Desirable Performance Research Articles

Establishing an efficient membrane bioreactor for simultaneous pollutant removal and purple bacteria production under salinity stress

Recovering resources from wastewater to alleviate the energy crisis has become the prevailing trend of technological development. Purple phototrophic bacteria (PPB), a group of fast-growing microbes, have been widely noticed for their potential in producing value-added products from waste streams. However, saline contents in these waste streams, such as food processing wastewater pose a big challenge, which not only restrain the pollutant removal efficiency, but also hinder the growth of functional microbes. To overcome this, a photo anaerobic membrane bioreactor cultivating PPB (PPB-MBR) was constructed and its performance upon long-term salinity stress was investigated. PPB-MBR achieved desirable pollutants removal performance with the average COD and NH4+ removal efficiency being 87% (±8%, n = 87) and 89% (±10%, n = 87), respectively during long-term exposure to salinity stress of 1–80 g NaCl L−1. PPB were predominant during the entire operation period of 87 days (60%–80%), obtaining maximum biomass yield of 0.67 g biomass g−1 CODremoved and protein productivity of 0.18 g L−1 d−1 at the salinity level of 20 g NaCl L−1 and 60 g NaCl L−1, respectively. The sum of value-added products in proportion to the biomass reached 58% at maximum at the salinity level of 60 g NaCl L−1 with protein, pigments and trehalose contributing to 44%, 8.7%, and 5%, respectively. Based on economic analysis, the most cost-saving scenario treating food processing wastewater was revealed at salinity level of around 20 g NaCl L−1. However, more optimization tools are needed to boost the production efficiency so that the profit from value-added products can outweigh the additional cost by excess salinity in the future implication.

Ion and Water Transport in 2D Nanofluidic Channels

AbstractTwo‐dimensional (2D) lamellar membranes, featuring organized nanochannels, tunable interlayer spacing, and modifiable chemical properties, are emerging as promising candidates for both theoretical research and practical applications. Rational design and regulation of the physical/chemical properties of the nanofluidic channels as well as manipulation of external factors are crucial to achieve desirable performance for the applications related to mass transport. Focusing on the recent advances in ion and water transport within 2D nanofluidic channels, this work gives a brief overview of the fabrication of 2D lamellar membranes based on the strategy of exfoliation and reconstruction. Then the transport phenomena within 2D nanofluidic channels along with the mechanisms and influential factors are highlighted. The representative applications of 2D lamellar membranes are also covered, especially in the areas of osmotic energy conversion, water purification and desalination, as well as single‐ion separation and extraction. It is concluded with a discussion of the current challenges and future perspectives in this potential field.

Augmented Finite Control Set MPC Design Technique for Wide Speed Range Control of Permanent Magnet Synchronous Motor Drives

The effective motion control task is highly influencing the final drive performance in wide-range motor drives applications such as electric vehicles (EVs), washing machines, compressors, elevators and lathe machines. Recently, permanent magnet synchronous motor (PMSM) drive has been widely employed in these applications to achieve desired performances such as high efficiency, high torque requirements with minimum size “occupancy”. The PMSM drive features combining with these modern drive applications are highly nonlinear and the desired operation requirements demand high-performance control schemes with fast system response and robustness features. Linear control schemes are usually implemented to drive the PMSM that entail trade-offs between drive performance and simplicity in control implementation. Therefore, this paper presents the nonlinear control technique based on augmented finite control set (AFCS) model predictive control (MPC) scheme (AFCS-MPC). The proposed AFCS-MPC scheme enhances the standard MPC design by augmenting the nonlinear characteristics of the PMSM drive to achieve wide speed range drive performance under both steady-state and dynamic operating conditions. Comparative performance studies have been conducted and presented to confirm the efficacy of the proposed scheme.

Optimizing deployment dynamics of composite tape-spring hinges

The composite tape-spring hinge (CTSH) is a lightweight structural connector widely employed in space structures, including spacecraft and satellites, due to its high specific strength and stiffness. Introducing cutouts enables CTSH to possess folding and deployment capability, while optimizing the cutouts finely to optimize the performance of CTSH. However, the interaction between cutout size and the dynamic deployment of CTSH is a novel topic. To address this, a multi-objective optimization problem is formulated, aiming to minimize both the maximum overshoot angle and deployment time while considering mass constraints. An accelerated size optimization is achieved by integrating data-driven surrogate modeling and size optimization. The optimized CTSH design exhibits a significant improvement in performance, with a 26.3% reduction in the maximum overshoot angle and a 12.6% reduction in the deployment time compared to the initial design. The proposed optimization strategy is highly adaptable and can be applied to various optimization problems, offering valuable insights for future designing space deployable structures with desirable performance.

Turning self-trapped exciton emission via Sb3+ doping in zero-dimensional hybrid indium chloride for X-ray scintillation

Zero-dimensional (0D) hybrid indium halides have recently received great attention for their potential as X-ray scintillators due to their non-toxicity, superior optical properties and exceptional stability. However, most indium halides suffer from low emission efficiency, resulting in inferior performance. Herein, we demonstrate that a small amount of Sb3+ doping can greatly enhance the photoluminescence efficiency of a 0D hybrid indium chloride, DMA4InCl7. The pristine crystals exhibit weak self-trapped exciton (STE) emission centered at 620 nm with a low quantum yield of 11%. After Sb3+ doping, the STE emission efficiency can be greatly increased to 91%. The spectroscopic experiments and theoretical calculations indicate the efficient energy transfer from excited Sb3+ ions to the emitting STE state of the host is responsible for the substantial increase in emission efficiency. Furthermore, we find the energy transfer efficiency is related to the distance between dopants and [InCl6]3- units. The strong STE emission endows the doped samples with desirable X-ray scintillation performance, with a high light yield of 23500 photons/MeV and a low detection limit of 175 nGyair·s−1.

Desirable performance and mechanism of RuPd nanoalloys in catalyzing hydrolytic dehydrogenation of NH3BH3

The dehydrogenation of liquid-phase chemical hydrogen storage materials (such as ammonia borane, AB, NH3BH3) is a promising strategy to develop the promising hydrogen economy. Considering that the self-hydrolysis of AB is nearly impossible at room temperature, it is very worthwhile to search a robust catalyst for this hydrolytic reaction and clarify the catalytic mechanism. In this work, a glucose-derived N/O co-doped and multi-level porous carbon (marked as g-pC, SBET = 1356 m2 g−1, Vtotal = 0.762 cm3 g−1, Smicro = 1079 m2 g−1, Vmicro = 0.427 cm3 g−1) is prepared for confining RuPd alloys. Benefitting from the positive effect of g-pC (such as the particular anchoring and geometric effects on highly and tightly confining RuPd nanoparticles, as well as enhanced hydrophilicity) and the exceptional metal alloy effect, the obtained bimetallic catalysts unveil drastically enhanced catalytic activity in AB hydrolysis compared to the monometallic counterparts. Especially, catalyzed by the optimal Ru0.25Pd0.75@g-pC with a mean alloy size of 1.5 nm (10 mg), the dehydrogenation of 1.00 mmol AB can be finished within 1 min at 303 K in NaOH solution (1.5 M). The corresponding turnover frequency and hydrogen generation rate are calculated to be 541.09 min−1 and 145,950 mL min−1 g−1, respectively. Moreover, about 62% of the initial catalytic activity is still retained even in the 18th cyclic experiment, suggesting the extraordinarily long durability. In addition, the isotopic analyses present a kinetic isotope effect (KIE) of 3.38, further confirming that the scission of an O-H bond in H2O is the rate-controlling step in this hydrolytic reaction. Our work offers a competitive metal alloy catalyst for generating hydrogen from AB aqueous solution and promote the development and safety utilization of hydrogen energy.

V2O5·3H2O/N-doped graphite felt cathode efficiently produced H2O2 and ·OH in the electro-Fenton system for enhanced antibiotics degradation

Enhancing H2O2 production and promoting the conversion of H2O2 to ·OH are two major problems that needed to be solved in electro-Fenton process. Herein, the V2O5·3H2O/N-doped graphite felt (V2O5·3 H2O/N-GF) cathode was developed to construct electro-Fenton system for antibiotics degradation. Benefiting from that the N-GF which possessed a large number of 2e-ORR active sites for H2O2 production, and the V2O5·3H2O particles could efficiently activate H2O2 to produce ·OH, the V2O5·3 H2O/N1-GF cathode exhibited outstanding catalytic activity. Besides, the V2O5·3 H2O/N1-GF cathode exhibited only 30 mV overpotential difference between the optimal oxygen reduction potential (OP ORR) and the optimal vanadium reduction potential (OP VRR), thereby facilitating ·OH generation. The V2O5·3 H2O/N1-GF cathode displayed desired degradation performance in a wide pH range (2.1–7.2), with TC removal of 93.8% within 60 min at pH of 3.3, and total organic carbon (TOC) removal of 62.8%. DFT calculations revealed that V2O5·3H2O were more readily to adsorb H2O2 than V2O5, which was conducive to improving H2O2 utilization and conversion. Four possible degradation pathways for TC were proposed and toxicity analysis of the intermediates were determined. The V2O5·3H2O/N1-GF could also decompose various antibiotics effectively in the system, and it exhibited great stability. This work can provide reference for designing efficient V-based cathode for electro-Fenton system.

Statistical Depth in Spatial Point Process

Statistical depth is widely used as a powerful tool to measure the center-outward rank of multivariate and functional data. Recent studies have introduced the notion of depth to the temporal point process, which exhibits randomness in the cardinality as well as distribution in the observed events. The proposed methods can well capture the rank of a point process in a given time interval, where a critical step is to measure the rank by using inter-arrival events. In this paper, we propose to extend the depth concept to multivariate spatial point process. In this case, the observed process is in a multi-dimensional location and there are no conventional inter-arrival events in the temporal process. We adopt the newly developed depth in metric space by defining two different metrics, namely the penalized metric and the smoothing metric, to fully explore the depth in the spatial point process. The mathematical properties and the large sample theory, as well as depth-based hypothesis testings, are thoroughly discussed. We then use several simulations to illustrate the effectiveness of the proposed depth method. Finally, we apply the new method in a real-world dataset and obtain desirable ranking performance.

Cobalt nanoparticles supported on nitrogen-doped carbon nanotubes for the efficient oxygen reduction reaction in Mg-air battery

Fabricating the non-precious-metal catalyst with desirable catalytic performance towards oxygen reduction reaction (ORR) is essential for Mg-air battery that adopts neutral brine electrolyte. However, the classic metal-nitrogen-carbon materials with strong ORR catalytic activity in alkaline solution usually display inferior performance than platinum-based catalysts in neutral environment. Herein, we construct a hybrid catalyst composed of cobalt nanoparticles and nitrogen-doped carbon nanotubes, based on pyrolyzing the mixture of melamine, pyrazole, hexadecyl trimethyl ammonium bromide, and 2-methylimidazole chelated with Co2+ and Zn2+ ions. This catalyst possesses abundant ORR catalytic active sites and mesoporous structure with large pore volume, which can result in the superior performance of Mg-air battery than that using Pt/C catalyst. Furthermore, its ORR catalytic mechanism is unraveled according to microstructure characterization and electrochemical response.

Machine-learning-based wind farm optimization through layout design and yaw control

The high power extraction of wind farms necessitates a comprehensive optimization system encompassing precise and efficient layout design and cooperative control. This study applies a novel ANN-based power prediction framework to resolve the layout optimization combined with the genetic algorithm, then composes a double-layer machine learning framework for the control optimization incorporating Bayesian machine learning. Three wind scenarios and control schemes are accounted for to investigate their impacts on the actual power benefits of the layout and control optimizations, respectively. The study shows that the divergence of wind resources will lead to more evenly scattered turbine arrangements for each direction sector in the optimized layout but may weaken the functionality of layout design in annual power rise owing to the compromise between different wind directions. Under the spread wind scenario, the spread optimized layout may narrow the space for the power enhancement of the yaw control, whereas the unidirectional optimized layout may give rise to a more considerable power gain from the yaw control. Row-based control shows desirable performance in the regular aligned layout, while column-based control is recommended for irregularly optimized layouts, particularly for unidirectional optimized ones. The spread optimized layout will widen the gap of power improvement between the column-based and independent controls, thus weakening the advantage of the column-based control.

Integration of Multiple Distributed Generation Sources in Radial Distribution System Using a Hybrid Evolutionary Programming-Firefly Algorithm

This paper presents an approach for the optimal integration of multiple distributed generation (DG) sources in a radial distribution system. The integration of DG sources poses various challenges such as can lead to higher power losses caused by reverse power flow, voltage exceeding secure limits, voltage stability, power quality, and economic operation. To address these challenges, a hybrid algorithm is proposed which combines the benefits of both Evolutionary Programming and Firefly Algorithm. The proposed hybrid Evolutionary - Firefly Algorithm is employed for the determination of the optimal size of the DG sources. The objective of the proposed algorithm is to minimize the total system power losses and improve the voltage profile. The algorithm considers various constraints including the DG capacity limits and voltage limits. A comprehensive case study is conducted on a radial distribution system to demonstrate the effectiveness of the proposed approach. The simulation results show that the hybrid algorithm can find the optimal size and location of DG sources while achieving the desired system performance. The integration of multiple DG sources leads to a significant reduction in power losses and improved voltage profile. Furthermore, the proposed approach provides a flexible framework for the optimal integration of DG sources in radial distribution systems, allowing for the accommodation of different types and capacities of DG sources. The proposed technique is tested on the IEEE Reliability Test systems, specifically the IEEE 69-bus. The combination of DG at bus 61 and bus 27 yields a loss reduction index of 94%.

Unraveling the interplay of DNAzyme and interfacial factors for enhanced biosensing

Deoxyribozyme (DNAzyme) and its substrate hybridization are crucial for achieving desirable detection performance in the DNAzyme coupling nanomaterial biosensor system. However, interfacial factors such as electrostatic repulsion, steric hindrance, and nonspecific adsorption from gold nanoparticles make this hybridization process complicated and challenging. Moreover, the DNAzyme structure changes with different application purposes, which might affect the DNAzyme and substrate's connection. Few studies have focused on the interplay of DNAzyme and interfacial factors in the biosensor field. In this work, three types of DNAzyme variants were designed, and their biosensor performance rules were studied and summarized with the synergistic effect of interfacial factors. Additionally, corresponding biosensor applications, such as multiple modulation functions and miRNA detections, were constructed based on the distinct principles of DNAzyme variants.

Advances in Liquid Crystal Epoxy: Molecular Structures, Thermal Conductivity, and Promising Applications in Thermal Management

Traditional heat conductive epoxy composites often fall short in meeting the escalating heat dissipation demands of large‐power, high‐frequency, and high‐voltage insulating packaging applications, due to the challenge of achieving high thermal conductivity (k), desirable dielectric performance, and robust thermomechanical properties simultaneously. Liquid crystal epoxy (LCE) emerges as a unique epoxy, exhibiting inherently high k achieved through the self‐assembly of mesogenic units into ordered structures. This characteristic enables liquid crystal epoxy to retain all the beneficial physical properties of pristine epoxy, while demonstrating a prominently enhanced k. As such, liquid crystal epoxy materials represent a promising solution for thermal management, with potential to tackle the critical issues and technical bottlenecks impeding the increasing miniaturization of microelectronic devices and electrical equipment. This article provides a comprehensive review on recent advances in liquid crystal epoxy, emphasizing the correlation between liquid crystal epoxy's microscopic arrangement, organized mesoscopic domain, k, and relevant physical properties. The impacts of LC units and curing agents on the development of ordered structure are discussed, alongside the consequent effects on the k, dielectric, thermal, and other properties. External processing factors such as temperature and pressure and their influence on the formation and organization of structured domains are also evaluated. Finally, potential applications that could benefit from the emergence of liquid crystal epoxy are reviewed.

Construction of a Metal-Silica Interface for Semihydrogenation of Alkynes.

Fabricating optimum surface structures represents an attractive approach for synthesizing supported catalysts with high activity and specific selectivity. New active sites could be flexibly constructed via the strong metal-support interaction under the redox condition. Herein, we demonstrated the formation of a new Rh-Si surface on a silica-modified carbon nanotube supported Rh catalyst under the high-temperature reduction condition as well as a thin amorphous silica coating layer and weak chemisorption toward the CO molecule. The electronic interactions between Rh and Si, along with the particular structure, guarantee desirable catalytic performance for the semihydrogenation of phenylacetylene under mild conditions. This facile approach might be extensively used in constructing new active sites with robust activity and specific selectivity in diverse heterogeneous catalysis systems.

An Anatomy- and Topology-Preserving Framework for Coronary Artery Segmentation.

Coronary artery segmentation is critical for coronary artery disease diagnosis but challenging due to its tortuous course with numerous small branches and inter-subject variations. Most existing studies ignore important anatomical information and vascular topologies, leading to less desirable segmentation performance that usually cannot satisfy clinical demands. To deal with these challenges, in this paper we propose an anatomy- and topology-preserving two-stage framework for coronary artery segmentation. The proposed framework consists of an anatomical dependency encoding (ADE) module and a hierarchical topology learning (HTL) module for coarse-to-fine segmentation, respectively. Specifically, the ADE module segments four heart chambers and aorta, and thus five distance field maps are obtained to encode distance between chamber surfaces and coarsely segmented coronary artery. Meanwhile, ADE also performs coronary artery detection to crop region-of-interest and eliminate foreground-background imbalance. The follow-up HTL module performs fine segmentation by exploiting three hierarchical vascular topologies, i.e., key points, centerlines, and neighbor connectivity using a multi-task learning scheme. In addition, we adopt a bottom-up attention interaction (BAI) module to integrate the feature representations extracted across hierarchical topologies. Extensive experiments on public and in-house datasets show that the proposed framework achieves state-of-the-art performance for coronary artery segmentation.

Structural and mechanical behavior of type-I collagen fibrils in presence of induced electrostatic interactions through ionic liquids

Tuning the self-assembly of collagen has broad applications in the biomedical field owing to their desired biological performance as collagenous materials with tunable functionalities can further determine cellular responses. In this work, an attempt has been made to tune the self-assembly of collagen using ionic liquids, viz., imidazolium chloride (IC) and choline dihydrogen phosphate (CDHP) at its physiological pH, followed by probing assembled systems using various characterization methods. Turbidity measurements of fibrillar networks were performed to ascertain the rate of fibril formation in addition of imidazolium chloride and choline dihydrogen phosphate to collagen at physiological pH. Morphological changes were examined using Scanning Electron Microscope (SEM), binding affinities were measured by Microscale Thermophoresis (MST), in addition to, changes in the shear viscosity, mechanical strength of collagen fibrils when interacted with imidazolium and choline based ILs were carried out using rotational rheometer and Quartz Crystal Microbalance (QCM) measurements. Experimental result depicts that CDHP imparts better crosslinking as well as mechanical strength compare to IC, which is already known for destabilizing the triple helix structure is inhibiting the fibril formation. This self-assembled, ionic-liquid treated collagen-fibrillar system would accelerate various force modulated fibrillar network study, for mimicking the ECM and tissue engineering application.

Incorporating participants' welfare into sequential multiple assignment randomized trials.

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential, multiple assignment, randomized trial (SMART) is an experimental design that can provide high-quality evidence for constructing optimal DTRs. In a conventional SMART, participants are randomized to available treatments at multiple stages with balanced randomization probabilities. Despite its relative simplicity of implementation and desirable performance in comparing embedded DTRs, the conventional SMART faces inevitable ethical issues, including assigning many participants to the empirically inferior treatment or the treatment they dislike, which might slow down the recruitment procedure and lead to higher attrition rates, ultimately leading to poor internal and external validities of the trial results. In this context, we propose a SMART under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design that holds the potential to improve participants' welfare by incorporating their preferences and predicted treatment effects into the randomization procedure. We describe the steps of conducting a SMART-EXAM and evaluate its performance compared to the conventional SMART. The results indicate that the SMART-EXAM can improve the welfare of the participants enrolled in the trial, while also achieving a desirable ability to construct an optimal DTR when the experimental parameters are suitably specified. We finally illustrate the practical potential of the SMART-EXAM design using data from a SMART for children with attention-deficit/hyperactivity disorder.

A Wilkinson power divider with harmonic suppression through low-pass filter for GSM and LTE applications

Conventional Wilkinson power dividers (WPDs) perform satisfactorily near the intended operation frequency. Nonetheless, these WPDs demonstrate subpar performance in the stopband and necessitate a significant physical space. To enhance the existing level of advancement and in order to improve on the current state-of-the-art, a modified WPD is designed and fabricated, demonstrating a significant improvement in stopband and superior isolation between output ports. To improve the stopband and suppress unwanted harmonics, a low-pass filter (LPF) structure is placed in the both branches of the conventional WPD. The proposed modified WPD depicts a wide stopband bandwidth (fSB > 17.25 GHz) from 2.75 to over 20 GHz with an attenuation level of 20 dB, suppressing 2nd to 11th harmonics. According to measured results, the input return loss (|S11|), insertion loss (|S21|) and output isolation (|S32|) at f = 1.8 GHz are better than 33 dB, 3.2 dB and 21 dB, respectively. Indeed, the proposed modified WPD exhibits a magnitude imbalance of 0.00018, a phase imbalance of 1.25 degrees and a group delay of 0.5 ns. The proposed WPD depicts a compact size of 35 mm × 25 mm (0.38 λg × 0.27 λg), where λg is the guided wavelength at f = 1.8 GHz. There is a good agreement between the simulated and measured results. According to the obtained results, the proposed modified WPD shows a desirable performance for modern LTE and GSM communication applications.

Employee Motivation and Outcomes of Developing and Maintaining High-Quality Supervisor–Subordinate Guanxi in Hotel Operations

Dyadic leader–follower relationships play a significant role in sustainable development of labor-intensive and service-oriented organizations. The purpose of this study is to assess employees’ motivation and outcomes of developing and maintaining high-quality supervisor–subordinate guanxi in Chinese hotels. A survey was undertaken in four- or five-star hotels, with a total of 318 matched employees-supervisor completed responses used for data analysis, which was conducted using SPSS Statistics and SmartPLS. The study’s results show that affection and obligation significantly motivate employees to develop and maintain supervisor–subordinate guanxi, which in turn contributes to the desirable task performance delivery and supervisor autonomy support. Furthermore, the study confirms the mediating roles of supervisor–subordinate guanxi and task performance. This work extends guanxi research and is among the first to identify why hotel employees are motivated to develop and maintain high-quality supervisor–subordinate guanxi based on the contextualization of self-determination theory and Chinese cultural elements.

A dynamic topology optimization design method based on multiple domain variable parameters

Topology optimization has been extensively studied for obtaining desired functional performances of a structure within a predefined design domain. However, existing topology optimization approaches mainly focus on the static structure. Additionally, a structure is generally consisted of multiple materials and its loading state is quite complicated in practical applications, which are seldom considered simultaneously during design optimization. In this paper, a dynamic topology optimization design method based on multiple domain variable parameters is proposed to solve these issues. First, a structure is divided into multiple domains, and an optimal topology model of discrete structure is proposed. Then, the constraints are relaxed and a per-element variable is introduced to process the design variables continuously. To eliminate the undesirable checkerboard patterns, a filtering method is proposed and an approach of projection is presented for determining the volume of the projected structure according to the practical design requirements. After that, a dynamic continuous optimization model is put forward for solving the optimal solution of the complex structure under various working conditions. Finally, the effectiveness and efficiency of the proposed method are validated by constructing a topology optimized link of the press.