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Developing high-efficient bifunctional electrocatalysts is significant for the overall water splitting. Bimetallic phosphides show great potential for the bifunctional hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) catalysts due to the excellent catalytic performance. Herein, the CoFeP two-dimensional nanoarrays successfully grown on nitrogen doped electrospun carbon nanofibers (CoFeP NS@NCNF) through template-directed growth and following phosphorization treatment. Benefiting from the hierarchical nanoarrays structure, synergistic effect of high electrical conductivity carbon nanofiber substrate and bimetallic phosphide, the CoFeP NS@NCNF exhibits efficient bifunctional electrocatalytic activities for OER and HER in 1 M KOH with overpotentials of 268 mV (η20) and 113 mV (η10), respectively. Moreover, the CoFeP NS@NCNF coupled two-electrode system needs a low voltage of 1.59 V at 10 mA cm−2 for overall water splitting. This work provides a promising way for the preparation of transition metal-based electrocatalysts with hierarchical structure derived from Prussian blue analogues (PBAs) for OER and HER.

High-performance sulfonated polysulfone (SPSf) mixed-matrix membranes (MMMs) were fabricated via a nonsolvent-induced phase separation (NIPS) method using zeolitic imidazolate frameworks-67 (ZIF-67) as a crosslinker. Acid-base crosslinking occurred between the sulfonic acid groups of SPSf and the tertiary amine groups of the embedded ZIF-67, which improved the dispersion of ZIF-67 and simultaneously improved the membrane strzcture and permselectivity. The dispersion of ZIF-67 in the MMMs and the acid-base crosslinking reaction were verified by energy-dispersive X-ray spectroscopy (EDX), X-ray diffractometry (XRD), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). The pore structure analysis of MMMs indicated that filling ZIF-67 into SPSf enhanced the average surface pore sizes, surface porosities and more micropore in cross-sections. The crossflow filtrations showed the MMMs have higher pure water fluxes (57 to 111 L m−2 h−1) than the SPSf membrane (55 L m−2 h−1) but also higher bovine serum albumin (BSA) rejection rate of 93.9–95.8%, a model protein foulant. The MMMs showed a higher water contact angle than the SPSf membrane due to the addition of hydrophobic ZIF-67 and acid-base crosslinking, and also maintained high thermal stability evidenced by the thermogravimetric analysis (TGA) results. At the optimal ZIF-67 concentration of 0.3 wt%, the water flux of the SPSf-Z67-0.3 membrane was 82 L m−2 h−1 with a high BSA rejection rate of 95.3% at 0.1 MPa and better antifouling performance (FRR = 70%). Highlights An SPSf-matrix ultrafiltration (UF) membrane was developed by blending with hydrophobic ZIF-67.; ZIF-67 has good dispersibility and compatibility with SPSf of weak acid-base interaction.; Simultaneous enhancement in the permeability and selectivity of the MMMs.

This article proposes a novel surfactant-confined preparation method that uses polyoxometalates (POMs) as the precursor to synthesize CoMo/Al2O3 catalysts. The proposed technique anchors a decyltri...

Transition metal phosphides have been known as promising electrocatalysts for hydrogen evolution and oxygen evolution reactions (HER and OER) due to their high catalytic activity. In this work, the FeCoP nanoparticles decorated on N-doped electrospun carbon nanofibers (FeCoP@NCNFs) was successfully synthesized through depositing Fe, Co-based Prussian blue analogue Co3[Fe(CN)6]2·10H2O (FeCo-PBA) onto the electrospun PVP/PAN nanofibers via layer-by-layer approach, followed by carbonization and phosphorization treatments. Benefiting from the high electrical conductivity, abundant catalytic active sites and the synergistic effect between FeCoP nanoparticles and N-doped carbon nanofibers network, the obtained FeCoP@NCNFs displays good bifunctional electrocatalytic activity. In 1 M KOH, the FeCoP@NCNFs achieves 10 mA cm−2 at an overpotential of 290, 226 mV for OER and HER, respectively. Moreover, it demands overpotential of 196 mV to achieve 10 mA cm−2 for HER in 0.5 M H2SO4. The FeCoP@NCNFs is used as both anode and cathode for overall water splitting, it requires a low voltage of 1.65 V to achieve a current density of 10 mA cm−2 and maintains outstanding stability over 10 h. Herein, a strategy for preparing bifunctional electrocatalysts of compositing transition metal phosphides with carbon nanofibers is proposed, and the application of metal-organic framework in electrocatalytic field is further extended.

The spectral element method (SEM) is widely used for analyzing high frequency electromagnetic wave propagation and scattering in complex structures. At low frequencies, however, the primary (direct) fields are usually much larger than the secondary fields caused by scattering, thus making it much more difficult to accurately simulate the secondary (scattered) fields because of the source singularity in the primary fields. To more effectively and accurately simulate the low-frequency secondary fields in subsurface structures, in this work the vector Helmholtz equation for the scattered fields is used to directly obtain the secondary field data in inhomogeneous anisotropic media. The computational method for the secondary electromagnetic fields is based on the mixed spectral element method (mixed SEM) for anisotropic objects in a layered anisotropic background medium. The electromagnetic field is separated into the background fields that are evaluated analytically using the dyadic Green’s functions (DGFs) of a layered uniaxially anisotropic medium, and the secondary fields caused by anomalous bodies with arbitrary shapes are numerically computed by the mixed SEM. This avoids the source singularity, and allows the transmitters to be located outside the computational domain. By enforcing Gauss’ law as the constraint condition, the mixed SEM efficiently eliminates the low frequency breakdown problem. Numerical results verify the proposed method over the traditional SEM in low-frequency scattering from objects in subsurface layered anisotropic media.

Intricate engineering of oxygen vacancies (OVs) to trap kinetically diffusible rarefied NO gas and to enhance the population of long-lived electrons remains a great challenge for NO removal in outdoor atmosphere. In this study, OV-engineered Bi2Sn2O7−x hollow nanocubes with distinct Sn/Bi-adjacent OVs were tightly managed and synthesized. Theoretical calculations and experimental studies revealed that not all types of OVs were beneficial for increasing the photoactivity owing to their different effects on the band structure and carrier diffusion path. Bi2Sn2O7−x with Sn-adjacent OVs could serve as adsorption sites, boosting rarefied NO enrichment and electron–hole separation. However, Bi2Sn2O7−x with Bi-adjacent OVs exhibited an opposite effect owing to increased charge recombination centers. Our findings highlight the importance of the character of OVs for efficient interface electron activation and for the removal of ambient rarefied gaseous pollutants.

The hyperglycemic environment and the presence of bacterial infections delay the healing of diabetic wounds. Herein, glucose oxidase (GOx) and Fe3O4/TiO2/Ag3PO4 were embedded in a polyacrylic acid-calcium phosphate (PAA-CaPs@Nps@GOx) hydrogel through an in situ biomimetic mineralization approach. The GOx encapsulation efficiency was 96.75% and exhibited exceptional enzyme activity stability. Moreover, the co-immobilization of GOx and Fe3O4/TiO2/Ag3PO4 nanoparticles generated a simple and multifunctional antibacterial platform with the advantages of decreasing blood glucose concentration and efficiently producing reactive oxygen species (ROS). In addition, the degradation rate of the hydrogel was controlled by regulating the concentration of phosphate thus controlling the release of Fe3O4/TiO2/Ag3PO4 and GOx. As a result, both the potential toxicity and oxidative stress associated with the antimicrobial biomaterial can be controlled within the body therefore potentially preventing detriment. In vivo results indicated that the PAA-CaPs@Nps@GOx hydrogel effectively promoted diabetic wound healing and showed great potential for clinical applications of chronic wound management.

Statistical process monitoring (SPM) methods have been adopted and studied to detect variations in the fused deposition modeling (FDM) process in recent years. The FDM process that builds parts layer-by-layer is accomplished in a specified manufacturing period (number of layers) without interruption or suspension. Thus, traditional SPM methods, where the average run length is used for the calculation of the control limits and the measurement of the performance, are no longer applicable to the FDM process. In this paper, an SPM method is proposed based on the surface image data of FDM parts with consistent layers and a specified period. The probability of alarm in a specified period (PASP) and the cumulative PASP are introduced to determine the control limits and evaluate the monitoring performance. Regions of interest are determined in a fixed way to cover the sizes and locations of different defects. The statistics are calculated based on the generalized likelihood ratio. The control limit is determined based on the specified period and the nominal in-control PASP. A simulation study for different locations, sizes and magnitudes of the mean shift of defects is presented. In the case study, the proposed SPM method is applied to monitor the FDM process of a cuboid, which verifies the effectiveness of the proposed method.

Sour water contains ammonia, carbon dioxide, and hydrogen sulfides, producing from oil refining, coking, and coal gasification. To reduce the energy consumption in sour water stripping, a novel process is proposed which integrates with the bottom flashing mechanical vapor recompression heat pump (MVRHP) for treating such wastewater. Here, Aspen Plus™ as a powerful set of chemical process simulation software is utilized to investigate the economy and feasibility of the novel process. Comparison of the results of two process simulations, it can be seen that it is possible to reduce the total annual cost by nearly 45% to adopt the novel process, despite the capital investment increase 45% more than the conventional process. Thus, the provided conceptual design will play a guiding role in the industrialization of the process.

Two-dimensional (2D) nanomaterials have drawn a wide range of research interests because of their unique ultrathin layered structures and attractive properties. In particular, the electrochemical properties and great variety of 2D nanomaterials make them highly attractive candidates for electrochemical capacitors, such as supercapacitors, lithium-ion capacitors, and sodium-ion capacitors. Herein, a comprehensive review of recent progress towards the application of 2D nanomaterials for electrochemical capacitors is provided. Several typical types of 2D nanomaterials are first briefly introduced, followed by detailed descriptions of their electrochemical capacitor applications. Finally, research perspectives and future research directions of these interesting areas are also provided.

Asphalt pavement contains dynamically changing moisture, and the movement of this moisture will change the relative humidity of the pavement, thereby affecting the dielectric properties of ...

Continuous observations from geostationary satellites can show the morphology of precipitation cloud systems in quasi-real-time, but there are still large deviations in the inversion of precipitation. We used binary-connected area recognition technology to identify meso-β-scale rain clusters over Hainan Island from 1 June 2000 to 31 December 2018, based on Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM data. We defined and statistically analyzed the parameters of rain clusters to reveal the typical morphological and precipitation characteristics of rain clusters, and to explore the relationship between the parameters and rainfall intensity of rain clusters. We found that the area and long axis of rain clusters over land were larger than those over the ocean, and that continental rain clusters were usually square in shape. Rain clusters with a larger area and longer axis were concentrated on the northern side of the mountains on Hainan Island and the intensity of rain was larger on the northern and eastern sides of the mountains. The variation of continental rain clusters over time was more dramatic than the variation of oceanic clusters. The area and long axis of rain clusters was larger between 14:00 and 21:00 from April to September and the long axis of the oceanic rain clusters increased in winter. There were clear positive correlations between the area, long axis and shape of the rain clusters and the maximum rain rate. The area and long axis of continental rain clusters had a higher correlation with the rain rate than those of oceanic clusters. The establishment of a relationship between the morphology of rain clusters and precipitation helps us to understand the laws of precipitation and improve the prediction of precipitation in this region.

Traditional four-bucket method for sinusoidal phase shifting interferometry (PSI) assumes the integration time T s to be equal to a quarter of the modulation period T c . As some image sensors need certain vacant time between two integrations, this assumption makes it somehow unrealistic to perform one measurement within a modulation period. Addressing this problem we investigated the four-integrating-bucket method with a shortened exposure time. We assume T s to be any value between 0 and T c /4 such that there would be some time between two adjacent integrations and the measurement can be fulfilled in one modulation period. The optimum modulation depth and phase offset of the sinusoidal modulation are deduced for different T s by minimizing xthe phase noise induced by additive noise. It is found that the optimum modulation depth is always around 2.45 whatever the value of T s is. What is more, decreasing the integration time to less than T c /4 helps to improve the fringe visibility as well and to further reduce the phase noise by up to 2.5 dB at most, which are demonstrated by both simulation and experiment.

Software aging is a risk associated with the continuous operation of software, and it is essential and meaningful to develop anti-aging technology to offset or mitigate the aging phenomenon. While considerable attention has been devoted to software aging and anti-aging techniques, few studies have focused on single-event effect as a software-aging reason in the context of a space environment. In this study, aiming at the software-aging problem caused by the specific reason above, besides the classic software rejuvenation, we further explore the anti-aging effects and rules of software reliability design modes, including triple modular redundancy (TMR) and logical partitioning. Reliability and availability are used as aging indicators, and the anti-aging effect of reliability design modes and rejuvenation policy is quantitatively analyzed through probabilistic model checking. The simulation and theoretical results show that the reliability design mode can alleviate software aging. However, the TMR mode is time-sensitive. It is found that the application of the rejuvenation policy makes time-sensitivity disappear. A combination of reliability design modes and rejuvenation policy can obtain the best anti-aging effect. The analysis and discussion in this paper can provide useful insights for software researchers to instantiate different software anti-aging inventions or new applications.

A new arbitrary phase shifting method is proposed in this paper for fiber-optic fringe projection profilometry. By introducing a small temporal sinusoidal phase modulation to the phase shift and employing the phase-generated carrier (PGC) method, the time-varying interference phase α(t)can be demodulated from the Michelson interference signal, which is reflected by the fiber end faces and recorded concurrently with the recording of the fringe pattern. Integrate sin [α(t)] and cos [α(t)] respectively, and then the phase shifts between frames can be determined and consequently used to solve the phase map with least-squares PS algorithm. The noise model of this method is deduced from which the optimum modulation amplitude can be selected. In the experiment, four fringe patterns with uncalibrated phase shifts were recorded under strong environmental disturbance, and were analyzed by utilizing the Carre algorithm, the proposed method and the modified Fourier transform (MFT) method respectively. A visual criterion is used to evaluate the performances of these methods. Experimental results indicate that the proposed method is much more robust to phase shift miscalibration than the Carre algorithm, and its performance is comparable to that of the MFT method while its computational complexity is substantially lower. Therefore, the proposed method is suitable for real-time phase shift calibration.

Ac phase tracking technique (PTAC) is an established and effective method for phase stabilization of fiber-optic fringe projectors (FoFP), but it may reduce the fringe visibility owing to the introduction of an extra sinusoidal phase modulation. In this paper we propose an integrating-bucket method to stabilize the phase of FoFPs which is applicable to both linear phase shifting (LPS) profilometry and sinusoidal phase shifting (SiPS) profilometry. The method requires no extra modulation of the interference phase; instead, it divides the interference signal period into N (N > 2) episodes with equal time intervals and directly integrates these episodes to obtain N discrete data. By manipulating these data the interference phase can be calculated and accordingly phase disturbance can be eliminated by the feedback loop. The proposed method is as effective as the PTAC technique but at the same time more computationally efficient because the operations involved are merely add, subtraction and arctangent solution. We built a digital phase controller with the proposed method, and managed to restrict the maximum phase drift of an FoFP to within 15 mrad in 5 min for both LPS and SiPS, which is similar to the result obtained with the PTAC technique. What’s more, we measured the mean value variation of the recovered phase map of a stabilized FoFP profilometer, and results are 30 mrad for LPS and 50 mrad for SiPS in 5 min.

For some design applications, the environment in actual field conditions does not remain constant but instead changes dynamically. In addition, stress levels might change sharply, and if the change happens for a long enough time and at a high enough rate, it could act as a shock to the product, although it is not actually a shock that occurs instantly. This situation is defined as an effective shock in this paper. An effective shock is caused by a rapid change in stress that has an analogous effect to an actual shock, where the stress change is immediate. Existing works on degradation modeling and lifetime prediction for products operating in a dynamic environment consider the effects of time-varying stress levels on the degradation rate of product performance. If shocks are considered at all, it is only those shocks that occur instantaneously. In this paper, a model that characterizes the degradation process of a product operating in a dynamic environment considering effective shocks is proposed to predict the residual lifetime of the product. This model is established based on a stress-dependent degradation rate and an effective shock function together with a Wiener process to model the stochastic degradation. A simulation study is presented as a demonstration of the application of this model, and a case study testing miniature light bulbs is presented to verify the effectiveness of the proposed model.

Mixed spatial autoregressive (SAR) models with numerical covariates have been well studied. However, as non-numerical data, such as functional data and compositional data, receive substantial amounts of attention and are applied to economics, medicine and meteorology, it becomes necessary to develop flexible SAR models with multiple data types. In this article, we integrate three types of covariates, functional, compositional and numerical, in an SAR model. The new model has the merits of classical functional linear models and compositional linear models with scalar responses. Moreover, we develop an estimation method for the proposed model, which is based on functional principal component analysis (FPCA), the isometric logratio (ilr) transformation and the maximum likelihood estimation method. Monte Carlo experiments demonstrate the effectiveness of the estimators. A real dataset is also used to illustrate the utility of the proposed model.

This article proposes a novel strategy for producing highly dispersed H3PW12O40 (HPW) on metal-organic frameworks (MOFs) via the anchoring action of amino groups originating from 2-amino terephthalic acid (APTA) in the MOF ligand. Under this method, amino groups are introduced into the linker of UiO-66 materials through a one-pot synthesis to disperse supported HPW, which has a negligible impact on the crystal structure of UiO-66. The acidic densities in the HPW/UiO-66 catalysts are effectively modified by adjusting the molar APTA/PTA (terephthalic acid) ratio in the mixed ligand and HPW loading. Consequently, the dispersion and stability of supported HPW are significantly enhanced, which make the as-prepared catalyst with 40 wt% of HPW present superior sec-butyl acetate (SBAC) yield (38.6 wt%) and selectivity (98 wt%) for the direct esterification of olefins. This strategy provides a new approach for preparing supported HPW with high dispersion and stability to be applied in olefin esterification.

A series of CoMo/graphene selective hydrodesulfurization (HDS) catalysts were prepared using the hexamethonium bromide-assisted hydrothermal method, and the influences of the hexamethonium bromide/Mo molar ratio and the CoMoS/MoS2 ratio on the HDS activity and selectivity were investigated. The results show that the kHDS value (2.76 × 10−7 mol g−1 s−1) of thiophene and the HDS selectivity factor (13.6) over the as-prepared catalysts were 1.3 times and 1.6 times greater than those over the CoMo/graphene prepared using the conventional impregnation method. The higher HDS activity and selectivity of the as-prepared catalysts result from the higher dispersion of Mo species and the higher CoMoS/MoS2 ratio compared to the CoMo/graphene prepared by impregnation. Among all the catalysts, the catalyst with a hexamethonium bromide/Mo molar ratio of 6.0 presents the highest HDS selectivity due to its highest ratio of edge to corner Co atoms in CoMoS with a superior CoMoS/MoS2 ratio. The present investigation provides a route for developing highly selective HDS catalysts using graphene as support by adjusting the hexamethonium bromide/Mo ratio to finely tune the morphology of the active phases.

The photocatalytic removal of gaseous NOx is commonly accompanied by secondary pollution, which necessitates the development of highly efficient nanostructured catalysts with a decreased propensity to toxic intermediate production. Herein, we describe the synthesis of plasmonic Bi/Bi2O2−xCO3 and demonstrate the presence of surface oxygen vacancies therein, revealing that the maximal NOx removal efficiency of Bi/Bi2O2−xCO3 under visible light irradiation reached 50.5% and exceeded that of a commercial photocatalyst, while the production of toxic NO2 as a by-product was completely suppressed (the selectivity reached up to 98%). In-situ introduction of plasmonic Bi on the surface of Bi2O2−xCO3 promoted the generation of H2O2 by capturing electrons from the defect states of Bi2O2−xCO3 via the two-electron reduction of O2 and thus inhibited NO2 production (as confirmed by scavenger experiments), additionally broadening the light absorption range of the above photocatalyst. Moreover, surface oxygen vacancies in Bi–O layers provided a channel for electron transfer between Bi and Bi2O2−xCO3, which resulted in increased charge separation efficiency (maximum photocurrent = 1.1 μA cm−2, 14.5 times higher than that of pristine Bi2O2CO3). Furthermore, the toxicity assessment authenticated good biocompatibility of Bi/Bi2O2−xCO3. Thus, this study sheds light on the possible roles of H2O2 in NOx degradation and provides an efficient surface engineering strategy to prepare highly reactive and selective photocatalysts.

With the absence of structure parameters of chillers, it is difficult to simulate the chiller performance by the conventional precise modeling approach. Thus, a novel modeling approach is proposed, which makes unknown structure parameters lumped and obtains them (i.e. the characteristic parameters, which are unique for each chiller) based on measured data of chillers. The modeling principle of feature recognition is described, based on which then the chiller models were developed. An experimental platform of chiller was established, and the relevant chiller models were established on basis of measured data. Moreover, to verify the chiller models, simulations and experiments were compared under variable water flow rate and variable water temperature conditions respectively. Results show that with the feature recognition method, the chiller models can function quickly and efficiently, and achieve a high accuracy. Compared with experimental results, relative errors of simulated performance parameters, such as refrigerating capacity and COP (coefficient of performance), are all within 10%. This study provides a new and efficient approach for chiller modeling.

Metal germanate nanospheres including Ca2Ge7O16, Zn2GeO4 and SrGe4O9 were successfully synthesized by a direct and large-scale electrospraying method. As anodes for lithium ion batteries, the prepared metal germanate nanospheres showed high electrochemical lithium storage performance including excellent cycling stability and high rate capacity. Especially, the Ca2Ge7O16 nanosphere anode delivered a high specific capacity of ∼ 670 mA h g−1 at 0.2 A g−1. The capacity retention was maintained around 71% even after 500 cycles. Moreover, when applied as room-temperature ammonia gas sensors, all three prepared germinate nanospheres showed significant sensing response values (6.04 for SrGe4O9, 2.73 for Zn2GeO4 and 1.70 for Ca2Ge7O16), fast response–recovery time, excellent stability and outstanding selectivity.

A simple algorithm is proposed in this paper for the implementation of second-order-polynomial-based peak-tracking methods used in FBG sensors. By assuming that wavelengths samples are evenly distributed in the acquired reflective spectrum, which is always desired for most interrogation systems, we decomposed the Moore-Penrose of the coefficient matrix into the multiplication of an upper triangular matrix and a symmetric matrix, and consequently derived an equation nearly as simple as that of the centroid method for the determination of peak wavelength. The algorithm does not involve matrix multiplication and inverse matrix solution, so it can be easily fulfilled with solely fixed-point operations and consumes only one tenth of the calculation time needed by conventional method. Besides, the symmetric feature of the factorization makes it possible to facilitate the calculation with an existing FIR core. By using a piecewise linear fitting to the wavelength samples, the algorithm is also applicable in cases where wavelength sampling interval is not constant. An interrogation system was built up based on FPGA and a commercial spectrometer with a wavelength nonlinearity of 3 nm. It was able to interrogate over 50 FBG sensors at the same time at a measurement frequency of 17 kHz by using the proposed algorithm.

White organic light-emitting diodes (WOLEDs) based on all thermally activated delayed fluorescence (TADF) emitters are especially attractive due to the merits of high efficiency and low cost. Novel TADF emitters (TFM-QP and CN-QP) were developed by selecting 6-(trifluoromethyl)quinoxaline or 6-(cyano)quinoxaline as the electron acceptor and phenoxazine as the electron donor. Aggregation induced emission is detected. Small singlet and triplet energy splitting values of 0.03–0.04 eV and long fluorescence lifetimes of 1.6–5.0 μs confirm their TADF nature. The chromaticity of monochromic OLEDs with TFM-QP and CN-QP as doped emitters was adjustable from yellow to orange–red by varying the doping concentration, and the yellow OLEDs exhibit external quantum efficiencies (ηext) of 14.4% and 9.7% at a low doping level. Full-TADF WOLEDs were fabricated using TFM-QP or CN-QP in combination with the sky-blue TADF emitter DMAC-DPS. The single-emitting-layer doped warm-white OLED (CN-QP:DMAC-DPS) exhibits excellent performance with a low turn-on voltage of 2.8 V, a stable color rending index (CRI) of 72, and high efficiencies of 48.22 cd A−1, 50.47 lm W−1, and 20.16%, which should be the highest efficiency records ever reported for full-TADF warm-white OLEDs so far. The non-doped full-TADF WOLED with an emitting layer structure of DMAC-DPS/TFM-QP/DMAC-DPS achieves a high CRI of 86 and a moderate ηext of 8.7%.

This paper proposes a novel one-step hydrothermal polyoxometalate (POM) dispersion method for synthesizing NiMo/Al2O3 hydrodesulfurization (HDS) catalysts with high Ni/Mo atomic ratios. The propose...

Oriented transfer of electron-hole charge carriers is important during photocatalytic processes. In this study, one-dimensional (1D) tubular B-doped graphitic carbon nitride (g-C3N4) with an effective charge transfer and separation was designed. The doping sites, energy level structure, and photo-generated electron-hole pair separation were predicted using systematical density functional theory (DFT) simulations. The supramolecular precursor for tubular g-C3N4 synthesis, namely melamine·cyanuric acid (M·CA), was controllably synthesized from a single melamine source. Intermolecular hydrogen bonding led to the arrangement of supramolecular aggregate structures into a prismatic crystal architecture during the hydrothermal treatment. The morphology modulation of g-C3N4 from bulk to 1D tubular architecture was realized by calcining the prism-like precursor. B-doped tubular g-C3N4 exhibited a narrower band-gap, multiple reflections of incident light, and oriented transfer of electron-hole charge carriers, which led to a widened light-harvesting range and improved photo-induced electron-hole pair separation and transfer ability. These factors contributed to the photocatalytic activity enhancement towards gaseous NOx degradation under visible light. In this work, a valuable design-fabrication pattern for g-C3N4 modification and engineering via DFT simulations was designed. Moreover, a strategy was developed for the simultaneous foreign atom doping and architecture control of g-C3N4 via the self-assembly of supramolecular precursors.

Oxygen vacancies of metal oxides play critical roles in tunning activity and selectivity for many photocatalysis mediated reactions, yet the mechanism of NO oxidation on defect enriched photocatalyst surface is seldomly discussed. Herein, we provide detailed insight into the relationship between oxygen vacancy manipulation by extrinsic Fe3+ substitution in SrTiO3 host lattice and the photocatalytic performance of NO abatement. In particular, the hydrothermal synthesized SrFexTi1-xO3-δ nanocubes (denoted as SFTO-hyd sample) rather than the impregnated-post annealing sample, enabled oxygen vacancy formation, and promoted O2 adsorption and superoxide anion radicals ( O2−) formation. The SFTO-hyd (x = 5%) sample showed remarkably higher NO removal activity and selectivity under Xe lamp (λ > 420 nm), in comparison with the pristine SrTiO3, P25 and impregnation-doped SFTO sample, underlining the important roles played by coexisted Fe3+ sites and oxygen vacancies. The in situ diffuse reflectance IR spectroscopy (DRIFTS) mechanically revealed that SrTiO3 provided Lewis acidic sites for NO dark adsorption and photoreaction with nitrates as final products; the substitutional Fe3+ sites provided more active sites for NO adsorption and photoreaction with enhanced number of radicals. This study deepens the understanding of photocatalytic NO abatement on defective surface, and may also provide a simple and cost effective strategy for synthesizing efficient and selective photocatalysts for environmental remediation.

The traditional differential chaotic keying (DCSK) system is a kind of low-power and low-complexity system. However, in order to meet the demand of high throughput of low-power network, like wireless body area network (WBAN), the DCSK system must be redesigned. A multicarrier M-ary differential chaos shift keying system(MC-MDCSK) has been proposed, where good diversity gain and high throughput have been achieved. Analytical bit-error-rate expressions are derived and verified by simulations over additive white Gaussian noise and multi-path fading channels.

In this paper, a novel neural network based compressed sensing (CS) receiver for chaotic ultra-wideband (UWB) communication system is proposed. Chaotic UWB system receiver based on CS has been proved to be feasible and can greatly reduce the sampling rate. However, the measurement signal in CS is not optimized according to the received chaotic signals. Thanks to the learning capability of neural network with deep learning algorithm, the proposed receiver is able to intelligently optimize the measurement signal in CS and discover the underlying mapping between the input and output signals. Numerical experiments demonstrate that the proposed scheme can effectively enhance the bit error rate (BER) performance than the conventional one. Moreover, we propose a simple and practical statistical adjustment method for the proposed receiver. Numerical experiments also show that the method can further improve the BER performance.

Lead sulfide (PbS) quantum dots (QDs) have shown promising performance as a sensitizer in infrared-to-visible photon upconversion systems. To investigate the key design rules, we compare three PbS-sensitized upconversion systems using three mediator molecules with the same tetracene triplet acceptor at different distances from the QD. Using transient absorption spectroscopy, we directly measure the triplet energy-transfer rates and efficiencies from the QD to the mediator and from the mediator to the emitter. With increasing distance between the mediator and PbS QD, the efficiency of the first triplet energy transfer from the QD to the mediator decreases because of a decrease in the rate of this triplet energy-transfer step, while the efficiency of the second triplet energy transfer from the mediator to the emitter increases because of a reduction in the QD-induced mediator triplet state decay. The latter effect is a result of the slow rate constant of the second triplet energy-transfer process, which is 3 orders of magnitude slower than the diffusion-limited value. The combined results lead to a net decrease of the steady-state upconversion quantum yield with distance, which could be predicted by our kinetic model. Our result shows that the QD/mediator interface affects both the first and second triplet energy transfer processes in the photon upconversion system, and the QD/mediator distance has an opposite effect on the efficiencies of the first and second triplet energy transfer. These findings provide important insight for the further rational improvement of the overall efficiency of QD-based upconversion systems.

The Lattice Boltzmann method (LBM) has been applied for the simulation of lid-driven flows inside cavities with internal two-dimensional circular obstacles of various diameters under Reynolds numbers ranging from 100 to 5000. With the LBM, a simplified square cross-sectional cavity was used and a single relaxation time model was employed to simulate complex fluid flow around the obstacles inside the cavity. In order to made better convergence, well-posed boundary conditions should be defined in the domain, such as no-slip conditions on the side and bottom solid-wall surfaces as well as the surface of obstacles and uniform horizontal velocity at the top of the cavity. This study focused on the flow inside a square cavity with internal obstacles with the objective of observing the effect of the Reynolds number and size of the internal obstacles on the flow characteristics and primary/secondary vortex formation. The current LBM has been successfully used to precisely simulate and visualize the primary and secondary vortices inside the cavity. In order to validate the results of this study, the results were compared with existing data. In the case of a cavity without any obstacles, as the Reynolds number increases, the primary vortices move toward the center of the cavity, and the secondary vortices at the bottom corners increase in size. In the case of the cavity with internal obstacles, as the Reynolds number increases, the secondary vortices close to the internal obstacle become smaller owing to the strong primary vortices. In contrast, depending on the sizes of the obstacles ( R / L = 1/16, 1/6, 1/4, and 2/5), secondary vortices are induced at each corner of the cavity and remain stationary, but the secondary vortices close to the top of the obstacle become larger as the size of the obstacle increases.

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures., Gut microbiome alterations are implicated in major depressive disorder (MDD) and bipolar disorder (BD); however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, the distinct microbial covarying units for MDD and BD are first identified, and microbial markers for distinguishing MDD from BD based on gut microbiome signatures are provided.

Spherical and porous nanoparticles are ideal nanostructures for drug delivery. But currently they are mainly composed of non-degradable inorganic materials, which hinder clinical applications. Here, biological porous nanospheres using RNA as the building blocks and cyclodextrin as the adhesive were synthesized. The RNA contained the aptamer of EpCAM for targeting delivery and siRNA for gene silencing of EpCAM, while cyclodextrin could load insoluble sorafenib, the core drug of targeted therapy for hepatocellular carcinoma (HCC), through its hydrophobic cavity. After being internalized into targeted HCC cells under the assistance of the aptamer, the porous nanospheres could be degraded by the cytoplasmic Dicer enzymes, releasing siRNA and sorafenib for synergistic therapy. The synergistic efficacy of the porous RNA nanospheres has been validated at in vitro function assay, subcutaneous tumor bearing mice, and orthotopic tumor bearing mice in vivo models. In view of the broad prospects of synergy of gene therapy with chemotherapy, and the fact that RNA and cyclodextrin of the porous nanospheres can be extended to load various types of siRNA and small molecule drugs, respectively, this form of biological porous nanospheres offers opportunities for targeted delivery of suitable drugs for treatment of specific tumors.

In this brief, a code index modulated multilevel code shifted differential chaos shift keying, which combines multilevel code shifted differential chaos shift keying (MCS-DCSK) with code index modulation, is proposed. In the proposed scheme, the reference chaos signal is the same with MCS-DCSK, and the multiple information bearing signals are simultaneously modulated by information symbols and selected Walsh codes with specified indices which are determined by additional information bits via the natural number to ${k}$ -combination mapping method. The proposed scheme achieves higher spectrum efficiency compared to MCS-DCSK since additional bits are carried by code indexes. The analytical bit error rate of the proposed system is derived and confirmed by simulation. Finally, advantages of the proposed scheme over MCS-DCSK are verified by numerical results.

This study investigated the effect of temperature on Phase I water vapor diffusion in asphalt mixtures. A test protocol with a series of Phase I water vapor diffusion tests was designed and performed on hot mix asphalt specimens and fine aggregate mixture specimens. A Gravimetric Sorption Device was utilized to perform the diffusion tests on three replicate specimens of each mixture type at five temperatures. A relative humidity differential was established between the inside and the outside of the test specimen and drove water vapor to diffuse into the specimen until reaching equilibrium. The mass of the test specimen was continuously measured at a frequency of every 5 s using the magnetic suspension balance. The mass of water molecules diffused into the specimen at any time point was calculated to be the measured mass of the specimen at that time point less the initial weight of the specimen. A previously developed 3-D diffusion model was applied to the test data of all replicate specimens to determine the Phase I water vapor diffusivities and the moisture retention capabilities per unit mass under only water vapor pressure at various temperatures. These two parameters were converted into the corresponding values under 1 atmosphere, which were increasing with the increase in temperature. It was found that water vapor diffused into the asphalt mixtures at a significantly lower speed under 1 atmosphere than under only water vapor pressure. It was also observed that an asphalt mixture had a much smaller moisture retention capability per unit mass under 1 atmosphere than under only water vapor pressure. The Arrhenius equation was selected based on theoretical justification to quantify the effects of temperature on diffusivities and moisture retention capabilities per unit mass. Excellent goodness of model fit was achieved for every replicate specimen with an R2 value larger than 0.95. The Arrhenius equation was demonstrated to be an appropriate theoretical model that was able to accurately characterize the temperature dependency of both diffusivities and moisture retention capabilities per unit mass.

Compared with the marine shale payzones, lacustrine shale payzones generally contain more interbed layers (e.g., sandstone interbeds and carbonate interbeds), bringing about a higher complexity to the identification of effective lacustrine shale payzones. In this work, a pragmatic but systematic approach is developed to identify the effective lacustrine shale payzones with commercial hydrocarbon-production potentials. Such identification approach is developed based on three easily accessible data sources that are obtained from multiple wells drilled in a given region: 1) well logging data; 2) measured properties of the core samples; and 3) production test data. In this approach, the first step is to identify shale-containing formations based on the lithology profile along a well that has been interpreted using the well logging data. Secondly, a shale-dominated formation is extracted from a given shale-containing formation if the ratio of total shale thickness to the total formation thickness exceeds 60%; this cut-off value is selected based on the consideration that such formation has a higher possibility of industrial production potential. Lastly, a shale-dominated formation can be classified as an effective shale payzone if the total organic carbon (TOC) content, porosity, and effective thickness are all greater than the given threshold values. By using this proposed method, one can obtain the total effective thickness and the regional distribution of effective lacustrine shale payzones, which could help to locate the sweet spot of the shale payzones as well as subsequently design proper methods for recovering the shale resources. The Lower Jurassic formations possess abundant lacustrine shale layers that are widely considered to be the potential lacustrine shale gas payzones in the northwest of Sichuan Basin in China. A case study in this formation is presented to demonstrate the efficacy of the newly developed approach in identifying the effective lacustrine shale payzones. Validation results prove that this new method can be used to effectively identify the effective lacustrine shale payzones with commercial production potentials.

Automated traffic signal performance measures (ATSPMs) are designed to equip traffic signal controllers with high-resolution data-logging capabilities which may be used to generate performance measures. These measures allow practitioners to improve operations as well as to maintain and operate their systems in a safe and efficient manner. While they have changed the way that operators manage their systems, several shortcomings of ATSPMs, as identified by signal operators, include a lack of data quality control and the extent of resources required to use the tool properly for system-wide management. To address these shortcomings, intelligent traffic signal performance measurements (ITSPMs) are presented in this paper, using the concepts of machine learning, traffic flow theory, and data visualization to reduce the operator resources needed for overseeing data-driven ATSPMs. In applying these concepts, ITSPMs provide graphical tools to identify and remove logging errors and data from bad sensors, to determine trends in demand intelligently, and to address the question of whether or not coordination may be needed at an intersection. The focus of ATSPMs and ITSPMs on performance measures for multimodal users is identified as a pressing need for future research.

Water vapor diffusion in asphalt mixtures has been investigated to develop water vapor diffusion models that predict the diffusivities of water vapor in asphalt mixtures. However, even the most comprehensive diffusion model available in the literature was not rigorously derived in the three-dimensional (3-D) coordinates but formulated by simply summing up the diffusion models for different directions. This study developed a closed-form 3-D diffusion model for Phase I water vapor diffusion in asphalt mixtures. The developed model was formulated through rigorous derivations originated from Fick’s second law in cylindrical coordinates. The final formulation was a discrete model with infinite terms. The developed model was applied to the data of Phase I water vapor diffusion tests performed on two types of asphalt mixtures at 20 °C using the Gravimetric Sorption Device. The initial relative humidity (RH) inside the test specimen was approximately 0% since the measuring cell where the specimen was placed was pre-vacuumed. The RH outside of the specimen was maintained at 51.51% throughout the test. The weight of the specimen was continuously measured to determine the mass of water molecules diffused into the specimen at different diffusion time points. The test data of every replicate specimen were fitted using the first 36 terms retained in the developed 3-D diffusion model in order to reduce computational efforts. A satisfied level of goodness of model fit was achieved with an R2 value larger than 0.97. The model parameters were determined during model fitting, including the diffusivities of the Phase I water vapor diffusion in asphalt mixtures and the moisture retention capability of each specimen per unit mass. These determined parameters of the hot mix asphalt specimens (HMA) were significantly larger than those of the fine aggregate mixture specimens, which should be attributed to the larger air void contents of the HMA specimens.

This article proposes a novel sodium dodecylbenzenesulfonate (SDBS)-assisted equilibrium adsorption method for preparing highly dispersed Ni/Al2O3 and Fe-promoted NiFe/Al2O3 thioetherification catalysts. The proposed strategy anchors nickel cations onto the electronegative surface of an Al2O3 support modified by negatively charged DBS− bilayers. As a result, this method achieves highly dispersed Ni nanoparticles without strengthening the metal-support interaction, promoting the reducibility and sulfurization of the supported Ni species. The as-prepared Ni-based catalysts have a smaller size, a higher dispersion of metal nanoparticles, and a greater amount of active metal sulfides than their counterparts prepared by the conventional impregnation method, endowing them with excellent catalytic performance for the highly selective removal of mercaptans. This method provides a new opportunity to prepare highly dispersed metal nanoparticles without a strong metal-support interaction.

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

The rapid development of portable electronic devices has accelerated the advancement of energy storage devices. On-chip microsupercapacitors (MSCs), as a group of high performance energy storage devices, have remarkable features of miniaturization, high security, and easy integration to build an all-in-one integrated system to meet the request of micro-portable electronic equipments. With the characteristics of high capacities, environmentally friendly and low cost, metal oxides are thought to be ideal candidates for on-chip MSCs. This paper summarizes the recent progress of metal oxides based on-chip MSCs. It starts with the introduction of several common methods for the synthesis of metal oxides nanostructures. The recent developments on the fabrication and electrochemical performance of metal oxides based on-chip MSCs are then highlighted in detail. Finally, the existing challenges and future perspectives of the on-chip MSCs are discussed.

As a two dimensional (2D) visible-light-responsive semiconductor photocatalyst, the photoreactivity of Bi2WO6 is not high enough for practical application owing to its limited response to visible light and rapid recombination of photogenerated electron-hole pairs. In this paper, 2D core-shell structured Bi2WO6@Bi2S3 nanoplates were prepared by calcination of a mixture of Bi2WO6 (1.3 g) and a certain amount of Na2S·9H2O (0–3.0 g) at 350 °C for 2 h. The reactivity of the resulting photocatalyst materials was evaluated by photocatalytic degradation of Brilliant Red X-3B (X3B), an anionic dye, under visible light irradiation (λ > 420 nm). As the amount of Na2S·9H2O was increased from 0 to 1.5 g, the degradation rate constant of X3B sharply increased from 0.40 × 10−3 to 6.6 × 10−3 min−1. The enhanced photocatalytic activity of Bi2WO6@Bi2S3 was attributed to the photosensitization of Bi2S3, which greatly extended the light-responsive range from the visible to the NIR, and the formation of a heterojunction, which retarded the recombination rate of photogenerated electron-hole pairs. However, further increases in the amount of Na2S·9H2O (from 1.5 to 3.0 g) resulted in a decrease of the photocatalytic activity of the Bi2WO6@Bi2S3 nanoplates owing to the formation of a photo-inactive NaBiS2 layer covering the Bi2WO6 surface.

Water vapor diffusion in a newly constructed asphalt pavement consists of water vapor accumulating toward the asphalt layer (Phase I) and water vapor passing through the asphalt layer (Phase II). The water vapor diffusion in Phase I under different relative humidity (RH) differentials has been investigated and can be found elsewhere in literature. However, it remains unclear whether the RH differential would affect the diffusion flux and diffusivity of the water vapor passing through the asphalt layer in Phase II. This study investigated the Phase II water vapor diffusion in asphalt mixtures under a variety of RH differentials. Experimental setups were designed and assembled for the Phase II water vapor diffusion experiments. Distilled water, saturated MgCl2 solution, saturated NaBr solution, and saturated KCl solution were stored in containers to provide the RH level of 100%, 36.5%, 62%, and 87%, respectively, under the asphalt mixture specimens that were sealed on top of these containers. The experimental setups were conditioned in environmental chambers to maintain a constant test temperature of 20 ± 0.5 °C and specific RH levels to establish the RH differentials between the air above and below the asphalt mixture specimen. The weight loss of the experimental setup was monitored three times a day using a high-precision scale. A linear relationship was identified between the RH differential and the diffusion flux of the water vapor in Phase II diffusion, which demonstrated that the Phase II water vapor diffusion followed Fick’s first law of diffusion. The calculated water vapor diffusivities in Phase II diffusion were significantly larger than those in Phase I diffusion and were independent of the variation of the RH differential between the air above and below the asphalt mixture specimen.

Activated carbon (AC) has been widely used for water purification. However, the microorganisms attached on the AC can result in microorganism secondary contamination in the purification process. Therefore, antimicrobial AC is being developed as a promising solution. In this paper, ZnO embedded activated carbon (ZnO-AC) is synthesized with an excellent antimicrobial property. The ZnO-AC is prepared using low cost and commercially available zinc oxide powder and granular AC. ZnO is embedded in-situ on the AC through a fast and simple immersion and heating process. EDX mapping and XPS spectra showed that ZnO was evenly embedded on AC. While the ZnO-AC had relatively low level of zinc concentration of 0.593 mg/g, it achieved a high reduction ratio of 99.99% towards E. Coli. To demonstrate the robust antimicrobial property of the ZnO-AC, tap water is applied for flushing. Results showed that ZnO-AC was able to reduce 91.18% of the E. Coli even after 500 L water flushing. Meanwhile, zinc leaching analysis demonstrated that ZnO-AC is safe to be used. Thus, the prepared ZnO-AC provided a promising solution in water purification industry.

This article proposes a novel decamethonium bromide-assisted method for modulating the size of supported metal nanoparticles in Pd/mesoporous HZSM-5 hydrodesulfurization (HDS) catalysts. The proposed approach significantly promotes the dispersion of supported palladium nanoparticles by bridging and anchoring the palladium precursor onto the surface of mesoporous HZSM-5 as well as restraining the subsequent aggregation of palladium nanoparticles in calcination. The as-prepared catalyst possessed higher 4,6-dimethyldibenzothiophene HDS activity than its counterpart that was prepared via impregnation due to its smaller Pd nanoparticles, higher Pd dispersion and higher content of Pd 0 species. This strategy provides a simple pathway for preparing supported metal nanoparticles with high dispersion.

This work overcomes the limitations in room-temperature and moisture-dependent activity of transition metal oxide-based catalysts for sub-ppm formaldehyde removal. The active site exposure and self-assembly hydrophilicity were highlighted in MnOx–CeO2 (MCO) nanospheres after the loading of colloidal 2.1 wt% TiO2 particles (TO–MCO). Approximately 57% (relative humidity = 72%) and 41% (dry air) recycling catalytic activities at 35 °C were achieved. Our results proved that surface electron transfer, which was previously weakened because of the loss of surface oxygen species and unsuitable defect-site depositions of low active ions, in the MCO catalyst was recovered via the dispersion of hydrophilic Ti–O groups. This electron transfer was also strongly correlated with the specific surface area, porosity, and oxidation states of transition metals. The greater active site exposure derived from the cyclic electron transfer eventually enhanced the HCHO chemisorption and participation of oxygen species on the surface of TO–MCO throughout the bimetallic (Mn–Ce) dismutation reactions. The abundant superoxide radicals that were activated by these oxygen species prompted a nucleophilic attack on carbonyl bonds. Direct photoionization mass spectrometry determined formic acid, dioxirane (minor), and HOCH2OOH (little) as intermediates governing the HCHO selectivity to CO2. The cytotoxicity of catalysts exposed to yeast cells was evaluated for their potential environmentally friendly application indoors.

This investigation offers new understanding regarding the nature of CoMoS and MoS2 active phases coexisting on sulfided CoMo/Al2O3 catalysts for the selective hydrodesulfurization (HDS) of gasoline. Two series of the CoMo/Al2O3 catalysts with different ethylenediaminetetraacetic acid (EDTA)/Co molar ratios and the EDTA-containing CoMo/Al2O3 catalysts with different cobalt contents were prepared, and the properties of their active metal phases were systematically correlated with their HDS selectivities. It was found that a high concentration of CoMoS phases improves the HDS activity of the sulfided CoMo/Al2O3 catalysts but that a high concentration of MoS2 phases enhances the olefin hydrogenation (OHYD) activity of these catalysts. From the perspective of microstructure, it was evident that the thiophene HDS reaction occurs primarily at the edge of CoMoS active phases and that the OHYD reaction occurs mainly at the corner of MoS2 active phases. These understandings shed light on the development of highly selective HDS catalysts.

Cyber physical systems (CPSs) are rapidly developing, with increasing scale, complexity, and heterogeneity. However, testing CPSs systematically to ensure that they operate with high reliability remains a big challenge. Therefore, it is necessary to summarize existing works and technologies systematically, with the aim of inspiring new inventions for more efficient CPS testing. Accordingly, this paper first investigated the advances in CPS testing methods from ten aspects, including different testing paradigms, technologies, and some non-functional testing methods (including security testing, robust testing, and fragility testing). Then, we further elaborate on the infrastructures of CPS testbeds from the perspectives of their architecture and the corresponding function analyses. Finally, challenges and future research directions are identified and discussed. It can be concluded that future CPS testing should focus more on the combination of different paradigms and technologies for multi-objective by integrating more emerging cutting-edge technologies such as Internet of things, big data, cloud computing, and AI.