Dissociation cross sections and rates in O2 + N collisions: molecular dynamics simulations combined with machine learning.

The collision-induced dissociation reaction of O2 (v, j) + N, a fundamental process in nonequilibrium air flows around reentry vehicles, has been studied systematically by applying molecular dynamics simulations on the 2A', 4A' and 6A' potential energy surfaces of NO2 in a wide temperature range. In particular, we have directly investigated the role of the 6A' surface in this process and discussed the applicability of the simplified approximate rate models proposed by Esposito et al. and Andrienko et al. based on the lowest two surfaces. The present work indicates that the state-selected dissociation of O2 + N is dominated by the 6A' surface for all except for the low-lying O2 states. Furthermore, a complete database of rovibrationally detailed cross sections and rate coefficients is a prerequisite for modeling the relevant nonequilibrium air flows in spacecraft reentry. Here, the combination of the quasi-classical trajectory (QCT) and the neural network (NN) has been proposed to predict all state-selected dissociation cross sections and further construct dissociation parameter sets. All NN-based models established in this work accurately reproduce the results calculated from QCT simulations over a wide range of rovibrational quantum numbers with R2 > 0.99. Compared with the explicit QCT simulations, the computational requirement for predicting cross sections and rates based on the NN models significantly reduces. Finally, thermal equilibrium rate coefficients computed from NN models match remarkably well the available theoretical and experimental results in the whole temperature range explored.

Exhaustive state-specific dissociation study of the N2(Σg+1)+N(S4) system using QCT combined with a neural network method.

This work studies the exhaustive rovibrational state-specific collision-induced dissociation properties of the N2+N system by QCT (quasi-classical trajectory) combined with a neural network method based on the ab initio PES recently published by Varga et al. [Phys. Chem. Chem. Phys. 23, 26273 (2021)]. The QCT combined with a neural network for state-specific dissociation (QCT-NN-SSD) model is developed and used to predict the dissociation cross sections and their energy dependence on the thermal range from a sparsely sampled noisy dataset. It is conservatively estimated that using this method can reduce the cost of the calculation by 96.5%. The rate coefficient of thermal non-equilibrium between different energy modes is obtained by combining the QCT-NN-SSD model with the multi-temperature model. The results show that, for the equilibrium state, dissociation mainly occurs at high vibrational and moderately low rotational levels. When the system is in non-equilibrium, there is no obvious vibrational level preference and highly rotationally excited molecules play a major role in promoting the dissociation by compensating for the lack of vibrational energy. The use of neural network training to generate complete datasets based on limited and discrete data provides an economical and reliable way to obtain a complete kinetic database needed to accurately simulate non-equilibrium flows.

Insight into thermal regulation of supercapacitors via surface-engineered phase change microcapsules.

Constructing efficient thermal management system to settle the thermal runaway of energy storage devices via employing phase change microcapsules (MEPCMs) is of great significance. However, it is still a challenge that the conventional MEPCMs go against the electrochemical performance and hardly be homogenously fixed in the electrodes. In order to conquer these long-standing critical issues, we designed a novel electrochemically active double-shell phase change microcapsule by introducing polypyrrole on the surface of dense amine resin shell of the conventional inert MEPCM. The active MEPCMs@PPy are uniformly immobilized on the surface of the electrode material using reduced graphene oxide to ensure the stable and efficient operation of the flexible supercapacitor. The assembled all-solid-state supercapacitor containing MEPCMs@PPy (SCs@MEPCMs@PPy) lagged 103 s to 55 °C than the SCs@00 without the added phase change material. At a high temperature of 55 °C and a scan rate of 50 mV s-1, SCs@MEPCMs@PPy exhibits an areal specific capacitance of 110.6 mA cm-2, which is higher than that of the original SCs@MEPCMs. A capacitance retention of 79.8 % and coulombic efficiency of 98.4 % can be reached after 3000 cycles. This study opens a new avenue for developing applicable microencapsulated phase change materials in temperature-regulated electrode systems for supercapacitors and alkaline-ion batteries.

HfS2/MoTe2 vdW heterostructure: bandstructure and strain engineering based on first-principles calculation.

In this study, a multilayered van der Waals (vdW) heterostructure, HfS2/MoTe2, was modeled and simulated using density functional theory (DFT). It was found that the multilayers (up to 7 layers) are typical indirect bandgap semiconductors with an indirect band gap varying from 0.35 eV to 0.51 eV. The maximum energy value of the valence band (VBM) and the minimum energy value of the conduction band (CBM) of the heterostructure were found to be dominated by the MoTe2 layer and the HfS2 layer, respectively, characterized as type-II band alignment, leading to potential photovoltaic applications. Optical spectra analysis also revealed that the materials have strong absorption coefficients in the visible and ultraviolet regions, which can be used in the detection of visible and ultraviolet light. Under an external strain perpendicular to the layer plane, the heterostructure exhibits a general transition from semiconductor to metal at a critical interlayer-distance of 2.54 Å. The carrier effective mass and optical properties of the heterostructures can also be modulated under external strain, indicating a good piezoelectric effect in the heterostructure.

Two-dimensional hybrid layered materials: strain engineering on the band structure of MoS2/WSe2 hetero-multilayers.

In this paper, we report a comprehensive modeling and simulation study of constructing hybrid layered materials by alternately stacking MoS2 and WSe2 monolayers. Such hybrid MoS2/WSe2 hetero-multilayers exhibited direct bandgap semiconductor characteristics with bandgap energy (E g) in a range of 0.45-0.55 eV at room temperature, very attractive for optoelectronics (wavelength range 2.5-2.75 µm) based on thicker two-dimensional (2D) materials. It was also found that the interlayer distance has a significant impact on the electronic properties of the hetero-multilayers, for example a five orders of magnitude change in the conductance was observed. Three material phases, direct bandgap semiconductor, indirect bandgap semiconductor, and metal were observed in MoS2/WSe2 hetero-multilayers, as the interlayer distance decreased from its relaxed (i.e., equilibrium) value of about 6.73 Å down to 5.50 Å, representing a vertical pressure of about 0.8 GPa for the bilayer and 1.5 GPa for the trilayer. Such new hybrid layered materials are very interesting for future nanoelectronic pressure sensor and nanophotonic applications. This study describes a new approach to explore and engineer the construction and application of tunable 2D semiconductors.