Carbon-assisted growth and high visible-light optical reflectivity of amorphous silicon oxynitride nanowires

Large amounts of amorphous silicon oxynitride nanowires have been synthesized on silicon wafer through carbon-assisted vapor-solid growth avoiding the contamination from metallic catalysts. These nanowires have the length of up to 100 μm, with a diameter ranging from 50 to 150 nm. Around 3-nm-sized nanostructures are observed to be homogeneously distributed within a nanowire cross-section matrix. The unique configuration might determine the growth of ternary amorphous structure and its special splitting behavior. Optical properties of the nanowires have also been investigated. The obtained nanowires were attractive for their exceptional whiteness, perceived brightness, and optical brilliance. These nanowires display greatly enhanced reflection over the whole visible wavelength, with more than 80% of light reflected on most of the wavelength ranging from 400 to 700 nm and the lowest reflectivity exceeding 70%, exhibiting performance superior to that of the reported white beetle. Intense visible photoluminescence is also observed over a broad spectrum ranging from 320 to 500 nm with two shoulders centered at around 444 and 468 nm, respectively

Stiffness optimization of geometrically nonlinear structures and the level set based solution

Load-normalized strain energy increments between consecutive load steps are aggregated through the Kreisselmeier-Steinhauser (KS) function, and the KS function is proposed as a stiffness criterion of geometrically nonlinear structures. A topology optimization problem is defined to minimize the KS function together with the perimeter of structure and a volume constraint. The finite element analysis is done by remeshing, and artificial weak material is not used. The topology optimization problem is solved by using the level set method. Several numerical examples in two dimensions are provided. Other criteria of stiffness, i.e., the end compliance and the complementary work, are compared

Stiffness optimization of geometrically nonlinear structures and the level set based solution

Load-normalized strain energy increments between consecutive load steps are aggregated through the Kreisselmeier-Steinhauser (KS) function, and the KS function is proposed as a stiffness criterion of geometrically nonlinear structures. A topology optimization problem is defined to minimize the KS function together with the perimeter of structure and a volume constraint. The finite element analysis is done by remeshing, and artificial weak material is not used. The topology optimization problem is solved by using the level set method. Several numerical examples in two dimensions are provided. Other criteria of stiffness, i.e., the end compliance and the complementary work, are compared

Triple Recycling Channel Strategies for Remanufacturing of Construction Machinery in a Retailer-Dominated Closed-Loop Supply Chain

Firms engaged in remanufacturing activities generally adopt more than one recycling channel to collect more used products and gain more profits. This paper explores the optimal strategies for a retailer-dominated closed-loop supply chain (CLSC) with a triple recycling channel in the construction machinery remanufacturing context. In this special system, the retailer is the leader and authorized by the original equipment manufacturer (OEM) to remanufacture. Moreover, the OEM, the retailer, and the secondary market all take part in the used products collection activities. Considering the differentiation of the OEM, the retailer, and the secondary market in collecting the used construction machinery, a mathematical model of the CLSC system based on reasonable assumptions is built, the closed-form optimal pricing decisions are derived, and the optimal collection efforts allocation strategies are explored within the framework of the game theory. In addition, the impacts of the reverse logistics cost coefficient, the competing coefficient, and the buy-back price coefficient on the supply chain performance are elaborately analyzed. These achievements provide decision makers with managerial insights and offer efficient guidelines for the construction machinery remanufacturing firms to solve similar puzzles

A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks

Many efforts have been taken to train spiking neural networks (SNNs), but most of them still need improvements due to the discontinuous and non-differential characteristics of SNNs. While the mammalian brains solve these kinds of problems by integrating a series of biological plasticity learning rules. In this paper, we will focus on two biological plausible methodologies and try to solve these catastrophic training problems in SNNs. Firstly, the biological neural network will try to keep a balance between inputs and outputs on both the neuron and the network levels. Secondly, the biological synaptic weights will be passively updated by the changes of the membrane potentials of the neighbour-hood neurons, and the plasticity of synapses will not propagate back to other previous layers. With these biological inspirations, we propose Voltage-driven Plasticity-centric SNN (VPSNN), which includes four steps, namely: feed forward inference, unsupervised equilibrium state learning, supervised last layer learning and passively updating synaptic weights based on spike-timing dependent plasticity (STDP). Finally we get the accuracy of 98.52% on the hand-written digits classification task on MNIST. In addition, with the help of a visualization tool, we try to analyze the black box of SNN and get better understanding of what benefits have been acquired by the proposed method

Dynamic modeling and analysis of load sharing characteristics of wind turbine gearbox

A coupled dynamic model, which contains helical gears-shafts-bearings for a wind turbine gearbox transmission system, was built considering nonlinear factors of the time-varying mesh stiffness, the external varying load, and the dynamic transmission error at first. The model is confirmed to be right after comparing the theoretical data with the experimental load sharing values, and also it is found that the static load sharing is conservative to evaluate the non-equilibrium effect of a planetary gear system. Besides, the analyzing results of the influence of average error and amplitude error on the load sharing show that the load sharing could be decreased if the error goes up a little. Then, by means of treating the static tracing point as the dynamic initial values, we analyzed the initial position’s influence on the load sharing of transmission system to provide a theoretical basis of load sharing control. Furthermore, we explored the influence of high-speed shaft position angle on the load sharing and the dynamic load factor of gears fixed on the parallel shafts. The results provide useful theoretical guidelines for the design of parallel shaft gear system in the wind turbines

Experiment and modeling into drilling of micro-hole on TC4 by electrochemical jet machining

This paper studied the rule of micro-hole in electrochemical jet machining (EJM) of TC4 alloy and established the mathematical model of machining process and predicted the machining profile. Considering the influence of machining gap and machining time, orthogonal experiment was designed. This paper established the mathematical model of the electrochemical jet machining process of TC4 alloy based on the response surface analysis (RSA) method. The results indicate that the electrochemical jet can improve the directivity of machining, reducing the machining gap can improve the machining efficiency, but the jet will cause secondary corrosion and abrupt change of current at the edge of inlet. The mathematical model based on response surface analysis is accurate after variance test. The experimental results show that the average error between the established prediction model of machining depth and the actual value is 2.32%, and the average error of the prediction model of inlet radius is 2.18%