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Results for “carbonization”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Ultrafast microwave-assisted synthesis of highly nitrogen-doped ordered mesoporous carbon
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Lessons for machine learning from the analysis of porosity-permeability transforms for carbonate reservoirs
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High pressure ignition delay times of H2/CO mixture in carbon dioxide and argon diluent
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Energetic insights into the crystallization of lanthanum carbonate amorphous precursors
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Bringing carbon to life via one-carbon metabolism
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Regulated redirection of central carbon flux enhances anaerobic production of bioproducts in Zymomonas mobilis
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Acid Erosion of Carbonate Fractures and Accessibility of Arsenic-Bearing Minerals: In Operando Synchrotron-Based Microfluidic Experiment
Underground flows of acidic fluids through fractured rock can create new porosity and increase accessibility to hazardous trace elements such as arsenic. In this study, we developed a custom microfluidic cell for an in operando synchrotron experiment using X-ray attenuation. The experiment mimics reactive fracture flow by passing an acidic fluid over a surface of mineralogically heterogeneous rock from the Eagle Ford shale. Over 48 h, calcite was preferentially dissolved, forming an altered layer 200–500 μm thick with a porosity of 63–68% and surface area >10$\times$ higher than that in the unreacted shale as shown by xCT analyses. Calcite dissolution rate quantified from the attenuation data was 3 $\times$ 10 –4 mol/m 2 s and decreased to 3 $\times$ 10 –5 mol/m 2 s after 24 h because of increasing diffusion limitations. Erosion of the fracture surface increased access to iron-rich minerals, thereby increasing access to toxic metals such as arsenic. Quantification using XRF and XANES microspectroscopy indicated up to 0.5 wt % of As(-I) in arsenopyrite and 1.2 wt % of As(V) associated with ferrihydrite. This study provides valuable contributions for understanding and predicting fracture alteration and changes to the mobilization potential of hazardous metals and metalloids.
Performance-Based Payments for Soil Carbon Sequestration Can Enable a Low-Carbon Bioeconomy
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Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model
We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.
Activation, Dehydrogenation, and Carbon–Carbon Coupling of Methane by Iridium Cations Studied by Infrared Multiple Photon Dissociation Spectroscopy and Density Functional Theory
Products resulting from the sequential activation of one, two, three, and four methane molecules by atomic iridium cations were characterized by gas-phase infrared multiple photon dissociation spectroscopy and density functional theory (DFT) calculations. Iridium cations were generated using a laser ablation source and reacted with methane in a linear radiofrequency ion trap before mass analysis and spectroscopic interrogation in a Fourier transform ion cyclotron resonance mass spectrometer coupled to the free-electron laser for intracavity experiments (FELICE) beamline. Product ions were irradiated using infrared light over the 250–1500 cm –1 range. Comparisons between the experimental and DFT-calculated spectra enabled structural determination of the products formed. The observed products include HIrCH + , Ir(CH 2 ) 2 + , H s Ir(C 3 H 5 ) + , and Ir(CH 3 ) s (C 3 H 5 ) + , where the subscript s denotes a syn orientation of the two ligands. Furthermore, formation of the latter two products provides evidence for efficient C–H bond activation and subsequent C–C coupling on the atomic iridium cation.