Modelling the removal of organic vehicle from ceramic or metal mouldings: The effect of gas permeation on the incidence of defects

A shrinking undegraded core and a porous outer layer result, if the organic vehicle used for shaping ceramic or metal powder mouldings recedes in the interparticle space of the moulded body during pyrolysis. In the present work, a numerical model has been used which simulates the undegraded shrinking core situation and quantifies degradation of the organic vehicle and the diffusion of the resulting products in solution in the organic phase during pyrolysis of a ceramic moulding. This model is extended to include gaseous mass transport in the porous outer layer for a moulding in the shape of an infinite cylinder. The effect of resistance to gaseous mass transport in the porous outer region on defects originating in inner regions was estimated. It is shown that the greatest obstruction to mass transport is diffusion of degradation products in solution in the organic phase. However, the permeability coefficient for gas transport in the outer region begins to affect the critical heating rate required for avoidance of defects only when it is less than 10^–15m².Nomenclature C Concentration,C=C (r, t), based on the total volume of ceramic suspension - d Effective molecular diameter of alphamethylstyrene - D Diffusion coefficient,D=D (C, T) - e Porosity of powder - E Activation energy for thermal degradation - h Remaining weight fraction of polymer - H_vap Enthalphy of vaporization - i Node number - I Pre-exponential constant in Equation 13 - j Time step - K _p Permeability coefficient - K ₀ Specific rate constant - m Mass of monomer displaced - M Mass of one alphamethylstyrene molecule - P Monomer vapour pressure - P _s Monomer vapour pressure at outer surface of the cylinder - P ₁ ⁰ Vapour pressure of monomer over its pure liquid - Q Rate of production of monomer, based on the total volume of ceramic suspension - r Radius of the cylinder - r _j Distance from central axis to the inner surface of the porous layer at time stepj - r ₀ Initial radius of the cylinder - R Universal gas constant - S ₀ Specific surface area of powder per unit solid volume - t Time - T Absolute temperature - T _c Temperature at maximum vapour pressure of monomer and atZ _c - V Volume of monomer - V _c Ceramic volume fraction - V _p Polymer volume fraction - w Mass of monomer stored in the porous annulus - Z Heating rate - Z _c Critical heating rate - ₁ Volume fraction of monomer in the polymer-monomer solution - Viscosity of the monomer vapour - _p Density of the polymer - Polymer-monomer interaction constant     

Single-Atom Metal Sites Anchored Hydrogen-Bonded Organic Frameworks for Superior “Two-In-One” Photocatalytic Reaction

Photoredox catalysis is a green solution for organics transformation and CO₂ conversion into valuable fuels, meeting the challenges of sustainable energy and environmental concerns. However, the regulation of single-atomic active sites in organic framework not only influences the photoredox performance, but also limits the understanding of the relationship for photocatalytic selective organic conversion with CO₂ valorization into one reaction system. As a prototype, different single-atomic metal (M) sites (M²⁺ = Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺, and Zn²⁺) in hydrogen-bonded organic frameworks (M-HOF) backbone with bridging structure of metal-nitrogen are constructed by a typical “two-in-one” strategy for superior photocatalytic C N coupling reactions integrated with CO₂ valorization. Remarkably, Zn-HOF achieves 100% conversion of benzylamine oxidative coupling reactions, 91% selectivity of N-benzylidenebenzylamine and CO₂ conversion in one photoredox cycle. From X-ray absorption fine structure analysis and density functional theory calculations, the superior photocatalytic performance is attributed to synergic effect of atomically dispersed metal sites and HOF host, decreasing the reaction energy barriers, enhancing CO₂ adsorption and forming benzylcarbamic acid intermediate to promote the redox recycle. This work not only affords the rational design strategy of single-atom active sites in functional HOF, but also facilitates the fundamental insights upon the mechanism of versatile photoredox coupling reaction systems.     

Ligand Design in Atomically Precise Copper Nanoclusters and Their Application in Electrocatalytic Reactions

Metal nanoclusters (MNCs) are compositionally well-defined and also structurally precise materials with unique molecule-like properties and discrete electronic energy levels. Atomically precise ligand-protected Cu nanoclusters (LP-CuNCs) are one category of typical MNCs that usually demonstrate unique geometric and electronic structures to serve as electrocatalysts. However, the synthesis, application, as well as structure-performance relationship of LP-CuNCs are not adequately studied. Significantly, the ligands are essential to the geometric structure, crystal structure, size, and electronic structure of LP-CuNCs, which determine their physiochemical properties and applications. In this review, significant progress in the ligand design of LP-CuNCs, and their application in electrocatalytic reactions is introduced. The general basics of ligand-protected MNCs (LP-MNCs) are first introduced and the functions of ligands are emphasized. Subsequently, a series of different ligands for LP-CuNCs including thiolates, phosphines, alkynyl, polymers, and biomolecules are highlighted. Thereafter, their applications in different electrocatalytic reactions are discussed. It is believed that this review will not only inspire the design and synthesis of novel LP-CuNCs, but also contribute to the extension of their applications in electrocatalytic reactions and the establishment of accurate structure-performance relationships.     

Privacy Preserving distributed smart grid system based on Hyperledger Fabric and Wireguard

Smart grid has drawn a lot of attention and investment in recent years, which not only helps the modern generation and distribution of traditional power but also highly widens the application of renewable energy sources. However, the main challenges in the application of smart grid are 1. the privacy preservation of users' information and 2. the trustful transmission channel among peers. In order to solve these problems, VPN and blockchain can be considered since they have some features perfectly suitable for these situations. In this paper, we propose a smart grid system based on WireGuard and Hyperledger Fabric to solve the problems mentioned above. And we also implement the whole system and give a view by web application. What's more, all the functionalities are displayed and tested, including building a smart device simulator, deploying data visualization and making some performance evaluations about transactions and WireGuard communication. Experiment results show that the introduction of WireGuard into network infrastructure does not cause too much loss of bandwidth and delay, but it ensures a certain degree of communication security. And Fabric provides the consistency and traceability of transactions in smart grid system.     

Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.     

Evaluation Model of Click Rate of Electronic Commerce Advertising Based on Fuzzy Genetic Algorithm

Mobile Networks and Applications - In order to improve the ability of quantitative evaluation of e-commerce advertising click rate, a model of e-commerce advertising click rate evaluation based on...     

Service placement strategy for joint network selection and resource scheduling in edge computing

The Journal of Supercomputing - In the edge computing, service placement refers to the process of installing service platforms, databases, and configuration files corresponding to computing tasks...     

A Survey on Long-Tailed Visual Recognition

The heavy reliance on data is one of the major reasons that currently limit the development of deep learning. Data quality directly dominates the effect of deep learning models, and the long-tailed distribution is one of the factors affecting data quality. The long-tailed phenomenon is prevalent due to the prevalence of power law in nature. In this case, the performance of deep learning models is often dominated by the head classes while the learning of the tail classes is severely underdeveloped. In order to learn adequately for all classes, many researchers have studied and preliminarily addressed the long-tailed problem. In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed studies. Specifically, we summarize these studies into ten categories from the perspective of representation learning, and outline the highlights and limitations of each category. Besides, we have studied four quantitative metrics for evaluating the imbalance, and suggest using the Gini coefficient to evaluate the long-tailedness of a dataset. Based on the Gini coefficient, we quantitatively study 20 widely-used and large-scale visual datasets proposed in the last decade, and find that the long-tailed phenomenon is widespread and has not been fully studied. Finally, we provide several future directions for the development of long-tailed learning to provide more ideas for readers.

     

The Effect of the Rotary Steerable Spindle Structure Parameters on the Characteristics of Cantilever Bearing

Journal of Failure Analysis and Prevention - In point-the-bit rotary steerable drilling system, the internal and outer diameter of the spindles and the fillet radius of the shaft shoulder have a...