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A Multiscale Modelling Approach to Elucidate the Mechanism of the Oxygen Evolution Reaction at the Hematite-Water Interface
Full text linkPhotoelectrochemical (PEC) splitting of water to make hydrogen is a promising clean-energy technology. The oxygen evolution reaction (OER) largely determines the energy efficiency in PEC water-splitting. Hematite, which is a cheap and sustainable semiconductor material with excellent chemical properties, a favourable band gap (2.1 eV) and composed of earth abundant elements is a suitable model photoanode material for studying OER. To understand the design of energy efficient anodes, it is highly desirable to have mechanistic insight into OER at an atomistic level which can be directly connected to experimentally measured quantities. We present a multiscale computational model of OER which connects the thermodynamics and kinetics of elementary charge transfer reactions in OER to kinetics of OER at laboratory length and time scales. We couple density functional theory (DFT) and DFT based molecular dynamics (DFT-MD) simulations with solvent effects at an atomistic level with kinetic Monte Carlo (kMC) simulations at a coarse-grained level in our multiscale model. The time and applied bias potential dependent surface coverage, which are experimentally not known, and the O2 evolution rate during OER at the hematite–water interface are calculated by the multiscale model. Furthermore, the multiscale model demonstrates the effect of explicitly modelling the interaction of water with the electrode surface via direct adsorption.</p
Liquid metal as the wall material of fusion reactors: deuterium retention and surface stability
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Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas
No full textA theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X
Effect of Co-Solvents on the Crystallization and Phase Distribution of Mixed-Dimensional Perovskites
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Plasma Driven Exsolution for Nanoscale Functionalization of Perovskite Oxides
Full text linkPerovskite oxides with dispersed nanoparticles on their surface are considered instrumental in energy conversion and catalytic processes. Redox exsolution is an alternative method to the conventional deposition techniques for directly growing well-dispersed and anchored nanoarchitectures from the oxide support through thermochemical or electrochemical reduction. Herein, a new method for such nanoparticle nucleation through the exposure of the host perovskite to plasma is shown. The applicability of this new method is demonstrated by performing catalytic tests for CO2 hydrogenation over Ni exsolved nanoparticles prepared by either plasma or conventional H2 reduction. Compared to the conventional thermochemical H2 reduction, there are plasma conditions that lead to the exsolution of a more than ten times higher Ni amount from a lanthanum titanate perovskite, which is similar to the reported values of the electrochemical method. Unlike the electrochemical method, however, plasma does not require the integration of the material in an electrochemical cell, and is thus applicable to a wide range of microstructures and physical forms. Additionally, when N2 plasma is employed, the nitrogen species are stripping out oxygen from the perovskite lattice, generating a key chemical intermediate, such as NO, rendering this technology even more appealing.</p
Ab initio study of metal carbide hydrides in 2.25Cr1Mo0.25V steel
Full text link2.25Cr1Mo0.25V is a state-of the-art alloy used in the fabrication of modern hydrogenation reactors. Compared to the conventional 2.25Cr1Mo steel, the 2.25Cr1Mo0.25V steel exhibits a better performance, in particular higher hydrogen damage resistance. Previous experimental studies indicate that carbides in steels may be responsible for the hydrogen-induced damage. To gain a better understanding of the mechanism of such damage, it is essential to study hydrogen uptake in metal carbides. In this study, Density Functional Theory (DFT) is used to investigate the stability of chromium, molybdenum and vanadium carbides (CrxCy, MoxCy and VxCy) in the 2.25Cr1Mo0.25V steel. The stability of their corresponding interstitial hydrides was also explored. The results showed that Cr7C3, Mo2C and V6C5 are the most stable carbides in their respective metal–carbon (Cr–C, Mo–C and V–C) binary systems. Specifically, V6C5 shows the strongest hydrogen absorption ability because of its strong V–H and C–H ionic bonds. On the other hand, V4C3, whose presence in the alloy was established in experimental studies, is predicted to be stable as well, along with V6C5. Our findings indicate that the hydrogen absorption ability of V4C3 is higher than that of V6C5. Additionally, the charge and chemical bonding analyses reveal that the stability of the metal carbide hydrides strongly depends on the electronegativity of the metal. Due to the high electronegativity of V, vanadium carbides form the strongest ionic bonds with hydrogen, compared to those of Mo and Cr. The results from this study suggest that the unique capacity of accommodating hydrogen in the vanadium carbides plays an important role in improved hydrogen damage resistance of the 2.25Cr1Mo0.25V alloy in hydrogenation reactors.</p
Neural network surrogate of QuaLiKiz using JET experimental data to populate training space
Full text linkWithin integrated tokamak plasma modeling, turbulent transport codes are typically the computational bottleneck limiting their routine use outside of post-discharge analysis. Neural network (NN) surrogates have been used to accelerate these calculations while retaining the desired accuracy of the physics-based models. This paper extends a previous NN model, known as QLKNN-hyper-10D, by incorporating the impact of impurities, plasma rotation, and magnetic equilibrium effects. This is achieved by adding a light impurity fractional density (n imp,light/n e) and its normalized gradient, the normalized pressure gradient (α), the toroidal Mach number (M tor), and the normalized toroidal flow velocity gradient. The input space was sampled based on experimental data from the JET tokamak to avoid the curse of dimensionality. The resulting networks, named QLKNN-jetexp-15D, show good agreement with the original QuaLiKiz model, both by comparing individual transport quantity predictions and by comparing its impact within the integrated model, JINTRAC. The profile-averaged RMS of the integrated modeling simulations is <10% for each of the five scenarios tested. This is non-trivial given the potential numerical instabilities present within the highly nonlinear system of equations governing plasma transport, especially considering the novel addition of momentum flux predictions to the model proposed here. An evaluation of all 25 NN output quantities at one radial location takes ∼0.1 ms, 104 times faster than the original QuaLiKiz model. Within the JINTRAC integrated modeling tests performed in this study, using QLKNN-jetexp-15D resulted in a speed increase of only 60–100 as other physics modules outside of turbulent transport become the bottleneck.</p