Selective catalytic hydrogenation has wide applications in both petrochemical and fine chemical industries, however, it remains challenging when two or multiple functional groups coexist in the ...substrate. To tackle this challenge, the “active site isolation” strategy has been proved effective, and various approaches to the site isolation have been developed. In this review, we have summarized these approaches, including adsorption/grafting of N/S-containing organic molecules on the metal surface, partial covering of active metal surface by metal oxides either via doping or through strong metal–support interaction, confinement of active metal nanoparticles in micro- or mesopores of the supports, formation of bimetallic alloys or intermetallics or core@shell structures with a relatively inert metal (IB and IIB) or nonmetal element (B, C, S, etc.), and construction of single-atom catalysts on reducible oxides or inert metals. Both advantages and disadvantages of each approach toward the site isolation have been discussed for three types of chemoselective hydrogenation reactions, including alkynes/dienes to monoenes, α,β-unsaturated aldehydes/ketones to the unsaturated alcohols, and substituted nitroarenes to the corresponding anilines. The key factors affecting the catalytic activity/selectivity, in particular, the geometric and electronic structure of the active sites, are discussed with the aim to extract fundamental principles for the development of efficient and selective catalysts in hydrogenation as well as other transformations.
•Sludge enhanced dewatering technologies are comprehensively reviewed.•Mechanisms of different sludge enhanced dewatering technologies are discussed.•Process adaptability of different sludge ...conditioning methods are analysed.•Sludge electro-dewatering and its coupled processes are discussed.•Sludge enhanced dewatering technology and its coupled processes are prospected.
Sludge is an inevitable by product of sewage treatment, and it includes pathogens, heavy metals, organic pollutants and other toxic substances. The components of sludge are complex and variable with extracellular polymeric substances (EPS) being one. EPS are highly hydrophilic and compressible, and make sludge dewatering difficult. Therefore, the development of efficient sludge-dewatering technology is an important means of mitigating rapid sludge growth. At present, the main methods used for sludge deep-dewatering technology are chemical preconditioning with high-pressure filtration and electrical mechanical dewatering. The selection of chemical preconditioning directly determines the final efficiency of the sludge-dewatering process. In this paper, we conduct a comprehensive review of the problems related to sludge dewatering and systematically summarise the impact of different chemical conditioning technologies on the efficiency of sludge dewatering. Furthermore, the characteristics of different enhanced dewatering technologies are evaluated and analysed for their adaptability and final disposal methods. We believe that this review can clarify the chemical conditioner mechanism to improve sludge dewatering, provide reference debugging information for the sludge-dewatering process and promote the development of efficient and environmentally friendly sludge-dewatering technology.
Fog is an emergent architecture for computing, storage, control, and networking that distributes these services closer to end users along the cloud-to-things continuum. It covers both mobile and ...wireline scenarios, traverses across hardware and software, resides on network edge but also over access networks and among end users, and includes both data plane and control plane. As an architecture, it supports a growing variety of applications, including those in the Internet of Things (IoT), fifth-generation (5G) wireless systems, and embedded artificial intelligence (AI). This survey paper summarizes the opportunities and challenges of fog, focusing primarily in the networking context of IoT.
MOFs have a highly ordered self‐assembled nanostructure, high surface area, nanoporosity with tunable size and shape, reliable host–guest interactions, and responsiveness to physical and chemical ...stimuli which can be exploited to address critical issues in sensor applications. On the one hand, the nanoscale pore size of MOFs ranging from less than 1 nm to ≈ 10 nm not only allows the diffusion of small molecules into the pores or through the MOF layer, but also excludes other larger molecules depending on the size, shape, and conformation of MOFs. On the other hand, MOFs with flexible structure exhibit a dynamic response to external stimuli, including guest molecules, temperature, pressure, pH, and light. Due to the unsaturated coordination metal sites and active functional groups, the interaction between certain analytes and active sites results in high selectivity. In this review, we summarize the latest studies on MOF‐based electronic sensors in terms of the function of MOFs, discuss challenges, and suggest perspectives.
Metal–organic frameworks (MOFs) that respond to physical and chemical stimuli are promising materials for electronic sensors owing to their outstanding sensing performance. In this Review, the functionality of MOFs as a mass‐loaded layer, filtration layer, electronic function layer, and optically sensitive layer is discussed.
The discovery of graphene one decade ago has triggered enormous interest in developing two-dimensional materials (2DMs)that is 2D allotropes of various elements or compounds (consisting of two or ...more covalently bonded elements) or molecular frameworks with periodic structures. At present, various synthesis strategies have been exploited to produce 2DMs, such as top-down exfoliation and bottom-up chemical vapor deposition and solution synthesis methods. In this review article, we will highlight the interfacial roles toward the controlled synthesis of inorganic and organic 2DMs with varied structural features. We will summarize the state-of-the-art progress on interfacial synthesis strategies and address their advancements in the structural, morphological, and crystalline control by the direction of the arrangement of the molecules or precursors at a confined 2D space. First, we will provide an overview of the interfaces and introduce their advantages and uniqueness for the synthesis of 2DMs, followed by a brief classification of inorganic and organic 2DMs achieved by interfacial synthesis. Next, the currently developed interfacial synthesis strategies combined with representative inorganic and organic 2DMs are summarized, including the description of method details, the corresponding structural features, and the insights into the advantages and limitations of the synthesis methods, along with some recommendable characterization methods for understanding the interfacial assembly of the precursors and crystal growth of 2DMs. After that, we will discuss several classes of emerging organic 2DMs with particular emphasis on the structural control by the interfacial synthesis strategies. Note that, inorganic 2DMs will not be categorized separately due to the fact that a number of review articles have covered the synthesis, structure, processing, and applications. Finally, the challenges and perspectives are provided regarding the future development of interface-assisted synthesis of 2DMs with diverse structural and functional control.
Presently, various high end systems have been utilized to check the instantaneous change in the climate through deep monitoring methods with advanced mathematical modelling, whereas the major problem ...in the present research is the data management and precision in detecting various disaster conditions of the smart environment. Though The present instrument for disaster prediction has come up with various satellites and radar, which suffers instrumentation and data management issues that has been resolved in this research. The prominent improvement in the IoT technology shows better fine-grain structure, more flexibility and accuracy. The Proposed technique uses Advanced Adaptive Wavelet Sampling Algorithm (AAWSA)that has been designed and developed in this paper helps to improve the precision range of the instrument during disaster prediction in the urban region. The developed instrument utilizes advanced mathematical modelling with the linear data analytics approach which shows emerging outcomes than the present system which are used in practice.
Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have ...proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber-physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance.
Privacy-preserving distributed machine learning becomes increasingly important due to the recent rapid growth of data. This paper focuses on a class of regularized empirical risk minimization machine ...learning problems, and develops two methods to provide differential privacy to distributed learning algorithms over a network. We first decentralize the learning algorithm using the alternating direction method of multipliers, and propose the methods of dual variable perturbation and primal variable perturbation to provide dynamic differential privacy. The two mechanisms lead to algorithms that can provide privacy guarantees under mild conditions of the convexity and differentiability of the loss function and the regularizer. We study the performance of the algorithms, and show that the dual variable perturbation outperforms its primal counterpart. To design an optimal privacy mechanism, we analyze the fundamental tradeoff between privacy and accuracy, and provide guidelines to choose privacy parameters. Numerical experiments using customer information database are performed to corroborate the results on privacy and utility tradeoffs and design.
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