehicles and industry, with future research focusing on advanced materials and manufacturing techniques for further optimization.

The indiscriminate disposal of empty aluminum beverage cans poses a major environmental pollution problem. The last decade has witnessed coordinated research targeted at finding cost-effective and practical solutions to minimize and utilize solid waste, which has become a major global environmental concern. This research is focused on the use of readily available waste aluminum (Al) cans for the synthesis of gamma-alumina. This work aims to synthesize γ-alumina from scrap Al cans using the sol-gel method, as well as their characterization. This study further explores the impact of reaction temperature on alumina synthesis at a fixed aging time of a half day. Characterization of γ-alumina was performed via FTIR, XRD, BET, and SEM–EDX analyses. The experimental results revealed the possibility of γ-alumina synthesis from waste Al cans, which can serve as catalysts/supports for various processes. A reaction temperature of 70 °C was found to be optimal for alumina synthesis from Al waste, as evidenced by our FTIR and XRD results, whereas alumina at room temperature recorded the highest surface area, at around 139 m2/g. Also, the results show that all the alumina synthesized at 70 °C recorded the highest weight and atomic percentage, at 9%, 8%, 27%, and 22%.

Nasri M.S., Zulfiqar M., Samsudin M.F., Sufian S., Yub Harun N., Abdul Mudalip S.K.

The rapid growth of textile industry has negatively impacted the health and quality of clean water sources, leading to an increase in water pollution disaster. To address these significant water effluent issues, there is a strong need for improved and effective environmental remediation processes to treat effluents containing organic contaminants. The present research explores the photocatalytic and adsorption capabilities of MXene/g-C3N4 for the discoloration of methylene blue (MB) by introducing a strong oxidizing agent, such as hydrogen peroxide (H2O2). To the best of our knowledge, this study is the first one to demonstrate that the MXene/g-C3N4 photocatalyst could efficiently activate H2O2, reducing the MB concentration by up to 99.71% and 81.88% in 240 min via photocatalysis and adsorption processes, respectively. The addition of H2O2 oxidant in photocatalysis system rapidly reduced the recombination rate of photogenerated electrons-hole pairs by producing powerful hydroxyl and superoxide radicals in the Fenton-like oxidation process. Langmuir–Hinshelwood kinetic modeling excellently described the degradation of MB, showing the highest R2 value of up to 0.9896. The thermodynamic parameters, including Gibbs free energy (ΔG° = − 28.203 to − 30.095 kJ/mol), entropy (ΔS° = 94.558 kJ/mol K, enthalpy (ΔH° = 25.255 kJ/mol and activation energy (Ea = 11.066 kJ/mol), confirmed that the system is spontaneous and favorable for MB degradation. The reduction in ΔG° contributed to the expansion of photocatalyst’s pores, while the positive value ΔS° at higher temperatures indicated an increase in the kinetic energy of the degradation system, encouraging a higher rate of diffusion of methylene blue towards MXene/g-C3N4. In adsorption modeling, the adsorption of MB followed intraparticle diffusion kinetics and Temkin isotherms, with the highest R2 values of 0.9906 & 0.9965, respectively. A series of MXene/g-C3N4 heterostructure photocatalysts (1, 4, 8 and 12 wt. %) was synthesized via a wet impregnation method and characterized through TEM and FESEM characterizations. This work provides new insights into the application of MXene/g-C3N4 for the improvement of photocatalysis system by introducing a powerful oxidizer.

Abstract In recent years, significant strides in technological advancement have revolutionized our lifestyles, driving a surge in demand for multifunctional and intelligent materials. Among these materials, Shape Memory Alloy (SMA) stands out for its unique ability to memorize and revert to its original shape through phase transformation. Despite its remarkable properties, SMAs exhibit a minor limitation in accurately retaining their original shape or length. Furthermore, there is a notable dearth of information regarding the modelling of SMA behaviour with high precision. This study endeavors to address these challenges by integrating experimental data with neural network modelling to comprehensively examine SMA behaviour for mechanical applications. Leveraging an experimental dataset, this research employs feedforward backpropagation neural network (BPNN) modelling to forecast the strain recovery of SMA Nitinol alloy. The model aims to predict the recovery strain of SMA by utilizing three input parameters: temperature conditional, number of coils, and initial length. Remarkably, the achieved error rates of 0.29%, 0.80%, and 9.20% for various strain measurements significantly undercut the commonly accepted error threshold of 10% for nonlinear data predictions in SMA behaviour. The final results underscore the high prediction accuracy of the Artificial Neural Network (ANN), offering promising prospects for SMA applications involving temperature-strain interactions and enhancing engineering design.

This study develops and validates a force feedback control system for automotive pedals utilizing an optimized PID controller using the hybrid Spiral Sine-Cosine algorithm (SSCA). The primary objective is to enhance system performance by integrating SSCA-tuned PID control and comparing results from simulation and Hardware-in-the-Loop (HIL) testing. Auto Regressive with Exogenous inputs (NARX) models were used as the system identification method for nonlinear dynamic system to accurately represent actuator and pedal force relationships. Results demonstrated that the HIL setup significantly improved performance metrics compared to simulations: overshoot decreased, rise time improved, and settling time reduced for various force parameters. The study confirms that SSCA-tuned PID control can be effectively implemented in real-life applications, particularly in force control pedal vehicles, with potential benefits including reduced driver fatigue due to the repetitive actions of pressing and releasing the vehicle pedal. Future research will aim to enhance this approach by integrating vehicle speed control with advanced actuator and pedal force control systems. This integration will ensure smoother and more precise control over vehicle dynamics, improving overall responsiveness and efficiency. Moreover, a primary focus will be on optimizing low-speed driving scenarios, particularly in traffic congestion, where precise control is critical. By addressing challenges such as stop-and-go movement, vehicle jerks, and energy efficiency, this research seeks to enhance both driver comfort and safety in urban traffic conditions.

The efficiency of photovoltaic (PV) systems is often limited due to surface temperature increases, which result from absorbed solar energy being converted into heat. This rise in temperature reduces power output, system performance, and panel lifespan. To address these challenges, combined photovoltaic thermal (PVT) systems have emerged, enabling the simultaneous generation of electricity and thermal energy. This review provides a detailed analysis of the factors affecting PV panel efficiency, explores various feasible cooling techniques including innovative methods to mitigate excessive heating, and highlights opportunities for future research in this field. The article focuses on the experimental and theoretical advancements in PV cooling over the past decade, offering valuable insights and practical guidelines for researchers aiming to improve PV module cooling strategies. Additionally, an economic assessment of PVT systems is conducted, evaluating their financial feasibility in terms of payback periods and costs. The review also presents a comparative analysis of PVT techniques, addressing their benefits, challenges, and potential applications. This work aims to serve as a comprehensive resource for researchers exploring the viability and industrial applications of PVT systems, paving the way for more efficient and sustainable solar energy solutions.

ABSTRACTThis study examines the relationship between ESG sub‐indicators and the performance of Taiwan's semiconductor industry from 2016 to 2020. Using a combination of data envelopment analysis, truncated regression, and classification and regression trees, the research evaluates the influence of 12 ESG factors on innovation, sustainability, and market performance. The findings reveal that midstream manufacturers lead in innovation and market performance, while upstream manufacturers excel in sustainability. Corporate governance transparency emerges as the most critical factor driving overall performance, followed by employee management, product quality, and stakeholder treatment. Conversely, greenhouse gas emissions and waste management have limited impact due to high costs and regulatory challenges. The study highlights the need for firms to balance ESG strategies with performance goals, emphasizing energy management and governance as key levers for innovation and competitiveness. This research provides practical insights into optimizing ESG implementation to enhance performance across the semiconductor value chain.

Roney M., Issahaku A.R., Dubey A., Tufail A., Istiaque Hamim S.M., Wilhelm A., Aluwi M.F.

Diabetes mellitus (DM) is one of the most common long-term metabolic illnesses with detrimental implications on health and 90–95% of DM cases worldwide are caused by type 2 diabetes (T2DM). The side effects of the existing medicines include vomiting, diarrhea, and serious damage to the kidneys, blood vessels, and nerves. Therefore, finding anti-diabetic medications without side effects is crucial. The main goal of this work is to find anti-diabetic inhibitors using in-silico evaluation techniques such as molecular docking, molecular dynamic simulation, principal component analysis, and drug probability analysis. The DPP-IV is one of numerous molecular targets implicated in the pathogenesis of DM and Diffractaic acid (DF) was docked into the active site of this enzyme to assess the inhibitory effect of DF. In addition, MD simulation and PCA were used to assess the stability of docked complex. Furthermore, the DF was then subjected to drug probability investigations. The binding affinity of the DF was − 40.2476 kcal/mol, which was comparable to the reference compound (− 43.0908 kcal/mol). Furthermore, the compound was in a stable structure, as demonstrated by MD simulation and PCA analysis. Based on drug probability tests, DF also demonstrated druggable qualities. The results of this investigation suggest that DF may function as a possible inhibitor against DM; nevertheless, more in vitro and in vivo investigations are required to validate the activity and other properties.

AbstractMicroplastics (particles smaller than 5 mm) are among the most common pollutants in aquatic habitats because they may develop to high densities and can interact with both the abiotic and biotic environments. There is less information available on microplastics in the freshwater systems than there is in the marine environment. This study aims to shed light on the abundance and spatial distribution of microplastics in the Brahmaputra River (Mymensingh) through the utilization of the wet peroxide oxidation isolation technique, supplemented with sodium chloride, to examine fish and sediment specimens collected between December 21, 2022 and January 12, 2023. A total of 26 and 189 microplastic particles were identified in the fish and sediment samples, respectively. Microplastics (MPs) concentrations in fish gut ranged from 0.5 ± 0.7 to 1.67 ± 0.58 MPs individual−1. The most prevalent shape found in fish stomachs was fiber (46%), and the most common color was transparent (32%). Sizes 0.5–1 mm (1.6 ± 0.74) had the most microplastics. This study found that fishes from the demersal (3.25 ± 1.7) zone had more MPs than the benthopelagic (2.5 ± 0.58) and pelagic (1.5 ± 0.7) zones. Omnivorous fishes (54%) consumed more microplastics than carnivorous (31%, 2.6 ± 0.58) and herbivorous fishes (15%,1.33 ± 0.94). Microplastic consumption had a moderate correlation with fish body weight (r = 0.34), length (r = 0.46), and gastrointestinal content (r = 0.45). The MPs per kilogram of Brahmaputra River bed sediment ranged from 8 to 31, with a mean abundance of 18.9 ± 7.01 particles kg−1. The most common shape identified in this study was fragments (52%) and 33% of sediment microplastics were blue in color. Microplastics were most abundant in the 1–3 m‐meter size class. Fourier transform infrared spectroscopy (FTIR) showed that polypropylene (PP) was the most prevalent MP in both fish (34%) and sediment (40%) samples. In this study, the Pollution load index (PLI) for each sampling site is <10, with the highest value found for station 2(1.97 ± 0.49), regarded as risk category I. This study's results will be useful for future research on microplastics in freshwater environments.Practitioner Points Abundance and distribution of microplastics were determined from the longest river of Bangladesh. The structural properties of microplastics were characterized using ATR‐FTIR spectroscopy. Pollution load index (PLI) of microplastics was investigated.

Moshood T.D., Mahmud F., Nawanir G., Ahmad M.H., Mohamad F., AbdulGhani A.

Biodegradable materials are emerging as a sustainable alternative to conventional petroleum-based plastics across packaging, sanitation, and agriculture sectors. These materials naturally decompose into harmless substances within a specified period, completing an eco-friendly lifecycle. However, the widespread adoption of biodegradable plastics depends on building confidence among consumers, manufacturers, and regulators regarding their effectiveness. This study employed a mixed-methods approach to investigate the key factors influencing biodegradable plastics’ sustainability, integrating theoretical frameworks with survey data collected from Malaysian plastic users aged 15 and above. Results revealed that individual characteristics, particularly environmental self-identity, significantly influence behavioural intentions toward sustainable practices, such as choosing eco-friendly packaging. The findings contribute to the theoretical understanding of biodegradable plastics adoption in developing markets while providing actionable insights for government and corporate stakeholders. This study recommends targeted awareness campaigns emphasising environmental self-identity to reduce conventional packaging use and promote biodegradable alternatives. By incorporating these identity-focused messages into marketing communications, organisations can enhance public awareness and market perception of biodegradable products.