Tunable permittivity in polymer composites filled with Si-based semiconductors by regulating induced polarization

Induced polarization shows a significant influence on dielectric permittivity of 0–3 polymer composites containing Si-based semi-conductive fillers. The nature of induced polarization is the increased electric conductivity or decreased band gap in Si-based semi-conductive fillers. In this work, the dependence of induced polarization onto particle size of α-SiC filler together with polarity of polymer matrix and Si-based semi-conductive filler has been elaborately investigated by detecting the permittivity of composites. It was found that increasing the grain size of SiC filler, improving the polarity of polymer matrix and reducing the band-gap of Si-based semi-conductive filler could favor the enhancement of the overall induced polarity in the composites. As a result, the significantly improved dielectric permittivity of composites higher than both of the neat polymer and filler was observed depending on the constituents of the composites. The highest dielectric permittivity of ~215@1 kHz was achieved in poly(vinyl alcohol) based composite filled with 60 vol% of 12 µm SiC particles. The dielectric permittivity of these 0–3 composites could be well tuned in a wide range through altering their constituents. This work might open a facile route to obtain the promising high-performance dielectric composite materials by regulating the degree of induced polarization.     

Coupled nanowire-based hybrid plasmonic nanocavities on thin substrates

We theoretically analyze nanowire-based hybrid plasmonic nanocavities on thin substrates at visible wavelengths. In the presence of thin suspended substrates, the hybrid plasmonic modes, formed by the coupling between a metal nanowire and a dielectric nanowire with optical gain, exhibit negligible substrate-mediated characteristics and overlap better with the gain region. Consequently, the confinement factor of the guided hybrid modes is enhanced by more than 42%. However, the presence of significant mirror loss remains the main challenge to lasing. By adding silver coatings with a sufficient thickness range on the two end facets, we show that the reflectivity is substantially enhanced to above 50%. For a coating thickness of 50 nm and cavity length of about 4 μm, the quality factor is above 100.     

立磨液压系统的自动化控制技术的研究

数字技术的数学基础——离散数学、逻辑数学等，早在17、18世纪就已经出现。但是发展成为数字技术并付诸实用，随着半导体器件、集成器件和超大规模集成器件的出现，数字技术在液压系统中的应用迅速而又普遍地发展起来。     

Promising methane gas sensor synthesized by microwave-assisted Co3O4 nanoparticles

The morphology and gas sensing characteristics of Co₃O₄ nanoparticles prepared using the microwave irradiation were investigated. XRD and TEM are used to analyze the structural and the morphological properties of the prepared nanoparticles. XRD results confirmed the formation of pure phase of these nanoparticles. The gas sensor based on the synthesis Co₃O₄ nanoparticles reveals faster response and recovery time at low temperature detection toward methane gas. Specifically, for methane concentration of 1%, the response and the recovery times at 200 °C are 100 s and 50 s, respectively. Furthermore, the sensing characteristics of Co₃O₄ nanoparticles were improved by increasing the operating temperatures and gas concentrations as well. The experimental results clearly demonstrate the potential use of Co₃O₄ nanoparticles as a sensing material in the fabrication of CH₄ sensors.     

Effects of annealing on nanocrystalline Bi2S3 thin films prepared by chemical bath deposition

Nanocrystalline Bi₂S₃ thin films are deposited on tin chloride treated glass substrate from the solution containing bismuth nitrate, triethanolamine (TEA) and thioacetamide (TAM) at a bath temperature 318 K. The prepared films are subsequently annealed at different temperatures for studying the effect of thermal treatment on the structural, surface morphology, optical and electrical properties of the films. The X-ray diffraction studies affirmed that the deposited films are orthorhombic structures with average crystallites size of 14 nm to 28 nm. The scanning electron microscopy (SEM) images revealed that the films comprise of grains of spherical shape of unequal size. It is also observed that the small particles aggregate together to form a larger cluster. The average grain sizes determined from the TEM images are smaller than the crystallites size obtained from the XRD studies. The optical band gap of the films has been estimated to be 2.24–2.05 eV for the as-prepared and annealed films, respectively. The electrical conductivity of the as prepared Bi₂S₃ films at room temperature is found to be in the order of 10⁻³ Ω⁻¹ m⁻¹.     

Investigating the role of a Schiff-base ligand in the characteristics of TiO2 nano-particles: Particle size,optical properties,and photo-voltaic performance of dye-sensitised solar cells

A Schiff base ligand was employed to synthesise TiO₂ nano-particles by a two-step sol–gel method. The effect of the ligand on purity, particle size, optical properties and photo-voltaic performance of dye-sensitised solar cells was investigated. Various concentrations of the ligand were applied and each sample was characterised. Changing the ligand content had an effective role on the optical and photo-voltaic properties of the final product. The obtained products were characterised through powder X-ray diffraction, scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectra, energy-dispersive X-ray spectrometry and ultraviolet–visible spectroscopy.     

Knowledge augmented broad learning system for computer vision based mixed-type defect detection in semiconductor manufacturing

Defect detection is a critical measurement process for intelligent manufacturing systems to provide insights for product quality improvement. For complex products such as integrated circuit wafers, several types of defects are usually coupled in a piece of wafer to form a mixed-type defect, which poses a challenge to current defect detection methods. This paper proposed a knowledge augmented broad learning system with a knowledge module and broad selective sampling module, which provides a multichannel selective sampling network to decouple the mixed-type defects. In this model, each channel is equipped with a pre-trained deformable convolution model to extract the feature of a fixed single-type defect. The knowledge module is designed to activate the candidate network channel by pre-detection of wafer maps. The experiment results indicated that the proposed model outperforms conventional models and other deep learning models, which demonstrated that the knowledge augmented broad selective sampling mechanism is effective for mixed-type defect detection.     

Stochastic programming for qualification management of parallel machines in semiconductor manufacturing

This paper is concerned with the qualification management problem of parallel machines under high uncertainties in the semiconductor manufacturing industry. Product–machine qualification, or recipe–machine qualification, is a complicated, time-consuming process that is frequently encountered in semiconductor manufacturing. High uncertainty, a common aspect of the semiconductor manufacturing process, significantly enhances the complexity of this process. This paper mainly focuses on addressing such a complex scheduling problem by presenting a general two-stage stochastic programming formulation, which embeds uncertainty into the qualification management problem. The proposed model considers the capacity loss resulting from traditional random capacity factors, such as tool failures, and recipe–machine qualification, making it more applicable to real systems. To solve this problem, we propose a Lagrangian-relaxation-based surrogate subgradient approach. Numerical experiments indicate that this approach is capable of optimizing the problem in acceptable computation time. In addition, given that obtaining complete distribution information for random variables is unavailable in practice, a simplified approach is also developed to approximate the initial problem.     

Enhanced thermoelectric performance via randomly arranged nanopores: Excellent transport properties of YbZn2Sb2 nanoporous materials

Fabricating nanoporous bulk thermoelectric (TE) materials with periodically arranged nanopores is highly challenging and expensive, although TE materials exhibit high power factors (α²σ) and low thermal conductivities (κ). Enhanced TE performance via randomly arranged nanopores is demonstrated with a YbZn₂Sb₂ nanoporous material (nPM) fabricated by a combination of melt quenching and two stage spark plasma sintering in less than 10 h. Measurement of the electrical conductivity, Hall mobility, Seebeck coefficient, and thermal conductivity show that simultaneously enhancing α²σ and reducing κ can realize in the YbZn₂Sb₂ nPM with randomly arranged nanopores about 50-200 nm in diameter. Compared with YbZn₂Sb₂ dense bulk materials (dBM) fabricated by a conventional method taking more than 180 h, α²σ at 300 K increases by 122%, κ at 300 K decreases by 29%, and the maximum ZT value at 775 K reaches 0.67, increasing by 46% for the nPM725 sample. This work shows that a periodic arrangement of nanopores is not essential for the fabrication of attractive TE materials, which offers a wider approach to nanostructure engineering to improve TE performance.     

The implementation of an activity-based costing collaborative planning system for semiconductor backend production

While the market turns to an environment with low profit margins for semiconductor backend operations, it is hard for an independent firm to survive today. Forming strategic alliances or integrating an enterprise's internal firms by means of collaborative planning/operations to gain competitive advantage is inevitable. This paper presents the development of an activity-based costing collaborative production planning system (ABC/CPPS) to help production planners to estimate the manufacturing profit of semiconductor backend turnkey (combined IC assembly and testing) operational services at the early stage of order release to production line in a collaborative context. The estimation is under the real constraints of production resources. A predicate/transition net (Pr/Tr net) is used to simulate and implement the activity-based costing (ABC) model with the dynamic characteristics of a production line incorporated. A financial measure, profit, is used to supplement and indicate the consequence of the planning result and link the view to the enterprise's financial vision.