Optical Absorption of SiC,BN, and BeO Nanosheets in Holstein Model

By applying the full π-band Holstein model, we analytically have calculated the electronic density of states (DOS) and optical conductivity of doped gapped graphene-like structures including silicon carbide (SiC), boron nitride (BN), and beryllium monoxide (BeO) beyond the Dirac cone approximation. We have implemented the Kubo linear response formalism which is established to get the retarded self-energy here. For strong electron-phonon (e-ph) coupling strengths, an addition peak in the optical conductivity has been found, associated with transitions between the midgap states and the Van Hove singularities of the main π-bands. Optical conductivity (optical absorption) decreases (increases) with the gap which is useful in the fabrication of low-dimensional-based solar cells. At large gaps, a clean sheet of doped graphene has a zero optical conductivity at low energies because of the optically interband excitations through the Dirac points. Also, the Drude weight remains unchanged for all cases at low energy regimes. Consequently, DOS and optical conductivity remain constant with temperature at low e-ph interaction strengths.     

Near‐optimal online routing in opportunistic networks

In opportunistic networks, nodes communicate intermittently based on store‐carry‐forward paradigm while exploiting node mobility. The challenge is to determine the ideal nodes to deliver the messages since there is no end‐to‐end connectivity. The nodes might make this decision based on the data sensed from the network. This technique is not ideal in scenarios where the speed of changes in the network topology is greater than the speed at which the nodes can collect info on the network, which might, in turn, be restricted due to usage constraints and uncertainty of knowledge about future contacts. To tackle the problems raised by the non‐deterministic environments, in this paper, a stochastic optimization model and corresponding algorithm are developed to find the optimal routes by considering the short and long‐term impact of choices, ie, the next hop. Herein, we first propose a stochastic model to resolve the routing problem by identifying the shortest path. In the second step, we show that the optimal solution of the proposed model can be determined in polynomial time. An online algorithm is then proposed and analyzed. The algorithm is O( lognρ ) competitive considering the number of nodes and their associated energy. This model can take advantage of the unexpected meets to make the routing more elastic in a short time of contact and with less of a burden on the buffer. The simulation results, against the prominent algorithms, demonstrate significant improvement of the proposed approach in delivery and average delay ratio.     

Safe reinforcement learning for dynamical games

This article presents a novel actor‐critic‐barrier structure for the multiplayer safety‐critical systems. Non‐zero‐sum (NZS) games with full‐state constraints are first transformed into unconstrained NZS games using a barrier function. The barrier function is capable of dealing with both symmetric and asymmetric constraints on the state. It is shown that the Nash equilibrium of the unconstrained NZS guarantees to stabilize the original multiplayer system. The barrier function is combined with an actor‐critic structure to learn the Nash equilibrium solution in an online fashion. It is shown that integrating the barrier function with the actor‐critic structure guarantees that the constraints will not be violated during learning. Boundedness and stability of the closed‐loop signals are analyzed. The efficacy of the presented approach is finally demonstrated by using a simulation example.     

Post-Markovian dynamics of quantum correlations: entanglement versus discord

Dynamics of an open two-qubit system is investigated in the post-Markovian regime, where the environments have a short-term memory. Each qubit is coupled to separate environment which is held in its own temperature. The inter-qubit interaction is modeled by XY–Heisenberg model in the presence of spin–orbit interaction and inhomogeneous magnetic field. The dynamical behavior of entanglement and discord has been considered. The results show that quantum discord is more robust than quantum entanglement, during the evolution. Also the asymmetric feature of quantum discord can be monitored by introducing the asymmetries due to inhomogeneity of magnetic field and temperature difference between the reservoirs. By employing proper parameters of the model, it is possible to maintain nonvanishing quantum correlation at high degree of temperature. The results can provide a useful recipe for studying dynamical behavior of two-qubit systems such as trapped spin electrons in coupled quantum dots.     

Hydrological Assessment of the 1973 Treaty on the Transboundary Helmand River,Using the SWAT Model and a Global Climate Database

Exploitation of the water resources of the Helmand River has been challenging for Iran and Afghanistan. Debates on this issue finally led to a treaty in 1973 between the two countries, in which a total amount of 26 m³/s water from the Helmand River should be delivered to Iran in a normal (or an above normal) water year. The treaty also specifies that a “normal water year” means the year during which the total volume of water at the hydrometric station of Dehrawud (upstream of the Kajakai Dam) is 5661.7 million cubic meter (MCM). This paper aims to assess the long term hydrological conditions of the Upper Helmand River, to detect the occurrence of any non-stationary process in its streamflow time series and compare the possible changes with the content of the 1973 water treaty. Due to very date scarce situation of this region, the SWAT (Soil & Water Assessment Tool) model and CRU (Climatic Research Unit) global dataset were applied to create the long term time series. The results showed that there has been no significant change in annual mean flows in the Upper Helmand River basin. However, there is a consistent increase in monthly flows from November to February and a decrease of the flows in June and July. The monthly changes can be attributed to an increasing trend in temperature in the study area, earlier snowmelts during winter and less snow pack in summer. The applied methodology of this study is useful to cope with the region’s data scarcity and can be applied for similar studies requiring long term time series of hydrological variables.     

Carbon monoxide hydrogenation over cobalt catalyst in a tube-wall reactor: Part II. Modelling studies

A mathematical model was developed to predict the performance of Fischer-Tropsch Synthesis over cobalt catalyst in a tube-wall reactor. Comparison was made between model predictions and previous experimental results (part 1 of this paper) for pressures 0.35-1.03 MPa, temperatures 250?275°C, and exposure velocities 139-722 μ/s. The agreement was good. The model predicts an increase in methanation activity with temperature. Carbon monoxide and hydrogen conversions, and water and carbon dioxide concentrations increase along the reactor axis. With an increase in exposure velocity, hydrocarbons and carbon dioxide production increase, but water production decreases. However, the water-gas shift activity increases continuously along the reactor axis. The model is based on two-dimensional transport equations, and employs the orthogonal collocation method in its numerical predictions.     

Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems

In this paper, an integral reinforcement learning (IRL) algorithm on an actor–critic structure is developed to learn online the solution to the Hamilton–Jacobi–Bellman equation for partially-unknown constrained-input systems. The technique of experience replay is used to update the critic weights to solve an IRL Bellman equation. This means, unlike existing reinforcement learning algorithms, recorded past experiences are used concurrently with current data for adaptation of the critic weights. It is shown that using this technique, instead of the traditional persistence of excitation condition which is often difficult or impossible to verify online, an easy-to-check condition on the richness of the recorded data is sufficient to guarantee convergence to a near-optimal control law. Stability of the proposed feedback control law is shown and the effectiveness of the proposed method is illustrated with simulation examples.     

Characterization and methanation activity of supported nickel catalysts

The methanation of carbon monoxide was studied over various supported nickel catalysts in a fixed bed reactor in the temperature range of 250 to 400°C. The hydrogen to carbon monoxide ratio was kept higher than stoichiometric in order to avoid carbon formation. The catalyst particles had an average diameter of 80 pm and nickel contents ranging from 5 to 42 wt %. The performance of laboratory prepared catalysts was compared with commercial ones. The catalysts were characterized by BET surface area, pore volume and carbon monoxide chemisorption. Specific activities for the methanation reaction were obtained and were found to vary with nickel concentration and with crystallite size. There exists a crystallite size range in which the maximum activity was observed. Metal support interactions may also contribute to the vdation in specific activity. The activation energy was found to vary from 58.2 MJ/kmol to 119.4 MJ/kmol. It appears that the methanation reaction over Ni/aIumina catalysts is a structure sensitive reaction. A compensation effect was observed for this reaction.