Acrolein hydrogenation on Pt(211) and Au(211) surfaces:a density functional theory study

Partial hydrogenation of acrolein, the simplest alpha, beta-unsaturated aldehyde, is not only a model system to understand the selectivity in heterogeneous catalysis, but also technologically an important reaction. In this work, the reaction on Pt(211) and Au(211) surfaces is thoroughly investigated using density functional theory calculations. The formation routes of three partial hydrogenation products, namely propenol, propanal and enol, on both metals are studied. It is found that the pathway to produce enol is kinetically favoured on Pt while on Au the route of forming propenol is preferred. Our calculations also show that the propanal formation follows an indirect pathway on Pt(211). An energy decomposition method to analyze the barrier is utilized to understand the selectivities at Pt(211) and Au(211), which reveals that the interaction energies between the reactants involved in the transition states play a key role in determining the selectivity difference.

A Model to Understand the Oxygen Vacancy Formation in Zr-Doped CeO2:Electrostatic Interaction and Structural Relaxation

Using density functional theory with the inclusion of on-site Coulomb Correction, the O vacancy formation energies of CexZr1-xO2 solid solutions with a series of Ce/Zr ratios are calculated, and a model to understand the results is proposed. It consists of electrostatic and structural relaxation terms, and the latter is found to play a vital role in affecting the O vacancy formation energies. Using this model, several long-standing questions in the field, such as why ceria with 50% ZrO2 usually exhibit the best oxygen storage capacity, can be explained. Some implications of the new interpretation are also discussed.

Multiple configurations of the two excess 4f electrons on defective CeO2(111):Origin and implications

Density-functional theory calculations have been carried out to systematically study single surface oxygen vacancies on CeO2(111). It is surprisingly found that multiple structures with the two excess electrons localized at different positions can exist. We show that the origin of the multiconfigurations of 4f electrons is a result of geometric relaxation on the surface and strong localization characteristic of 4f electrons in ceria. The importance of 4f electron structures is also presented and discussed. These results may possess implications for our understanding of materials with f electrons.

Structure and Catalytic Activity of Gold in Low-Temperature CO Oxidation

Structures and catalytic activities of Au thin films supported at anatase TiO(2)(101)) and a Au substrate are studied by using density functional theory calculations. The results show that O(2) can hardly adsorb at flat and stepped Au thin films, even supported by fully reduced TiO(2)(101) that can highly disperse Au atoms and offer strong electronic promotion. Interestingly, in both oxide-supported and pure Au. systems, wire-structured Au can adsorb both CO and O(2) rather strongly, and kinetic analysis suggests its high catalytic activity for low-temperature CO oxidation. The d-band center of Au at the catalytic site is determined to account for the unusual activity of the wire-structured film. A generalized structural model based on the wire-structured film is proposed for active Au, and possible support effects are discussed: Selected oxide surfaces can disperse Au atoms and stabilize the formation of a filmlike structure; they may also serve as a template for the preferential arrangement of Au atoms in a wire structure under low Au coverage.

An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.

Evolution of microstructure and changes of mechanical properties of CLAM steel after long-term aging

The China Low Activation Martensitic (CLAM) steel has been developed as a candidate structural material for future fusion reactors. It is essential to investigate the evolution of microstructure and changes of mechanical properties of CLAM steel during thermal exposure. In this study, the long-term thermal aging of the CLAM steel has been carried out in air at 600 °C and 650 °C for 1100 h, 3000 h and 5000 h. The microstructural evolution with aging time was studied, including characteristics of the growth of M23C6 carbides and the formation of Laves-phase precipitates as well as the evolved subgrains. The microstructural evolution leads to the changes of mechanical properties of the CLAM steel. The Ductile–Brittle Transition Temperature (DBTT) increases significantly during the thermal aging, which is related to the formation of Laves-phase in the steel matrix. The possible mechanism of stabilizing microstructure during the thermal exposure has been analyzed based on the interaction between M23C6 carbides and subgrain boundaries.

Low cycle fatigue properties of CLAM steel at room temperature

The low cycle fatigue (LCF) properties and the fracture behavior of China Low Activation Martensitic (CLAM) steel have been studied over a range of total strain amplitudes from 0.2 to 2.0%. The specimens were cycled using tension-compression loading under total strain amplitude control. The CLAM steel displayed initial hardening followed by continuous softening to failure at room temperature in air. The relationship between strain and fatigue life was predicted using the parameters obtained from fatigue test. The factors effecting on low cycle fatigue of CLAM steel consisted of initial state of matrix dislocation arrangement, magnitude of cyclic stress, magnitude of total strain amplitude and microstructure. The potential mechanisms controlling the stress response, cyclic strain resistance and low cycle fatigue life have been evaluated.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

Multi-agents modelling of EV purchase willingness based on questionnaires

Traditional experimental economics methods often consume enormous resources of qualified human participants, and the inconsistence of a participant’s decisions among repeated trials prevents investigation from sensitivity analyses. The problem can be solved if computer agents are capable of generating similar behaviors as the given participants in experiments. An experimental economics based analysis method is presented to extract deep information from questionnaire data and emulate any number of participants. Taking the customers’ willingness to purchase electric vehicles (EVs) as an example, multi-layer correlation information is extracted from a limited number of questionnaires. Multi-agents mimicking the inquired potential customers are modelled through matching the probabilistic distributions of their willingness embedded in the questionnaires. The authenticity of both the model and the algorithm is validated by comparing the agent-based Monte Carlo simulation results with the questionnaire-based deduction results. With the aid of agent models, the effects of minority agents with specific preferences on the results are also discussed.

A novel forward gene selection algorithm for microarray data

This paper investigates the gene selection problem for microarray data with small samples and variant correlation. Most existing algorithms usually require expensive computational effort, especially under thousands of gene conditions. The main objective of this paper is to effectively select the most informative genes from microarray data, while making the computational expenses affordable. This is achieved by proposing a novel forward gene selection algorithm (FGSA). To overcome the small samples' problem, the augmented data technique is firstly employed to produce an augmented data set. Taking inspiration from other gene selection methods, the L2-norm penalty is then introduced into the recently proposed fast regression algorithm to achieve the group selection ability. Finally, by defining a proper regression context, the proposed method can be fast implemented in the software, which significantly reduces computational burden. Both computational complexity analysis and simulation results confirm the effectiveness of the proposed algorithm in comparison with other approaches

An efficient and robust case sorting for algorithm for transient stability assessment

An efficient and robust case sorting algorithm based on Extended Equal Area Criterion (EEAC) is proposed in this paper for power system transient stability assessment (TSA). The time-varying degree of an equivalent image system can be deduced by comparing the analysis results of Static EEAC (SEEAC) and Dynamic EEAC (DEEAC), the former of which neglects all time-varying factors while the latter partially considers the time-varying factors. Case sorting rules according to their transient stability severity are set combining the time-varying degree and fault messages. Then a case sorting algorithm is designed with the “OR” logic among multiple rules, based on which each case can be identified into one of the following five categories, namely stable, suspected stable, marginal, suspected unstable and unstable. The performance of this algorithm is verified by studying 1652 contingency cases from 9 real Chinese provincial power systems under various operating conditions. It is shown that desirable classification accuracy can be achieved for all the contingency cases at the cost of very little extra computational burden and only 9.81% of the whole cases need to carry out further detailed calculation in rigorous on-line TSA conditions.

ALMA Observations of a Gap and a Ring in the Protoplanetary Disk around TW Hya

We report the first detection of a gap and a ring in dust continuum emission from the protoplanetary disk around TW Hya, using the Atacama Large Millimeter/Submillimeter Array. The gap and ring are located at 25 and 41 AU from the central star, respectively, and are associated with the CO snowline at ~ 30AU. The gap width and depth are 15AU at the maximum and 23% at the minimum, respectively, regarding that the observations are limited to an angular resolution of ~ 15AU. In addition, we detect a decrement in CO line emission down to ~ 10AU, indicating freeze-out of gas-phase CO onto grain surfaces and possible subsequent surface reactions to form larger molecules. According to theoretical studies, the gap could be caused by gravitational interaction between the disk gas and a planet with a mass less than super-Neptune (2 Neptune mass), or result from destruction of large dust aggregates due to the sintering of CO ice.