Probing reaction processes and reversibility in Earth-abundant Na[subscript 3]FeF[subscript 6] for N
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Highlights: • The GeoMicro3D model was innovatively developed for simulating the reaction process and microstructure formation of AAS. • In GeoMicro3D, the dissolution of slag and reactions of aqueous ions are fundamentally described in the local lattice cell. • A novel approach is proposed to speed up the nucleation simulations. • GeoMicro3D was implemented and verified with the relevant experimental data and thermodynamic calculation results. For the first time, this study developed a novel model, named GeoMicro3D, to simulate the reaction process and microstructure formation of alkali-activated slag. The GeoMicro3D model consists of four modules that are designed to simulate, respectively: (i) the initial spatial distribution of real-shape slag particles in alkaline activator, (ii) the dissolution of slag and diffusion of ions via the transition state theory and lattice Boltzmann method, respectively, (iii) the spatial distribution of reaction products using a nucleation probability theory, and (iv) the chemical reactions with thermodynamic modelling. Afterwards the GeoMicro3D model was implemented and verified. The simulation results were discussed and compared with the relevant experimental data and thermodynamic calculation results using GEMS. A good agreement was found in the comparisons, showing the strong simulation capability of GeoMicro3D.
We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.
Described herein is a catalytic reaction process including introducing one or more gas-phase reactants into a reactor comprising a microporous catalyst having a pore size less than or equal to 2 nm and adjusting the temperature and/or the pressure of the reactor such that one or more of the gas-phase reactants condense within the micropores of the catalyst thereby causing the catalytic reaction to take place in a liquid phase. Additionally, a process for engineering defects on a carboxylate-based metal organic framework (MOF) catalyst is described. The process includes providing a carboxylate-based MOF catalyst; and heating the carboxylate-based MOF catalyst in an inert gas atmosphere at temperatures between about 150° C. and about 900° C.
Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.
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A highly sensitive CO 2 sensor, comprising nanostructured copper sulfide that exhibits desired localized surface plasmon resonance, demonstrates a significant surface-enhanced infrared absorption for 100 ppm CO 2 with an enhancement factor of 10 4 .
Background: Dust grains condensed in the outflows of presolar classical novae should have been present in the protosolar nebula. Candidates for such presolar nova grains have been found in primitive meteorites and can in principle be identified by their isotopic ratios, but the ratios predicted by state-of-the-art one-dimensional hydrodynamic models are uncertain due to nuclear-physics uncertainties. Purpose: To theoretically calculate the thermonuclear rates and uncertainties of the S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35 reactions and investigate their impacts on the predicted 34 S/ 32 S isotopic ratio for presolar nova grains. Method: A shell-model approach in a (0 +1 ) ℏ ω model space was used to calculate the properties of resonances in the 34 S(p ,γ ) 35 Cl and 34 g,m Cl (p ,γ ) 35 Ar reactions and their thermonuclear rates. Uncertainties were estimated using a Monte Carlo method. The implications of these rates and their uncertainties on sulfur isotopic nova yields were investigated using a postprocessing nucleosynthesis code. The rates for transitions from the ground state of 34 Cl as well as from the isomeric first excited state of 34 Cl were explicitly calculated. Results: At energies in the resonance region near the proton-emission threshold, many negative-parity states appear. Energies, spectroscopic factors, and proton-decay widths are reported. The resulting thermonuclear rates are compared with previous determinations. Conclusions: The shell-model calculations alone are sufficient to constrain the variation of the 34 S/ 32 S ratios to within about 30%. Uncertainties associated with other reactions must also be considered, but in general we find that the 34 S/ 32 S ratios are not a robust diagnostic to clearly identify presolar grains made from nova ejecta.
Manual and automatic methods and devices using a ACOMP system for active control of polymerization reaction processes. An ideal desired trajectory of one or more reaction and polymer characteristics can be established to produce a desired final polymer product with specified characteristics from a polymerization reaction process. A current reaction trajectory of a polymerization reaction process can be driven to an ideal or desired reaction trajectory. In a manual embodiment an operator can use ACOMP data to adjust process variables in order to drive the current reaction trajectory toward the ideal or desired reaction trajectory. In an automated mode a control program can use ACOMP data to make adjustments to process variables to drive the polymerization reaction process toward the desired trajectory as closely as possible either empirically or by solving the governing equations for the polymerization reaction process.
"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects
A numerical simulation study was performed to examine the post-detonation reaction processes produced by the detonation of a 12 mm diameter hemispherical pentaerythritol tetranitrate (PETN) explosive charge. The simulations used a finite rate detailed chemical reaction model consisting of 59 species and 368 reactions to capture post-detonation reaction processes including air dissociation from Mach 19+ shock waves that initially break out of the PETN charge, reactions within the detonation products during expansion, and afterburning when the detonation products mix with the shock heated air. The multi-species and thermodynamically complete Becker-Kistiakowsky-Wilson real-gas equation of state is used for the gaseous phase to allow for the mixing of reactive species. A recent simplified reactive burn model is used to propagate the detonation through the charge and allow for detailed post-detonation reaction processes. The computed blast, shock structures, and mole fractions of species within the detonation products agree well with experimental measurements. A comparison of the simulation results to equilibrium calculations indicates that the assumption of a local equilibrium is fairly accurate until the detonation products rapidly cool to temperatures in the range of 1500-1900 K by expansion waves. Below this range, the computed results show mole fractions that are nearly chemically frozen within the detonation products for a significant portion of expansion. In conclusion, these results are consistent with the freeze out approximation used in the blast modeling community.
The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.
Synthesis of cathode materials plays an important role in determining the production efficiency, cost and performance of lithium-ion batteries. However, the conventional synthesis methods always experience a slow heating rate and involve a complicated multi-step reaction process and sluggish reaction dynamics, leading to high energy and long time consuming. Herein, we report a high-temperature shock (HTS) strategy for the ultra-fast synthesis of cathode materials in seconds. The HTS process experiences an ultra-high heating rate, leading to a non-equilibrium reaction and fast reaction kinetics and avoiding high energy and long time consuming. Mainstream cathode materials (such as LiMn 2 O 4 , LiCoO 2 , LiFePO 4 , and Li-rich layered oxide/NiO heterostructured material) are successfully synthesized with pure phases, oxygen vacancies, ultra-small particle sizes and good electrochemical performance. In conclusion, the HTS process not only provides an efficient synthesis approach for cathode materials but also can be extended beyond lithium-ion batteries.
Iron ore pellets are reduced in a 50%H 2 –50%N 2 1 atm gas mixture at 750, 800, 850, 900, and 950 °C while simultaneously documenting swelling (change in pellet radius) and weight change. Swelling increases with increasing temperature, with catastrophic swelling (>20% of reduction swelling index) observed at 850, 900, and 950 °C. As the pellet is reduced, the pellet radius increases until 40–50% reduction is achieved, followed by a decrease in diameter beyond 40–50% reduction at 750 and 850 °C. At 950 °C, the pellet radius continues to increase with additional pellet reduction without any subsequent decrease in diameter. Scanning electron microscopy (SEM) analysis shows that the neighboring grains inside the pellet sinter together at 750 and 850 °C, whereas the individual grains sinter internally at 950 °C. SEM analysis and observations suggest that the reduction process at 750 and 850 °C can be approximated as a topochemical reaction process, while the reduction process at 950 °C can no longer be approximated as a topochemical reaction process. In conclusion, an empirical equation for the radius of the pellet is derived with fitting parameters dependent on temperature and the degree of reduction of the pellet undergoing reduction based on the experimental data.
Background: Light curves are the primary observable of type-I x-ray bursts. Computational x-ray burst models must match simulations to observed light curves. Most of the error in simulated curves comes from uncertainties in rp process reaction rates, which can be reduced via precision mass measurements of neutron-deficient isotopes in the rp process path. Purpose: Perform a precise atomic mass measurement of 27 P. Use this new measurement to calculate rp process reaction rates and input these rates into an x-ray burst model to reduce simulated light curve uncertainty. Use the mass measurement of 27 P to validate the isobaric multiplet mass equation (IMME) for the A = 27 T = 3/2 isospin quartet which 27 P belongs to. Method: High-precision Penning trap mass spectrometry utilizing the time-of-flight ion cyclotron resonance technique was used to determine the atomic mass of 27 P. The MESA code (Modules for Experiments in Stellar Astrophysics) was then used to simulate x-ray bursts using a one-dimensional multizone model to produce updated light curves. Results: The mass excess of 27 P was measured to be –670.7(6) keV, a 14-fold precision increase over the mass reported in the 2020 Atomic Mass Evaluation (AME2020). The 26 Si(p, $γ$) 27 P– 27 P($γ$, p) 26 Si rate equilibrium has been determined to a higher precision based on the precision mass measurement of 27 P. x-ray burst light curves were produced with the MESA code using the new reaction rates. Changes in the mass of 27 P seem to have minimal effect on light curves, even in burster systems tailored to maximize impact. Conclusion: The mass of 27 P does not play a significant role in x-ray burst light curves. It is important to understand that more advanced models do not just provide more precise results, but often qualitatively different ones. This result brings us a step closer to being able to extract stellar parameters from individual x-ray burst observations. In addition, the IMME has been validated for the A = 27, T = 3/2 quartet. The normal quadratic form of the IMME using the latest data yields a reduced $χ$ 2 of 2.9. Finally, the cubic term required to generate an exact fit to the latest data matches theoretical attempts to predict this term.
The precursor reaction process for the fabrication of Cu(In,Ga)Se 2 solar cells potentially allows for low-cost fabrication and scalable processing for manufacturing. Additionally, this process has yielded record efficiencies in lab-scale experiments. Thus far, research on the precursor reaction method has been restricted to relatively low Ga compositions with Ga/(In+Ga) ≈ 25%. By increasing the ratio of Ga, it is possible to increase the bandgap, and thus, increase the open-circuit voltage. This work develops and characterizes the precursor reaction process for use with Ga/(In+Ga) ≈ 50%, with the goal of improving the open-circuit voltage and efficiency. It is shown that with an increased Ga ratio, increased V ∞ is achieved, but the rate of conversion from the precursor to absorber phases is decreased. Additionally, increased Ga improves the film adhesion at increased selenization temperatures as well as improving the film morphology.
In this work, we employed density functional theory to elucidate the energetics associated with elementary steps along a Langmuir-Hinshelwood mechanism for the Haber-Bosch synthesis of ammonia from N 2 and H 2 on a hexagonal, Mo-terminated molybdenum nitride surface. Using nudged elastic band calculations, we determined the energy barriers involved in the reaction processes. An active site consisting of four nearest-neighbor Mo atoms, previously identified as an active site on similar surfaces, was chosen to investigate the reaction processes. Using this approach, we calculate a barrier of ~0.5 eV for the dissociation of N 2 . The superior activity of the dissociation of the strong N 2 bonds is rationalized based on the unique geometric and electronic configurations present at these active sites. Despite the favorable energetics for nitrogen dissociation, the energy cost for hydrogenation of NH x (0 ≤ x ≤ 2) species is shown to be energetically limiting for the formation of ammonia through the Langmuir-Hinshelwood mechanism at these sites, with elementary step activation barriers calculated to be as large as ~2 eV. A comparison to Haber-Bosch results derived from a similar γ-Mo 2 N model system suggests the relative independence of surface chemistry and bulk stoichiometry for rhombic Mo 4 active sites present on molybdenum nitrides.
The lithium–sulfur (Li–S) battery is a promising next-generation energy storage technology because of its high theoretical energy and low cost. Extensive research efforts have been made on new materials and advanced characterization techniques for mechanistic studies. However, it is uncertain how discoveries made on the material level apply to realistic batteries due to limited analysis and characterization of real high-energy cells, such as pouch cells. Evaluation of pouch cells (>1 A h) (instead of coin cells) that are scalable to practical cells provides a critical understanding of current limitations which enables the proposal of strategies and solutions for further performance improvement. Herein, we design and fabricate pouch cells over 300 W h kg -1 , compare the cell parameters required for high-energy pouch cells, and investigate the reaction processes and their correlation to cell cycling behavior and failure mechanisms. Spatially resolved characterization techniques and fluid-flow simulation reveal the impacts of the liquid electrolyte diffusion within the pouch cells. We found that catastrophic failure of high-energy Li–S pouch cells results from uneven sulfur/polysulfide reactions and electrolyte depletion for the first tens of cycles, rather than sulfur dissolution as commonly reported in the literature. The uneven reaction stems from limited electrolyte diffusion through the porous channels into the central part of thick cathodes during cycling, which is amplified both across the sulfur electrodes and within the same electrode plane. A combination of strategies is suggested to increase sulfur utilization, improve nanoarchitectures for electrolyte diffusion and reduce consumption of the electrolytes and additives.