This study proposes a method to recover liquefied natural gas (LNG) cold energy from the fuel gas supply system (FGSS) of a two-stroke ME-GI dual-fuel (DF) marine engine to enhance energy utilization efficiency. LNG cold energy was employed to reduce the scavenging air temperature (SAT) through a CaCl2-based secondary refrigerant loop integrated into the engine cooling system. Thermodynamic analysis showed that approximately 12.3% of the required scavenging air cooling heat flux can be recovered at full load. Transient crank-angle-resolved CFD simulations, validated against experimental data (maximum deviation < 8%), were conducted to evaluate combustion and emission impacts under varying SAT conditions. Reducing SAT from 37 degrees C to 17 degrees C in DF mode increased indicated mean effective pressure (IMEP) by approximately 3.8%, reduced specific gas consumption by 3.7%, and significantly decreased NO emissions by up to 36.5% and soot emissions by 47.6%, while CO2 emissions decreased by 1.8%. Considering both performance enhancement and emission reduction, operating the engine in DF mode with SAT controlled at approximately 17 degrees C is recommended. The proposed system demonstrates a practical pathway for improving thermal efficiency and reducing greenhouse gas (GHG) emissions in LNG-fueled marine propulsion systems.
Strong acids can induce severe geochemical disruptions in soil by directly damaging microbial communities through toxicity, pH reduction, corrosion, and oxidative stress. With increasing awareness of acid contamination in soils, this study aimed to identify pollution sources such as HCl, HF, HNO3, and H2SO4 by analyzing 16S rRNA gene profiles of acidophilic microorganisms. Upon acid exposure, soil pH rapidly declined to between 1.8 and 2.0. Next-generation sequencing (NGS) and terminal restriction fragment length polymorphism (T-RFLP) analyses revealed a reduction in Proteobacteria and a corresponding increase in acidophilic Firmicutes. Clustering analysis showed distinct microbial community structures depending on the acid type. T-RFLP data provided clearer group separation than NGS. However, accurate identification of specific contaminants remained challenging. A machine learning model employing artificial neural networks achieved 94.4 percent accuracy in predicting acid types using species-level NGS data. When applied to T-RFLP data, the model reached 86.9 percent accuracy. This was similar to the predictive performance observed using genus-and family-level classifications from NGS. Augmenting the T-RFLP dataset further improved model accuracy. These findings demonstrate that integrating machine learning with molecular microbial profiling offers a promising approach for monitoring and identifying sources of acidic soil contamination.
In this study, kappa-Ga2O3 thin films were heteroepitaxially grown on GaN templates using metal-organic chemical vapor deposition (MOCVD), and the effects of growth conditions and nucleation layer structures on phase formation and crystalline quality were systematically investigated. Under direct growth conditions, increasing the growth temperature and H2O flow rate led to the incorporation of the beta-Ga2O3 phase. In particular, mixed kappa + beta phases were observed at elevated temperatures above 680 degrees C. To suppress beta-phase formation and maintain a single kappa phase, a two-step growth method was employed, and the influence of nucleation layer thickness and structure on the crystalline quality was comparatively analyzed. As a result, the 100 nm-thick kappa-Ga2O3 nucleation layer exhibited improved surface coalescence and a reduced threading dislocation density, effectively suppressing beta-phase formation even under high-temperature epitaxial conditions. Phi-scan analysis further confirmed the presence of three-fold rotational domains in the kappa-Ga2O3 films and revealed an in-plane epitaxial relationship of kappa-Ga2O3 (201) // GaN (11-20). Additionally, the maximum growth temperature at which a single-phase kappa-Ga2O3 could be maintained was identified to be 720 degrees C. These findings propose an effective approach for the stable growth of single-phase kappa-Ga2O3 thin films at elevated temperatures.
Anthropogenic carbon dioxide (CO2) emissions drive global climate change, motivating the development of bioprocesses that improve carbon utilization and enable CO2 recycling. In this study, we developed a CO2-fixing Saccharomyces cerevisiae chassis for single-cell protein (SCP) production using xylose derived from cellulosic biomass as a carbon source. A RuBisCO- based CO2-fixation pathway was previously integrated into a xylose-utilizing strain, enabling the routing of CO2 into central metabolism. Flux balance analysis combined with 13C-based intracellular metabolite analysis verified the assimilation of externally supplied CO2 into central metabolism, suggesting the potential for assimilation of fermentation-derived CO₂ and improved carbon utilization during SCP production. To enhance SCP production, the PAN2 gene encoding a component of the poly(A)-ribonuclease complex, previously associated with increased global protein production in S. cerevisiae, was truncated in the CO2-fixing strain. Under anaerobic conditions, the engineered strain exhibited a significant increase in cellular protein content, accompanied by an overall upward trend in amino acid levels relative to the parental strain. Collectively, these results metabolically verify RuBisCO-mediated CO2-fixation in yeast strain and demonstrate the feasibility of coupling CO2-fixation to SCP production. This work also provides insights into the potential of integrating CO₂-fixation with renewable carbon metabolism and establishing a proof-of-concept platform for the development of low-carbon yeast bioprocess.
This study numerically investigates the NO removal performance of a staged catalyst substrate employed in an industrial marine after-treatment system. The computational domain is based on the lab-scale experimental device used for measuring pressure drop, serving as a digital twin to accurately reproduce the staged catalyst configuration prior to its application in full-scale industrial reactors. Experiments were conducted to estimate the parameters for a porous model, employed for efficient computation of flow and reactive mass transfer inside the catalyst substrate without needing a complex computational mesh of the monolith structure. A reaction mechanism from the literature was modified and verified for marine SCR reactors. The three-dimensional numerical simulations in this study indicate that the NO removal in the staged catalyst substrate varies depending on the catalyst configuration, primarily due to differences in the upstream flow uniformity. This study demonstrates that relocating a single catalyst substrate to the downstream position improved conversion by 6.5 percentage points, while a two-stage catalyst configuration yielded a 15.5 percentage-point increase under identical exhaust conditions. In addition, the residence time exhibited significant variations depending on the catalyst arrangement and inlet velocity, highlighting it as a critical parameter governing NO reduction performance. The findings in the present study can serve as a reference for future analyses conducted under practical conditions in industrial-scale marine SCR systems.
