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Developing efficient and durable bifunctional electrocatalysts for oxygen reduction and evolution reaction (ORR/OER) is highly desirable in energy conversion and storage systems. This study prepares nickel–ruthenium layered double hydroxide (NiRu-LDHs) nanosheets subjected to decoration with conductive silver nanoparticles (Ag NP/NiRu-LDHs), which interestingly induce their multivacancies associated with catalytic site activity and populations. The as-prepared Ag NP/NiRu-LDH shows excellent catalytic activity toward both OER and ORR features with low onset overpotentials of 0.21 V and −0.27 V, respectively, with a 0.76 V potential gap between OER potential at 10 mA cm–2 and ORR potential at −3 mA cm–2, demonstrating that it is the preeminent bifunctional electrocatalyst reported to date. Compared with pristine NiRu-LDHs, the resulting Ag NP/NiRu-LDHs nanosheets require only an overpotential of 0.31 V to deliver 10 mA cm–2 with excellent durability. The superb bifunctional performance of Ag NP/NiRu-LDH is ascribed to the formation of multivacancies, mutual benefits of synergistic effect between metal LDHs and silver nanoparticles, and increased accessible active sites together with site activity are the key to the perceived performance. This work provides a new strategy to decorate LDHs and to engineer multivacancies to enhance site activity and populations simultaneously as ORR/OER bifunctional electrocatalysts.

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This study uses ground-based dual-Doppler radar and surface observations to document the structural and surface features of the arc-shaped radar echoes (ASREs) evident along an outer rainband of Typhoon Longwang as it approached northern Taiwan on 1 October 2005. The particular aim of this study is to explore the possible distinction between the present case, previously documented tropical cyclone rainbands (TCRs), and squall lines. The dual-Doppler-derived fields show that the leading precipitation of the studied ASREs exhibited a convective nature with a sharp horizontal gradient of reflectivity and a significant vertical extent. The regions behind the leading convection were characterized by band-relative rear-to-front flow at low levels and were associated with a broader area of stratiform precipitation. The deep layer of front-to-rear flow extending from the surface to the upper troposphere was generally present ahead of the ASREs. This flow appears to be lifted upward at and immediately ahead of the leading edge of the low-level rear-to-front flow to form rearward-tilting updrafts. These airflow patterns are similar to those of the convective region of squall lines but differ fundamentally from those of previously documented TCRs that were located closer to the inner core of cyclones. The detailed analyses of surface fluctuations during the passage of one of the studied ASREs further show an abrupt pressure rise (2 mb), a temperature drop (48C), and a pronounced deceleration of inflow air coincident with the leading heavy precipitation. The evaluation presented suggests that the convectively generated cold pool may be important in influencing the structures and propagation of the studied ASREs.

Fault diagnosis using structural knowledge, namely, the signed directed graph (SDG), is presented.A design procedure is proposed to overcome several problems associated with the SDG: (1) it produces spurious (multiple) interpretations and (2) it may delete the true interpretation when the process variable is going through nonsingle transition (this is frequently encountered in a control loop). The proposed method has the following features: (1) discretize a continuous process response into several states, and different conditions (truth tables) are imposed to check the consistency of fault propagation; (2) find the dominant path of fault propagation using steady-state gains; and (3) express the variable associated with the integrator in the velocity form. The first feature improves the modularity of the diagnostic system, which in term makes the design and maintenance of the diagnostic system easy. Furthermore, improved diagnostic resolution can be achieved by imposing more stringent conditions a t different states and by finding the dominant path. The third feature enables the system to handle variables with nonsingle transition in a control loop. A CSTR example is used to illustrate the design procedure. Simulation results show that the proposed approach based on the SDG provides an attractive alternative for process diagnosis. IntroductionIn an operating chemical plant, product quality and plant safety are maintained by controlling process variables. If there are any equipment malfunctions or human error, the product quality may suffer, the plant may be forced to shut down, and catastrophic events such as explosions, fires, or the release of toxic chemicals may occur. In most chemical plants, abnormal measurements trigger alarms in the central control room, which alert process operators. It is normally the operator's responsibility to take remedial actions to restore the plant to normal operation or to initiate the shut-down procedure. Hence, operators must find out the causes of process upsets, i.e., the fault origin. The process of finding the fault origin is called "fault diagnosis".Conventionally, fault diagnosis is the responsibility of the process operators. It is not an easy task for the operators to diagnose process faults because many factors affect the performance of the operators responding to a process alarm. These factors include the number and frequency of alarm firing, the mode of presentation of data to process operators, the complexity of the plant, and the operator's training, experience, alertness, and reaction to stress. These factors make the fault diagnosis by operators difficult. Therefore, the automated diagnostic system becomes attractive.Techniques for automated diagnosis can be classified into qualitative approach and quantitative approach depending on how rigorous the model is. Quantitative fault diagnosis utilizes a rigorous process model and on-line measurements to back-calculate unmeasured process variables as well as model parameters (Isermann, 1984). This kind of approach can a...