Conversion of n-type CuTCNQ into p-type nitrogen-doped CuO and the implication for room temperature gas sensing

Sensors to detect toxic and harmful gases are usually based on metal oxides that are operated at elevated temperature. However, enabling gas detection at room temperature (RT) is a significant ongoing challenge. Here, we address this issue by demonstrating that microrods of semiconducting CuTCNQ (TCNQ=7,7,8,8-tetracyanoquinodimethane) with nanostructured features can be employed as conductometric gas sensors operating at 50°C for detection of oxidizing and reducing gases such as NO2 and NH3. The sensor is evaluated at RT and up to 200°C. It was found that CuTCNQ is transformed into a N-doped CuO material with p-type conductivity when annealed at the maximum temperature. This is the first time that such a transformation, from a semiconducting charge transfer material into a N-doped metal oxide is detected. It is shown here that both the surface chemistry and the type of majority charge carrier within the sensing layer is critically important for the type of response towards oxidizing and reducing gases. A detailed physical description of NO2 and NH3 sensing mechanism at CuTCNQ and N-doped CuO is provided to explain the difference in the response. For the N-doped CuO sensor, a detection limit of 1 ppm for NO2 and 10 ppm for NH3 are achieved.

The effect of alternate supply of shielding gases in austenite stainless steel GTA welding

Welding system has now been concentrated on the development of new process to achieve cost savings, higher productivity and better quality in manufacturing industry. Discrete alternate supply of shielding gas is a new technology that alternately supplies the different kinds of shielding gases in weld zone. As the newdevelopedmethods compared to the previous generalwelding with a mixing supply of shielding gas, it cannot only increase thewelding quality, but also reduce the energy by 20% and the emission rate of fume. As a result, under thesamewelding conditions,comparedwith thewelding by supplying pure argon, argon + 67% helium mixture by conventional method and thewelding by supplying alternately pure argon and pure helium by alternate method showed the increased welding speed. Also, the alternate method showed the same welding speed with argon + 67% helium mixture without largely deteriorating of weld penetration. The alternate method with argon and helium compared with the conventional methods of pure argon and argon + 67% helium mixture produced the lowest degree of welding distortion.

Characteristics of alternate supply of shielding gases in aluminum GMA welding

Recently, unlike conventional method in supplying shielding gas, a newly method which alternately supplies different kinds of shielding gases in weld zone is developed and partly commercialized. However, literature related to the present status of the technology in the actual weld field is very scant. To give better understand on this technology, this study was performed. Compared with conventional gas supply method, the variations of weld porosity and weld shape in aluminum welding with alternate supply method of pure argon and pure helium were compared with conventional gas supply method with pure argon and argon + 67%helium mixture, respectively. As a result, compared with the welding by supplying pure argon and argon + 67%helium mixture by conventional method, the welding by supplying alternately pure argon and pure helium, produced lower degree of weld porosity and deeper and broader weld penetration profile.

Development of diagnostic and prognostic algorithms for SF6 puffer circuit breakers from transient waveforms : a validation proposal

- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions.

Modelling the effects of bone fragment contact in fracture healing

The fracture healing process is modulated by the mechanical environment created by imposed loads and motion between the bone fragments. Contact between the fragments obviously results in a significantly different stress and strain environment to a uniform fracture gap containing only soft tissue (e.g. haematoma). The assumption of the latter in existing computational models of the healing process will hence exaggerate the inter-fragmentary strain in many clinically-relevant cases. To address this issue, we introduce the concept of a contact zone that represents a variable degree of contact between cortices by the relative proportions of bone and soft tissue present. This is introduced as an initial condition in a two-dimensional iterative finite element model of a healing tibial fracture, in which material properties are defined by the volume fractions of each tissue present. The algorithm governing the formation of cartilage and bone in the fracture callus uses fuzzy logic rules based on strain energy density resulting from axial compression. The model predicts that increasing the degree of initial bone contact reduces the amount of callus formed (periosteal callus thickness 3.1mm without contact, down to 0.5mm with 10% bone in contact zone). This is consistent with the greater effective stiffness in the contact zone and hence, a smaller inter-fragmentary strain. These results demonstrate that the contact zone strategy reasonably simulates the differences in the healing sequence resulting from the closeness of reduction.

Toward a fuzzy domain ontology extraction method for adaptive e-learning

With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.