Isomer-specific speciation behaviors probed from premixed flames fueled by acetone and propanal
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Laser based directed energy deposition (DED) is a competitive method for repairing and remanufacturing metallic parts used in numerous industries including aerospace and biomedical. However, the numerous dynamic phenomena associated with the DED process often result in defects such as entrapped-gas pores, lack of fusion, and undesirable anisotropic properties. The entrapped-gas pore, being one of the most common issues, not only influences melt-pool dynamics but also reduces the fabrication quality and mechanical properties of parts fabricated by the DED process. To reduce and further understand this issue, the real-time observation of the pore formation process needs to be studied first. To directly observe the phenomena in the melt pool, high-speed techniques are needed because rapid solidification leads to rapid pore formation and movement. In-situ high-speed X-ray has been proven to be an effective method in investigating the melt pool dynamics and pore formation mechanisms in the laser powder bed fusion process, in which the fabrication process is quite different from that in DED. Here, the high-speed X-ray method is extended to study the formation of entrapped-gas pores. The real-time formation and quantitative analysis of pores under each set of processing parameters (particle velocity, laser power, and spot welding dwelling time of stationary laser) in the DED process are investigated. We found that the DED with a higher particle velocity (3.19 m/s) produced a smaller average pore size of 27.8 µm and a lower pore area fraction of 0.52%. The DED under lower laser power (156 W) generated a smaller average pore size of 20.3 µm and a lower pore area fraction of 1.94%. The shorter dwelling time (10 ms) benefited the decrease of both average pore size and pore area fraction.
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Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.
Solar radiation modification (SRM) is a possible deliberate approach to decrease or reflect incoming solar radiation with the goal of reducing global temperatures, which have increased over the last decades due to high atmospheric greenhouse gas concentrations. Stratospheric aerosol injection, specifically, has shown potential for successfully reducing global temperatures in climate model simulations. Despite the growing literature in the areas of climate change and SRM, their combined effects on renewable energy generation, a climate change mitigation strategy, have not been addressed. In this review paper, we synthesize previous literature on the possible effects of climate change and SRM on renewable energy resources (i.e., wind energy, solar energy, biomass energy, and hydropower), review the status of climate change and SRM research, and explore potential effects of SRM on renewable energy primarily in the Continental United States (CONUS), but with global perspectives as well. We discuss the research challenges and impacts of SRM on renewable energy and conclude by discussing the potential implications of SRM for renewables for SRM governance and policy. This work is not advocating for or against SRM. It is highlighting an important potential impact for future decision makers.
In this work, a Chlorella sp.-Cupriavidus necator (C. necator) microcosm was artificially established for phenol degradation. Additionally, the cooperation relationship between Chlorella sp. and C. necator was initially demonstrated, and then the effects of Chlorella sp./C. necator inoculation ratio, light intensity, temperature and pH on the performance of this microcosm were systematically evaluated and optimized. The optimal conditions for phenol degradation were as follows: a Chlorella sp./C. necator inoculation ratio of 1:1, a light intensity of 110 μmol m -2 s -1 , a temperature in the range of 25-32 °C and a pH in the range of 5.5-7.5. Under optimal conditions, this microcosm could degrade phenol with a maximum concentration of 1200 mg L -1 within 60 h. It was found that only when the phenol concentration was reduced to the tolerance concentration of microalgae, that is, the last stage of phenol degradation, the cooperation effect could be generated, indicating that the tolerance of microalgae to phenol may be more important than its degradation performance. Comparative transcriptomic analysis was conducted to discuss the cooperation mechanism of this microcosm subject to high phenol concentrations. The up-regulation of genes involved in photosynthesis and carbon fixation of Chlorella sp. demonstrated the CO 2 and O 2 exchange between Chlorella sp. and C. necator and their cooperation relationship. This study suggests that this microcosm has great potential for the bioremediation of phenol contaminants.
Metastable orientation relationships (ORs) between Cu and Cr were kinetically stabilized via epitaxial thin film deposition on MgO(001). Both Cu(001) and Cr(001) grow epitaxially on MgO(001). The Bain OR was observed by x-ray diffraction and scanning transmission electron microscopy for Cr(001) / Cu(001) / MgO(001). In contrast, three Cr/Cu ORs were found for Cr deposition on Cu(001) / MgO(001): the Pitsch OR, and two previously unreported ORs related to the Bain and Pitsch ORs, respectively. Ab initio calculations predict the energetics of these ORs, and reveal that the deformation resistance of Cr leads to the three observed ORs on Cu(001).
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Lignin decomposition is critically linked to terrestrial carbon (C) cycle due to the enormous C mass of lignin and its importance in controlling overall rates of litter decomposition. Interactions between lignin and iron (Fe) minerals have been increasingly recognized as key mediators of lignin decomposition in experimental studies. However, we still lack a quantitative understanding of how Fe minerals interact with microbes to control lignin decomposition. Here, we leveraged experimental results from an incubation of Fe-rich soil, in which lignin decomposition rates were measured at aerobic conditions after four levels of pre-treated O2 availability, to examine microbe-Fe (MiFe) interactions in lignin decomposition with a MiFe model. We quantified how Fe redox cycling interacted with microbial activities to control lignin decomposition via data-model integration. Our results showed that the MiFe model with time-dependent growth and mortality functions better represented CO2 release from lignin decomposition (R2 ranging from 0.96 to 0.97) than models assuming either first-order or Michaelis-Menten kinetics. Reduction of Fe(III) to Fe(II) after pre-treatments with lower O2 availability stimu-lated the Fenton reaction to break down macro-molecular lignin into small molecules available to microbes. The small molecules of lignin and necromass bounded with oxidized Fe and were protected from decomposition. After 1-year incubation, the model implied that most of C stabilized with Fe minerals was derived from small molecular lignin C. Our quantitative analysis of microbe-Fe interactions sheds new light on lignin decomposition and preservation and helps improve model prediction of soil C persistence under global change.
Machine learning (ML) models have been applied to forecast solar energy; however, they often lack clarity of interpretability and underlying physics. This work addresses such challenges by developing a hierarchy of ML models that gradually introduce predictors to improve the forecast accuracy based on a physics-based framework. Three ML models (ARIMA, LSTM, and XGBoost) are examined and compared with four physics-informed persistence models reported in Part I and the simple persistence model to assess the improvement of different models. The 7-year measurements at the U.S. Department of Energy's Atmospheric Radiation Measurement's Southern Great Plains Central Facility site are used for forecasts and evaluations. The results reveal that the step-by-step introduction of predictors leads to different improvements for models at different hierarchical levels. Comparison of the ML models with persistence models shows that LSTM and XGBoost outperform all the persistence models, with LSTM having the overall best performance; however, ARIMA underperforms the four physics-informed persistence models. This study demonstrates the importance and utility of incorporating physics into ML models in improving forecast accuracy by introducing a hierarchy of physics-based predictors, distinguishing predictor contributions, and enhancing the ML interpretability. The combined use of Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) significantly improves the forecast accuracy compared to using individual irradiances alone because the pair contains more information on cloud-radiation interactions.
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Doped metal oxide nanocrystals (NCs) exhibit tunable localized surface plasmon resonances (LSPRs) in the infrared spectral region. Compared to the binary oxides commonly studied, plasmonic NCs derived from ternary oxides remain far less explored primarily due to the difficulty of controlling NC phase-purity and stoichiometry. Here, we report the synthesis of inverse spinel-type cadmium stannate (Cd 2 SnO 4 ) NCs, for which cation-exchange reactions were developed to tailor their composition and LSPR properties. X-ray absorption spectroscopy studies revealed that the inequivalent tetrahedrally and octahedrally coordinated Cd 2+ can be selectively exchanged for Cu + and In 3+ ions, respectively, enabling broadband tunable LSPR and Cu-mediated cation-exchange with lanthanide ions that are otherwise difficult to incorporate. Here, our work paves the way for systematic compositional engineering to accelerate the design of complex metal oxide NCs with emerging plasmonic, electronic, and magnetic properties.
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This study performed technoeconomic and life-cycle analyses to assess the economic feasibility and emission benefits and tradeoffs of various biofuel production pathways as an alternative to conventional marine fuels. We analyzed production pathways for (1) Fischer-Tropsch diesel from biomass and cofeeding biomass with natural gas or coal, (2) renewable diesel via hydroprocessed esters and fatty acids from yellow grease and cofeeding yellow grease with heavy oil, and (3) bio-oil via fast pyrolysis of low-ash woody feedstock. We also developed a new version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) marine fuel module for the estimation of life-cycle greenhouse gas (GHG) and criteria air pollutant (CAP) emissions of conventional and biobased marine fuels. The alternative fuels considered have a minimum fuel selling price between 2.36 and 4.58 $/heavy fuel oil gallon equivalent (HFOGE), and all exhibit improved life-cycle GHG emissions compared to heavy fuel oil (HFO), with reductions ranging from 40 to 93%. The alternative fuels also exhibit reductions in sulfur oxides and particulate matter emissions. Additionally, when compared with marine gas oil and liquified natural gas, they perform favorably across most emission categories except for cases where carbon and sulfur emissions are increased by the cofed fossil feedstocks. The pyrolysis bio-oil offers the most promising marginal CO2 abatement cost at less than $100/tonne CO2e for HFO prices >$1.09/HFOGE followed by Fischer-Tropsch diesel from biomass and natural gas pathways, which fall below $100/tonne CO2e for HFO prices >$2.25/HFOGE. Pathways that cofeed fossil feedstocks with biomass do not perform as well for marginal CO2 abatement cost, particularly at low HFO prices. This study indicates that biofuels could be a cost-effective means of reducing GHG, sulfur oxide, and particulate matter emissions from the maritime shipping industry and that cofeeding biomass with natural gas could be a practical approach to smooth a transition to biofuels by reducing alternative fuel costs while still lowering GHG emissions, although marginal CO2 abatement costs are less favorable for the fossil cofeed pathways.