Current trends in structural development and modification strategies for metal-organic frameworks (MOFs) towards photocatalytic H2 production: A review

Photocatalytic H₂ generation using semiconductor photocatalysts is considered as a cost-effective and eco-friendly technology for solar to energy conversion; however, the present photocatalysts have been recognized to depict low efficiency. Currently, porous coordination polymers known as metal-organic frameworks (MOFs) constituting flexible and modifiable porous structure and having excess active sites are considered to be appropriate for photocatalytic H₂ production. This review highlights current progress in structural development of MOF materials along with modification strategies for enhanced photoactivity. Initially, the review discusses the photocatalytic H₂ production mechanism with the concepts of thermodynamics and mass transfer with particular focus on MOFs. Elaboration of the structural categories of MOFs into Type I, Type II, Type III and classification of MOFs for H₂ generation into transition metal based, post-transition metal based, noble-metal based and hetero-metal based has been systematically discussed. The review also critically deliberate various modification approaches of band engineering, improvement of charge separation, efficient irradiation utilization and overall efficiency of MOFs including metal modification, heterojunction formation, Z-scheme formation, by introducing electron mediator, and dye based composites. Also, the MOF synthesized derivatives for photocatalytic H₂ generation are elaborated. Finally, future perspectives of MOFs for H₂ generation and approaches for efficiency improvement have been suggested.     

Hybrid wideband transceiver design for achievable rate maximization in millimeter-wave MIMO systems

Telecommunication Systems - This paper proposes two algorithms for hybrid (Analog–Digital) beamforming in a single-user millimeter-wave (mm-wave) multi-input multi-output (MIMO) systems under...     

ACTNET: End-to-End Learning of Feature Activations and Multi-stream Aggregation for Effective Instance Image Retrieval

International Journal of Computer Vision - We propose a novel CNN architecture called ACTNET for robust instance image retrieval from large-scale datasets. Our key innovation is a learnable...     

Prediction of the maximum spoutable height in spout-fluid beds

The development of the semi-theoretical correlation in Hadzisdmajlovic et al. (1983) for predicting the maximum spoutable height in a spout-fluid bed, is observed to involve certain discrepancies. Based on their experimental data, a new correlation is proposed.     

Hydrogen limitation--a method for controlling the performance of membrane biofilm reactor for autotrophic denitrification of wastewater.

Hydrogen-driven denitrification using the fiber membrane biofilm reactor (MBfR) was evaluated for consistent operation in tertiary wastewater treatment. The possibility of controlling the process rates, as well as biofilm parameters by supplying limited amounts of electron donor (hydrogen), was tested. Limiting the hydrogen supply proved to be efficient in controlling the biofilm growth and performance of the MBfR. Denitrification rates remained unchanged for both synthetic wastewater (SWW) and real municipal wastewater (MWW) effluent as well through the fluctuations in the substrate (NO3-N) concentration. The average denitrification rates were 0.50 (+/- 0.02) g NO3-N per day per m2 for SWW and 0.59 (+/- 0.04) g NO3-N per day per m2 for MWW. Biofilm density rather than thickness was the determining factor in substrate diffusion and biofilm sloughing, ultimately determining operating stability. Limited hydrogen supply assured constant volatile solids (VS) concentration in the biofilm. It was determined that VS/TS ratio higher than 0.25 assured stable biofilm operation. Decrease of VS/TS ratio below 0.25 led to shearing of the nonbiological outer layers of the biofilm. The values of chemical oxygen demand (COD), volatile suspended solids (VSS) and total suspended solids (TSS) in the final effluent were stable and well below wastewater effluent guidelines. Substitutions of bicarbonate with gaseous carbon dioxide as the carbon source did not affect denitrification rates despite lower than optimum pH conditions.     

Qualitative response of safety injection system for a large size break in the reactor coolant system cold leg

Safety injection system, accumulator injection system and residual heat removal system of CHASNUPP-1 were simulated using the computer code APROS. We observed the qualitative response of the simulated system during injection and re-circulation phases after LOCA. During rapid depressurization of SRC system due to leakage, these systems started coolant injection in the SRC system as per plant requirement. Different thermal-hydraulic parameters of the respective systems are presented and discussed. Results obtained are in good agreement with the reported document of the reference power plant.     

GA-SVR: a novel hybrid data-driven model to simulate vertical load capacity of driven piles

Piles are widely applied to substructures of various infrastructural buildings. Soil has a complex nature; thus, a variety of empirical models have been proposed for the prediction of the bearing capacity of piles. The aim of this study is to propose a novel artificial intelligent approach to predict vertical load capacity of driven piles in cohesionless soils using support vector regression (SVR) optimized by genetic algorithm (GA). To the best of our knowledge, no research has been developed the GA-SVR model to predict vertical load capacity of driven piles in different timescales as of yet, and the novelty of this study is to develop a new hybrid intelligent approach in this field. To investigate the efficacy of GA-SVR model, two other models, i.e., SVR and linear regression models, are also used for a comparative study. According to the obtained results, GA-SVR model clearly outperformed the SVR and linear regression models by achieving less root mean square error (RMSE) and higher coefficient of determination (R²). In other words, GA-SVR with RMSE of 0.017 and R² of 0.980 has higher performance than SVR with RMSE of 0.035 and R² of 0.912, and linear regression model with RMSE of 0.079 and R² of 0.625.

     

Applying dual-tree complex discrete wavelet transform and gamma modulating function for simulation of ground motions

The aim of this paper is to develop a stochastic-parametric model for the generation of synthetic ground motions (GMs) which are in accordance with a real GM. In the proposed model, the dual-tree complex discrete wavelet transform (DT-CDWT) is applied to real GMs to decompose them into several frequency bands. Then, the gamma modulating function (GMF) is used to simulate the wavelet coefficients of each level. Consequently, synthetic wavelet coefficients are generated using extracted model parameters and then synthetic GM is extracted by applying the inverse DT-CDWT to synthetic wavelet coefficients. This model simulates the time–frequency distribution of both wide-frequency and narrow-frequency bandwidth GMs. Besides being less time consuming, it simulates several dominant frequency peaks at any moment in the time duration of GM, because each frequency band is separately simulated by the gamma function. Moreover, the inelastic response spectra of synthetic GMs generated by the proposed model are a good estimate of target ones. Using the random sign generator in the proposed model, it is possible to generate any number of synthetic GMs in accordance with a recorded one. Because of these advantages, the proposed model is suitable for using in performance-based earthquake engineering.

     

A review on fault detection and diagnosis techniques: basics and beyond

Safety and reliability are absolutely important for modern sophisticated systems and technologies. Therefore, malfunction monitoring capabilities are instilled in the system for detection of the incipient faults and anticipation of their impact on the future behavior of the system using fault diagnosis techniques. In particular, state-of-the-art applications rely on the quick and efficient treatment of malfunctions within the equipment/system, resulting in increased production and reduced downtimes. This paper presents developments within Fault Detection and Diagnosis (FDD) methods and reviews of research work in this area. The review presents both traditional model-based and relatively new signal processing-based FDD approaches, with a special consideration paid to artificial intelligence-based FDD methods. Typical steps involved in the design and development of automatic FDD system, including system knowledge representation, data-acquisition and signal processing, fault classification, and maintenance related decision actions, are systematically presented to outline the present status of FDD. Future research trends, challenges and prospective solutions are also highlighted.

     

Grain boundary embrittlement in Cu-AI-Niβ-phase alloys

The grain boundary embrittlement in Cu-AI-Ni-phase alloys has been investigated. The study included both the bulk alloys and rapidly solidified ribbons. It was observed that the fracture characteristics and the phase transformations in rapidly solidified ribbons were similar to those in the bulk alloys. Various factors responsible for intergranular fracture were considered. It was found that intrinsic or extrinsic precipitates at the grain boundaries are not responsible for the embrittlement. It was further observed that the segregation of impurities does not occur at the grain boundaries and hence is not a factor contributing to the embrittlement. The intrinsic characteristics, however, appear to play an important role. These may include high elastic anisotropy, ordered structure and plastic incompatibility. Severe embrittlement in high-nickel alloys is associated with spinodal decomposition occurring in these alloys. The large grain size exhibited by these alloys is found not to be a significant factor contributing to the embrittlement.