Nurfanizan Mohd Afandi

Anaerobic Digestion (AD) is a renewable energy technology that converts organic wastes into a sustainable energy source, such as biogas. This paper presents the formulation of a Machine Learning (ML) forecasting model to predict emissions from the AD process. Five distinctive ML algorithms, including Artificial Neural Networks (ANN), Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and Genetic Algorithm (GA)-optimized have been developed to evaluate their predictive performance and formulated using key operational parameters as input variables. Model performance of each ML algorithm was evaluated using statistical analysis such as the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The results demonstrated that the RF model achieved the highest accuracy in predicting emissions, while the SVM model had the lowest. The RF model yielded the best prediction, with an R2 value of 0.9733, followed by GA-optimized, DT, ANN, and SVM (with R2 values of 0.9714, 0.9527, 0.9475, and 0.9389, respectively). The findings of this study emphasized the potential of ML forecasting models to support the development of efficient and sustainable biogas systems, with particular relevance to agricultural waste management in Malaysia.

Pre-treatment of lignocellulosic biomass is crucial for increasing biogas production via anaerobic digestion, as it breaks down complex organic compounds and reduces particle size, making feedstock more accessible to microorganisms. Conventional alkaline pre-treatments, such as sodium hydroxide (NaOH), are effective but pose environmental risks due to disposal difficulties and causticity. This study proposes using methylamine, an organic alkaline solution, as an environmentally friendly alternative to improve the pre-treatment sustainability. The study investigates the efficacy of methylamine as a pre-treatment for oil palm empty fruit bunches (OPEFBs) and compares its performance with conventional alkaline solution, NaOH, and magnesium hydroxide Mg(OH) ₂ . Experimental results, including morphological analysis of the OPEFB fiber structure and biogas composition analysis via Gas Chromatography, revealed that methylamine and NaOH substantially enhanced gas output compared to untreated samples. The pre-treatments effectively degraded the lignin and hemicellulose layers in the OPEFB, leaving cellulose. The 10% methylamine treatment was the only condition to produce detectable methane (2.25%) after 21 days, suggesting that methylamine may facilitate earlier methanogenesis compared to untreated, NaOH, and Mg(OH) ₂ treated samples. This is due to the efficient decomposition of organic compounds and increased microbial activity, which is assisted by the ability of the pre-treatment. The findings indicate that higher concentrations of alkaline pre-treatments improve biogas yields by optimizing the anaerobic digestion process. Methylamine has immense potential as an excellent pre-treatment solution, providing practical benefits for renewable energy generation and waste management due to its biodegradability and low environmental impact. These findings highlight the need to use the right alkaline solution and concentrations to maximise biogas production from OPEFBs.

Green hydrogen derived from renewable resources is increasingly recognized as a basis for future low-carbon energy systems. This study presents a comprehensive techno-environmental comparison of two thermochemical conversion pathways utilizing biomethane: steam methane reforming (SMR) and chemical looping reforming (CLR). Through integrated process simulations, compositional analyses, energy modeling, and cost evaluation, we examine the comparative advantages of each route in terms of hydrogen yield, carbon separation efficiency, process energy intensity, and economic performance. The results demonstrate that CLR achieves a significantly higher hydrogen concentration in the raw syngas stream (62.44%) than SMR (43.14%), with reduced levels of residual methane and carbon monoxide. The energy requirements for hydrogen production are lower in the CLR system, averaging 1.2 MJ/kg, compared to 3.2 MJ/kg for SMR. Furthermore, CLR offers a lower hydrogen production cost (USD 4.3/kg) compared to SMR (USD 6.4/kg), primarily due to improved thermal integration and the absence of solvent-based CO₂ capture. These insights highlight the potential of CLR as a next-generation reforming strategy for producing green hydrogen. To advance its technology readiness, it is proposed to develop a pilot-scale CLR facility to validate system performance under operational conditions and support the pathway to commercial implementation.

Hydrogen production is essential in the transition to sustainable energy. This study examines two hydrogen production routes, steam methane reforming (SMR) and chemical looping reforming (CLR), both using raw natural gas as feedstock. SMR, the most commonly used industrial process, involves reacting methane with steam to produce hydrogen, carbon monoxide, and carbon dioxide. In contrast, CLR uses a metal oxide as an oxygen carrier to facilitate hydrogen production without generating additional carbon dioxide. Simulations conducted using Aspen HYSYS analyzed each method’s performance and energy consumption. The results show that SMR achieved 99.98% hydrogen purity, whereas CLR produced 99.97% purity. An energy analysis revealed that CLR requires 31% less energy than SMR, likely due to the absence of low- and high-temperature water–gas shift units. Overall, the findings suggest that CLR offers substantial advantages over SMR, including lower energy consumption and the production of cleaner hydrogen, free from carbon dioxide generated during the water–gas shift process.

Hybrid turbine blade protection systems, which combine thermal barrier coatings (TBCs) and cooling mechanisms, are essential for safeguarding turbine blades in advanced gas turbine applications. However, conventional furnace evaluation methods are inadequate for accurately simulating the complex thermal conditions experienced by TBCs in these environments. Initial testing revealed substantial degradation of TBCs when subjected to high temperatures without the necessary cooling support. To address this limitation, the furnace setup was modified to incorporate a cooling air system. This system channeled 400 °C air to the back surface of the TBC while subjecting the front to 1400 °C furnace air, effectively replicating the thermal gradient encountered in hybrid protection systems. The modified furnace setup demonstrated a remarkable improvement in the performance of yttria-stabilized zirconia TBCs. By cooling the back surface of the TBC, the metal substrate temperature decreased, thereby improving the thermal gradient on the coating and its durability. The thermal gradient achieved by the modified furnace was verified to simulate accurately the conditions experienced by TBCs in advanced gas turbines. The conventional furnace setup, lacking a cooling mechanism, overestimated the heat transfer on the TBCs, leading to inaccurate results. The modified furnace, with its integrated cooling system, more accurately simulated the conditions experienced by TBCs in real-world advanced gas turbine applications and more reliably assessed their performance.

Cold spray has become a prominent deposition technology for coating, repair, and restoration in many industries, such as the aerospace, automotive, and power generation industries. It also has the potential to be used as an alternative overlay restoration for power plant components as it has minimal thermal distortion phase changes, as compared to conventional welding and thermal spray. This article aims to bridge the gap in the scientific literature by presenting a comprehensive review of cold spray in the context of power plant components. Firstly, this review examines the challenges of cold spray and subsequently elucidates effective mitigation strategies. Secondly, the review analyses the recent development of cold spray in the field of coating application. Moving forward, it investigates the integration of cold spray technology in repair applications, focusing on practical implementation and effectiveness. Finally, the review presents the overall impact of cold spray, its current outlook, and discusses future prospects. As such, the review will provide the community with a broad understanding of cold spray applications in the power plant sector.

Cold spray is a promising approach to repair all damages and defects in aluminum (Al) constituent elements. The study aims to investigate the mechanical and tribological properties of Al coatings deposited using high-pressure cold-spray (HPCS) and low-pressure cold-spray (LPCS) techniques. Al powder was sprayed on a cold-rolled plate of aluminum 1100, which was used as the substrate. The results showed that the micro-hardness of the LPCS Al coating reached up to 196.6 HV before the wear test compared to that of HPCS (174.3 HV). Moreover, more low friction coefficients obtained by LPCS (0.798) than HPCS (0.807) indicated good tribological properties with a high amount of oxide composition. Meanwhile, the wear studies reveal that the specific wear rate of the Al coating of LPCS (0.008) was lower than the HPCS (0.009) as the load increased from 3 N to 5 N, thus providing excellent wear resistance. Therefore, the results exhibited greater mechanical and tribological characteristics for Al coatings produced by the LPCS process than by the HPCS process.