Femtosecond laser micro-milling dental glass ceramics: An experimental analysis and COMSOL finite element simulation

Dental glass ceramic materials are widely used in all-ceramic restoration technology. In order to effectively solve the problems existing in the process of traditional diamond cutter milling dental glass ceramic materials, such as severe needle loss, large tool wear and general milling efficiency, a new method of ultrafast laser milling dental glass ceramics is proposed. In this paper, 1030 nm femtosecond laser with pulse width of 600fs was used to micro-mill dental glass ceramics. Confocal laser microscopy was used to measure the milling depth and surface roughness of single-layer milling under selected laser processing parameters. The pre-layered milling software was developed to control the z-axis lifting and to compensate the focal length synchronously. Scanning electron microscope (SEM), Raman spectrometer and Vickers micro-hardness tester were used to characterize the dental glass ceramics after femtosecond laser milling. The results showed that under the specific laser processing parameters, the infrared femtosecond laser milling system can achieve a good processing morphology without changing the surface composition and surface hardness of dental glass ceramics. This new dental glass ceramics processing method based on ultrafast laser technique indicated a new direction for further chair processing of dental all-ceramic restoration technology.     

Application of the cold sintering process to the electrolyte material BaCe0.8Zr0.1Y0.1O3-δ

This paper describes and discusses the application of the original sintering process named cold sintering to the electrolyte material BaCe_0.8Zr_0.1Y_0.1O_3-δ to enhance its densification at a temperature below that needed in a conventional sintering. This new technique enables the acceleration of the densification resulting in a more compacted microstructure with an unexpected high relative density of 83 % at only 180 °C. A subsequent annealing at 1200 °C further enhances the densification which reaches 94 %. The electrochemical performance of CSP sintered ceramics was investigated and optimized by varying different process parameters. The comparison with the conventional sintered material reveals an increase of the total conductivity by mostly increasing the grain boundary one. This result emphasizes the benefits of CSP to not only reduce the sintering temperature but also to enhance the electrochemical properties.     

Quantitative analysis of semiconductor supply chain contracts with order flexibility under demand uncertainty: A case study

The evidence base for the configuration of rolling horizon flexibility (RHF) contracts (a type of quantity flexibility contract) used in the semiconductor industry to coordinate production and demand remains meagre, more art than science. Informed by the characteristics of actual clauses and demand behaviors drawn from a company’s experience, a discrete-event simulation model is developed to represent the company’s supply chain. It comprises of three parties: a customer, a supplier (semiconductor manufacturer), and a capacity provider. Through analysis of customer forecasted demand the paper characterizes forecast demand as being under, over or unbiased. Models of these forecasted demands drives both long and short term planning. In long term planning, which is given twelve months before an order is delivered, capacity at the capacity provider is booked. Short term planning is also driven by this forecast which, within a binding period, is governed by an RHF contract. Results from the model report inventory levels, and delivery compliance, namely Delivery Performance (DP) and Delivery Reliability (DR), measures widely used in this sector. It is concluded from this work that on the balance of performance measures RHF contracts with asymmetrical flexibility bounds are substantially better than those with symmetrical boundaries, and that this conclusion is robust with regard to both over-planning and under-planning behaviors. This robustness is a critical attribute with respect to the endemic medium-term vacillation between both states experienced in practice in this sector.     

Understanding structure and porosity of nanodiamond-derived carbon onions

Carbon onions derived by thermal annealing of nanodiamonds are an intriguing material for various applications that capitalize the nanoscopic size, high electrical conductivity, or moderately high external surface area. Yet, the impact on synthesis conditions and possible post-synthesis treatment on the pore characteristics lacks a detailed parametric understanding. We present a comprehensive model describing the change of structure, morphology, specific surface area (SSA), and pore size distribution (PSD) of carbon onions derived via thermal annealing of nanodiamonds as a function of synthesis parameters and the effect of physical activation in air. Different heating rates, temperatures, holding times, as well as two different nanodiamond precursors were used. During thermal annealing the increase in SSA occurs along with a loss of surface functional groups and volatile impurities. The sp³-to-sp² conversion results in a much lower density and an increase in SSA of up to ∼160%. At high temperatures, a sintering and carbon redistribution process limits the increase in SSA and leading to the formation of micrometer-sized graphitic particles with a very low SSA. Oxidation in air is a facile way for the effective removal of predominately amorphous carbon between carbon onion particles and the removal of outer carbon shells.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Crystallization and spectroscopic properties in Er3+ doped oxyfluorogermanate glass ceramics containing Na

The Er³⁺ doped oxyfluorogermanate glasses, with a composition containing Na element, were synthesized by the conventional melting–quenching technique. When Na element was introduced into the composition of oxyfluorogermanate glass, the crystals behavior was investigated in details. Depending on the annealing procedure supplied, thermal annealing of precursor glasses in the system GeO₂/BaF₂/AlF₃/Na₂O/NaF/ZnO/GdF₃/ErF₃ led to the precipitation of different crystal phase nanocrystals. It was confirmed the nanocrystals in GC600 is orthorhombic NaBaAlF₆ which led to enhance obviously in the UC luminescence of Er³⁺. However, the nanocrystals in G585 led to decrease in the UC luminescence, which indicated few Er ions enter into the lattice of this nanocrystal phase. The reason of the decrease in UC emission intensity of GC585 was analyzed.     

校企合作动车组结构与原理实训平台开发

为了培养适合动车组生产企业需要的高素质技术技能人才,校企合作开发了实物和软件相结合的动车组结构与原理实训平台,把动车组的安装、调试、运行和维护作业现场还原,用于满足动车组技术专业课程的教学,让学生在"做中学",达到企业与高职院校的双赢。