With the rapid development of a two-dimensional (2D) nanomaterial, the confined liquid binary mixture has attracted increasing attention, which has significant potential in membrane separation. ...Alcohol/water is one of the most common systems in liquid–liquid separation. As one of the most focused systems, recent studies have found that ethanol molecules were preferentially adsorbed on the inner surface of the pore wall and formed an adsorbed ethanol layer under 2D nanoconfinement. To evaluate the effect of the alcohol adsorption layer on the mobility of water molecules, molecular simulations were performed to investigate four types of alcohol/water binary mixtures confined under a 20 Å graphene slit. Residence times of the water molecules covering the alcohol layer were in the order of methanol/water < ethanol/water < 1-propanol/water < 1-butanol/water. Detailed microstructural analysis of the hydrogen bonding (H-bond) network elucidated the underlying mechanism on the molecular scale in which a small average number of H-bonds between the preferentially adsorbed alcohol molecules and the surrounding water molecules could induce a small degree of damage to the H-bond network of the water molecules covering the alcohol layer, resulting in the long residence time of the water molecules.
The Group Sparse Representation (GSR) model shows excellent potential in various image restoration tasks. In this study, we propose a novel Multi-Scale Group Sparse Residual Constraint Model ...(MS-GSRC) which can be applied to various inverse problems, including denoising, inpainting, and compressed sensing (CS). Our new method involves the following three steps: (1) finding similar patches with an overlapping scheme for the input degraded image using a multi-scale strategy, (2) performing a group sparse coding on these patches with low-rank constraints to get an initial representation vector, and (3) under the Bayesian maximum a posteriori (MAP) restoration framework, we adopt an alternating minimization scheme to solve the corresponding equation and reconstruct the target image finally. Simulation experiments demonstrate that our proposed model outperforms in terms of both objective image quality and subjective visual quality compared to several state-of-the-art methods.
Biogas from anaerobic digestion (AD), as an important alternative to fossil fuels, has contributed to energy recovery and environmental sustainability. Incomplete or inefficient mixing within ...anaerobic reactors can result in poor biogas production or energy wastage. Thus, identifying mixing performance is meaningful for the digester design, operation and maximum biogas production. Over the years, various experimental and computational fluid dynamics (CFD) techniques have been developed to characterize the mixing performance of digesters. This review described the critical impact of mixing on biogas production in AD. Then, experimental techniques available on local and global scales were reviewed and compared in terms of their advantages, disadvantages, characterization capabilities and scope of application. Moreover, the implementation, reliability, indicators and application of CFD techniques in AD were thoroughly discussed. Based on the above discussion, mixing significantly affects AD methane production, and intermittent mixing is preferred for maximum biogas production. Local experimental techniques have been considered to be the simplest and cheapest for arbitrarily sized digesters; global experimental techniques relying on computer systems have received increasing attention for their applications in AD flow fields. More research efforts are needed to discover new experimental techniques that overcome the limitations of digestate opacity and industrial reactor geometries, in addition, compartmental models based on CFD to couple hydrodynamics with biokinetics are interesting and allow for greater implementation of CFD applications.
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In multi-label learning, scholars have proposed many multi-label learning algorithms that explore label-specific features in recent years. Previous studies tend to focus only on the forward ...projection of the instance feature space to the category label space to learn label-specific features for multi-label classification, and only simple correlations between labels are considered; however, the loss of discriminative information in the instance space and the essential connections between labels resulting from the reduction of feature dimensionality during forward projection are usually ignored. Based on the overall consideration, in this paper, we propose a bi-directional mapping for multi-label learning of label-specific features method(BDLS). Specifically, under a unified linear model for learning label-specific features for multi-label classification, we propose a novel reconstruction loss function to compensate for the loss of discriminative information generated during forward mapping. And we also propose an effective causal learning machine to explore the intrinsic causal relationships among labels for the purpose of mining the essential connections among labels. Experimental results and analysis on several multi-label datasets validate the effectiveness of our proposed method.
In this work, an ordered flower-like Cu2SnS3/reduced graphene oxide (CTS/RGO) hybrid materials was successfully synthesized via a facile and efficient hydrothermal route using thiourea as sulfur ...source and polyvinylpyrrolidone as chelating agent. The formation of CTS architectures and reduction of graphene oxide (GO) occur at the same time during the hydrothermal process. The flower-like CTS architectures were self-assembled by many nanosheets with an average thickness of 45 nm, and were wrapped in RGO nanosheets. The composite exhibited enhanced photocatalytic activities for the degradation of Rhodamine B (RhB) under visible light irradiation. The photodegradation rate of RhB in aqueous solutions (2 × 10−5) reached to 87% in 210 min, which presented higher activity than pure CTS. The factors influencing photocatalytic activity, the photostability and the possible mechanism for the improved performance of CTS/RGO hybrid materials were also discussed and proposed. The present study may provide a new approach to gain in-depth insight to the design a highly efficient photocatalyst with well-defined interface.
•An ordered CTS/RGO hybrid was prepared by using PVP as chelating agent.•The as-obtained CTS/RGO hybrid exhibits enhanced photocatalytic activity.•The factors influencing photocatalytic activity and possible mechanism are proposed.
The model-based signal decomposition algorithm is an important research direction in the field of digital signal processing, especially based on the amplitude modulation and frequency modulation ...(AMFM) model. In this paper, a signal decomposition algorithm based on multiple complex AMFM model is proposed to analyze multi-model data sets. Firstly, the analyzed signal is converted into the form of the analytic signal because of the simple representation of the AMFM model in the analytic domain. Then, the multi-model optimization equation of the analytic signal is realized by the estimated instantaneous frequency (IF) of each model, which can be estimated by time–frequency analysis (TFA). Finally, each model parameter of the optimization equation is solved by the partial differential equation and the alternating direction method of multipliers method (ADMM) to find the global optimal solution of the signal. In the optimization equation, we introduce the leakage factor to improve the extraction accuracy of the model; at the same time, we employ the cyclic iteration method to optimize the equation parameters to improve the convergence rate of the algorithm. Several examples of the simulated and real-life signals are provided to show that the proposed algorithm can accurately estimate the parameters of each model in the signal.
Bearing is an important part of rotary machinery, which usually operates under a variety of complicated and severe conditions, and is prone to break down. To reduce and prevent the loss caused by the ...fault of bearings, a method based on multi‐band filtering (MBF) is proposed and applied to bearing fault diagnosis in this paper. Bearing signal is decomposed into multiple sub‐band signals by an MBF constructed from a specific prototype filter (finite impulse response filter) through cosine modulation. Then, the required sub‐band can be selected adaptively according to bearing fault frequency. To make the fault frequency more prominent, an adaptive filtering method is exploited to reduce the noise contained in the selected sub‐band. Finally, bearing fault diagnosis is realized by envelope spectrum analysis. Experimental results show that better performance in both simulated and real data are achieved by the proposed algorithm, which indicates that the proposed method can realize bearing fault diagnosis efficiently when compared to other state of the art methods.
The increasing global population and urbanization have led to a pressing need for effective solutions to manage the organic fraction of municipal solid waste (OFMSW). High-solids anaerobic digestion ...(HS-AD) has garnered attention as a sustainable technology that offers reduced water demand and energy consumption, and an increased biogas production rate. However, challenges such as rheology complexities and slow mass transfer hinder its widespread application. To address these limitations, this review emphasizes the importance of process optimization and the mass transfer enhancement of HS-AD, and summarizes various strategies for enhancing mass transfer in the field of HS-AD for the OFMSW, including substrate pretreatments, mixing strategies, and the addition of biochar. Additionally, the incorporation of innovative reactor designs, substrate pretreatment, the use of advanced modeling and simulation techniques, and the novel conductive materials need to be investigated in future studies to promote a better coupling between mass transfer and methane production. This review provides support and guidance to promote HS-AD technology as a more viable solution for sustainable waste management and resource recovery.
Early bearing fault diagnosis can prevent from production accidents and improve safety, so it has an important practical engineering significance. In this paper, an intelligent condition monitoring ...of rolling bearing based on Hermitian scale-energy spectrum (HSES) and time-domain characteristics is presented. First, aiming to the difficulty of feature extraction for rolling bearing, the HSES of continuous wavelet transform is proposed to analyze the vibration signal from the viewpoint of energy distribution. In order to build robust features, the dimensionless parameters are also used to assist in extracting time-domain characteristics. Then, these characteristics of the time and wavelet domains are mapped into a low-dimensional feature space by using the principal components analysis, which can reduce the redundancy of the features. Within the acquired feature space, support vector machine is used to intelligently determine the existence of bearing failure and classify the type of fault. Moreover, in order to make the model automatically optimize parameters in different working conditions, a designed genetic algorithm is implemented in this paper. Experimental results show that the proposed method can not only accurately recognize fault pattern but also effectively realize the automation during the whole process.
In modern chemical engineering processes, the involvement of solid/fluid interface is the most important component of process intensification techniques, such as confined membrane separation and ...catalysis. In the review, we summarized the research progress of the latest theoretical and experimental works to elucidate the contribution of interface to the fluid properties and structures at nano- and micro-scale. We mainly focused on water, alcohol aqueous solution, and ionic liquids, because they are classical systems in interfacial science and/or widely involved in the industrialization process. Surface-induced fluids were observed in all reviewed systems and played a critical role in physicochemical properties and structures of outside fluid. It can even be regarded as a new interface, when the adsorption layer has a strong interaction with the solid surface. Finally, we proposed a perspective on scientific challenges in the modern chemical engineering processes and outlined future prospects.
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