Controlled Kinetics of On-Surface Dehydrogenation using a Low-Energy Electron Beam

Self-assembly and on-surface synthesis are vital strategies used for fabricating surface-confined 1D or 2D supramolecular nanoarchitectures with atomic precision. In many systems, the resulting structure is determined by kinetics of processes involved, i.e., reaction rate, on-surface diffusion, nucleation, and growth, all of which are typically governed by temperature. However, other external factors have been only scarcely harnessed to control the on-surface chemical reaction kinetics and self-assembly. Here, we show that a low-energy electron beam can be used to steer chemical reaction kinetics and induce the growth of molecular phases unattainable by thermal annealing. The electron beam provides a well-controlled means of promoting the elementary reaction step, i.e., deprotonation of carboxyl groups. The reaction rate linearly increases with increasing electron beam energy beyond the threshold energy of 6 eV. Our results offer the novel prospect of controlling the self-assembly, enhancing the rate of reaction steps selectively, and thus altering the kinetic rate hierarchy.

Solution and Parameter Identification of a Fixed-Bed Reactor Model for Catalytic CO2 Methanation Using Physics-Informed Neural Networks

In this study, we develop physics-informed neural networks (PINNs) to solve an isothermal fixed-bed (IFB) model for catalytic CO2 methanation. The PINN includes a feed-forward artificial neural network (FF-ANN) and physics-informed constraints, such as governing equations, boundary conditions, and reaction kinetics. The most effective PINN structure consists of 5–7 hidden layers, 256 neurons per layer, and a hyperbolic tangent (tanh) activation function. The forward PINN model solves the plug-flow reactor model of the IFB, whereas the inverse PINN model reveals an unknown effectiveness factor involved in the reaction kinetics. The forward PINN shows excellent extrapolation performance with an accuracy of 88.1% when concentrations outside the training domain are predicted using only one-sixth of the entire domain. The inverse PINN model identifies an unknown effectiveness factor with an error of 0.3%, even for a small number of observation datasets (e.g., 20 sets). These results suggest that forward and inverse PINNs can be used in the solution and system identification of fixed-bed models with chemical reaction kinetics.

Parametrical investigation for the optimization of spherical jet-stirred reactors design using large eddy simulations

Due to the importance of gas-phase chemical reaction kinetics in low-emission combustion, stirred tank reactors have been used for decades as an experimental tool to study high- and low-temperature oxidation. A Jet-Stirred Reactor (JSR) setup is valuable to determine the evolution of species mole fractions. For the accuracy of the experimental results, it is important that a JSR is designed such that the concentration field is as homogeneous as possible in order to avoid disturbance of the chemical kinetics. In this work, numerical simulations were performed to investigate the mixing in a JSR chamber. The turbulent structures inside the JSR and the nozzles are captured using Large Eddy Simulations. We conducted numerically a parametric study to evaluate the effects of thermodynamic conditions and geometrical parameters on the mixing characteristics. More specifically, the diameter of the spherical chamber is modified together with the diameter of the nozzles through which fresh gases are fed. The characterization of the gas flow inside a typical spherical JSR layout and results derived by the normalized standard deviation of a tracer mass fraction show that a reduction of the JSR diameter at high pressures improves the homogeneity. Further, we propose a new optimized configuration consisting of six nozzles pointing to the center of the reactor which provides a more uniform composition compared to the standard JSR design.

Review of ZnO Binary and Ternary Composite Anodes for Lithium-Ion Batteries

To enhance the performance of lithium-ion batteries, zinc oxide (ZnO) has generated interest as an anode candidate owing to its high theoretical capacity. However, because of its limitations such as its slow chemical reaction kinetics, intense capacity fading on potential cycling, and low rate capability, composite anodes of ZnO and other materials are manufactured. In this study, we introduce binary and ternary composites of ZnO with other metal oxides (MOs) and carbon-based materials. Most ZnO-based composite anodes exhibit a higher specific capacity, rate performance, and cycling stability than a single ZnO anode. The synergistic effects between ZnO and the other MOs or carbon-based materials can explain the superior electrochemical characteristics of these ZnO-based composites. This review also discusses some of their current limitations.

Numerical simulation of n-dodecane spray combustion based on OpenFOAM

For the purpose of providing the scientific insights to combustion characteristics of spray jet, numerical calculations of reacting and non-reacting spray cases are performed for ECN (engine combustion network) Spray A (n-dodecane spray combustion) which coupled finite chemistry combustion model PaSR and detailed chemical reaction kinetics based on OpenFOAM. The applicability and accuracy of the spray model is verified in the non-reacting spray case, and it is found that the predicted spray characteristics such as the penetration length of liquid and vapor and the mixture fraction are in good agreement with the test results. The two processes of low-temperature reaction and high-temperature ignition experienced by n-dodecane spray ignition are analyzed in reacting spray case, and it is found that the low-temperature reaction continues to exothermic before high-temperature ignition, and continues to proceed stably after high-temperature ignition, which promotes high-temperature ignition and flame stability. Finally, the effects of different fuel injection pressures on ignition delay time and flame lift-off length are studied.