A stoichiometric methane–air premixed jet flame was established between parallel high-voltage and grounded electrodes while the oxygen content of the surrounding gas was systematically reduced from air to pure nitrogen. In pure nitrogen coflow, the particle pathlines became essentially unidirectional toward the grounded electrode, whereas oxygen addition progressively restored a second branch toward the high-voltage electrode. This oxygen-controlled transition provides direct evidence that surrounding oxygen is essential for the anode-directed ionic wind branch, while the observed behavior is consistent with electron–oxygen attachment followed by subsequent anion chemistry.
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.
