Adsorption of molecular oxygen on doped graphene: atomic, electronic and magnetic properties

Adsorption of molecular oxygen on B-, N-, Al-, Si-, P-, Cr- and Mn-doped graphene is theoretically studied using density functional theory in order to clarify if O2 can change the possibility of using doped graphene for gas sensors, electronic and spintronic devices. O2 is physisorbed on B-, and Ndoped graphene with small adsorption energy and long distance from the graphene plane, indicating the oxidation will not happen; chemisorption is observed on Al-, Si-, P-, Cr- and Mn-doped graphene. The local curvature caused by the large bond length of X-C (X represents the dopants) relative to CC bond plays a very important role in this chemisorption. The chemisorption of O2 induces dramatic changes of electronic structures and localized spin polarization of doped graphene, and in particular, chemisorption of O2 on Cr-doped graphene is antiferromagnetic. The analysis of electronic density of states shows the contribution of the hybridization between O and dopants is mainly from the p or d orbitals. Furthermore, spin density shows that the magnetization locates mainly around the doped atoms, which may be responsible for the Kondo effect. These special properties supply a good choice to control the electronic properties and spin polarization in the field of graphene engineering.Comment: 7 pages, 10 figure

A Case based Online Trajectory Planning Method of Autonomous Unmanned Combat Aerial Vehicles with Weapon Release Constraints

As a challenging and highly complex problem, the trajectory planning for unmanned combat aerial vehicle (UCAV) focuses on optimising flight trajectory under such constraints as kinematics and complicated battlefield environment. An online case-based trajectory planning strategy is proposed in this study to achieve rapid control variables solution of UCAV flight trajectory for the of delivery airborne guided bombs. Firstly, with an analysis of the ballistic model of airborne guided bombs, the trajectory planning model of UCAVs is established with launch acceptable region (LAR) as a terminal constraint. Secondly, a case-based planning strategy is presented, which involves four cases depending on the situation of UCAVs at the current moment. Finally, the feasibility and efficiency of the proposed planning strategy is validated by numerical simulations, and the results show that the presented strategy is suitable for UCAV performing airborne guided delivery missions in dynamic environments

Bregman Graph Neural Network

Numerous recent research on graph neural networks (GNNs) has focused on formulating GNN architectures as an optimization problem with the smoothness assumption. However, in node classification tasks, the smoothing effect induced by GNNs tends to assimilate representations and over-homogenize labels of connected nodes, leading to adverse effects such as over-smoothing and misclassification. In this paper, we propose a novel bilevel optimization framework for GNNs inspired by the notion of Bregman distance. We demonstrate that the GNN layer proposed accordingly can effectively mitigate the over-smoothing issue by introducing a mechanism reminiscent of the "skip connection". We validate our theoretical results through comprehensive empirical studies in which Bregman-enhanced GNNs outperform their original counterparts in both homophilic and heterophilic graphs. Furthermore, our experiments also show that Bregman GNNs can produce more robust learning accuracy even when the number of layers is high, suggesting the effectiveness of the proposed method in alleviating the over-smoothing issue

Quantum Langevin molecular dynamics determination of the solar-interior equation of state

The equation of state (EOS) of the solar interior is accurately and smoothly determined from \textit{ab initio} simulations named quantum Langevin molecular dynamics (QLMD) in the pressure range of $58 \leq P \leq 4.6\times10^5$ Mbar at the temperature range of $1 \leq T \leq 1500$ eV. The central pressure is calculated, and compared with other models. The effect of heavy elements such as carbon and oxygen on the EOS is also discussed.Comment: to publish in AP

Thermal conductivity of MgO in giant planetary interior conditions predicted by deep potential

Thermal conductivity $\kappa$ of MgO plays a fundamental role in understanding the thermal evolution and mantle convection in the interior of terrestrial planets. However, previous theoretical calculations deviate from each other and the $\kappa$ of high-pressure B2 phase remains undetermined. Here, by combining molecular dynamics and deep potential trained with first-principles data, we systematically investigate the $\kappa$ of MgO from ambient state to the core-mantle boundary (CMB) of super-Earth with $5M_{\oplus}$. We point out the significance of 4-phonon scatterings and modify the conventional thermal conductivity model of MgO by considering the density-dependent proportion of 3-phonon and 4-phonon scatterings. The $\kappa$ profiles of MgO in Earth and super-Earth are further estimated. For super-Earth, we predict a significant reduction of $\kappa$ at the B1-B2 phase transition area near the CMB. This work provides new insights into thermal transport under extreme conditions and an improved thermal model for terrestrial planets.Comment: 4 figure