A method for detecting abnormal behavior of ships based on multi-dimensional density distance and an abnormal isolation mechanism.

Abnormal ship behavior detection is essential for maritime navigation safety. Most existing abnormal ship behavior detection methods only build A ship trajectory position outlier detection model; however, the construction of a ship speed outlier detection model is also significant for maritime navigation safety. In addition, in most existing methods for detecting a ship's abnormal behavior based on abnormal thresholds, one unsuitable threshold leads to the risk of the ship not being minimized as much as possible. In this paper, we proposed an abnormal ship behavior detection method based on distance measurement and an isolation mechanism. First, to address the problem of traditional trajectory compression methods and density clustering methods only using ship position information, the minimum description length principle based on acceleration (AMDL) algorithm and Multi-Dimensional Density Clustering (MDDBSCAN) algorithm is used in this study. These algorithms not only considered the position information of the ship, but also the speed information. Second, regarding the issue of the difficulty in determining the anomaly threshold, one method for determining the anomaly threshold based on the relationship between the velocity weights and noise points of the MDDBSCAN algorithm has been introduced. Finally, due to the randomness issue of the selected segmentation value in iForest, a strategy of selectively constructing isolated trees was proposed, thus further improving the efficiency of abnormal ship behavior detection. The experimental results on the historical automatic identification system data set of Xiamen port prove the practicality and effectiveness of our proposed method. Our experiment results show that the proposed method achieves an improvement of about 10% over the trajectory outlier detection based on the local outlier fraction method, about 14% over the isolation-based online anomalous trajectory method in terms of the accuracy of ship position information anomaly detection, and about 3% over the feature fusion method in terms of the accuracy of ship speed anomaly detection. This method improves algorithm efficiency by about 5% compared to the traditional isolation forest anomaly detection algorithm.

Mixed reality drills of indoor earthquake safety considering seismic damage of nonstructural components.

The damaged indoor nonstructural components in the earthquake often cause casualties. To improve the indoor earthquake safety capacity of occupants, a mixed reality (MR) drill method for indoor earthquake safety considering seismic damage of nonstructural components is proposed. First, an MR device, HoloLens, is used to capture indoor point clouds, and the indoor three-dimensional scene is reconstructed using point clouds. Subsequently, the seismic motion models of indoor components are established, so that the indoor nonstructural seismic damage scene is constructed using the physics engine and displayed using HoloLens. Finally, a guidance algorithm for a safe zone was designed for the drills. Taking a typical office as an example, an indoor earthquake safety drill was performed. The drill results show that the proposed MR method can increase the average efficiency of moving to a safe zone by 43.1%. Therefore, the outcome of this study can effectively improve the earthquake safety ability of occupants, thereby reducing casualties.

Overview of predictive maintenance based on digital twin technology.

The upgrade and development of manufacturing industry makes predictive maintenance more and more important, but the traditional predictive maintenance can not meet the development needs in many cases. In recent years, predictive maintenance based on digital twin has become a research hotspot in the manufacturing industry field. Firstly, this paper introduces the general methods of digital twin technology and predictive maintenance technology, analyzes the gap between them, and points out the importance of using digital twin technology to realize predictive maintenance. Secondly, this paper introduces the predictive maintenance method based on digital twin (PdMDT), introduces its characteristics, and gives its differences from traditional predictive maintenance. Thirdly, this paper introduces the application of this method in intelligent manufacturing, power industry, construction industry, aerospace industry, shipbuilding industry, and summarizes the latest development in these fields. Finally, the PdMDT puts forwards a reference framework in manufacturing industry, the framework describes the specific implementation process of equipment maintenance, and gives an example of industrial robot using the framework, and discusses the limitations, challenges and opportunities of the PdMDT.

Kinetic Promotion Effect of Hydrogen and Dimethyl Disulfide Addition on Propane Dehydrogenation over the Pt-Sn-K/Al2O3 Catalyst.

The kinetic effects of co-feeding of dimethyl disulfide (DMDS) and hydrogen on propane dehydrogenation (PDH) over the Pt-Sn-K/Al2O3 catalyst were investigated by the response surface method. The 3-level Box-Behnken design for 4 factors (reaction temperature, propene, hydrogen, and DMDS flow rate) was used to design the experiment. The initial propane conversion, propene selectivity, and coking amount were chosen as responses and the results were fitted by quadratic models. The fresh and coked catalysts were characterized by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS), thermogravimetry (TG), N2 physisorption, and Fourier-transform infrared spectroscopy (FT-IR). Analysis of variance (ANOVA) results showed that the DMDS flow rate is significant for propane conversion and coking amount while hydrogen flow rate is only significant for the conversion. By using the fitted model for the response surface, it is found that DMDS can significantly reduce the coking amount at the expense of propane conversion, and hydrogen weakly affects the selectivity and coking amount. The optimal conditions to achieve maximum conversion and selectivity and minimum coking amount are not consistent. The DMDS and hydrogen flow rate should be optimized to obtain the maximum economic profit out of the propane dehydrogenation (PDH) process.

Mechanistic insights into acid-affected hydrogenolysis of glycerol to 1,3-propanediol over an Ir-Re/SiO2 catalyst.

Glycerol hydrogenolysis to 1,3-propanediol is identified to follow the dehydration-hydrogenation pathway with the rate-determining step (RDS) of H* + OH* → H2O* over an IrRe catalyst. The positive effects of solid acids are elucidated to originate from the reduced energy barrier of the RDS by H protons, while the negative ones of liquid acids are from excessively strong adsorption of anions.

C-H bond activation in light alkanes: a theoretical perspective.

Alkanes are the major constituents of natural gas and crude oil, the feedstocks for the chemical industry. The efficient and selective activation of C-H bonds can convert abundant and low-cost hydrocarbon feedstocks into value-added products. Due to the increasing global demand for light alkenes and their corresponding polymers as well as synthesis gas and hydrogen production, C-H bond activation of light alkanes has attracted widespread attention. A theoretical understanding of C-H bond activation in light hydrocarbons via density functional theory (DFT) and microkinetic modeling provides a feasible approach to gain insight into the process and guidelines for designing more efficient catalysts to promote light alkane transformation. This review describes the recent progress in computational catalysis that has addressed the C-H bond activation of light alkanes. We start with direct and oxidative C-H bond activation of methane, with emphasis placed on kinetic and mechanistic insights obtained from DFT assisted microkinetic analysis into steam and dry reforming, and the partial oxidation dependence on metal/oxide surfaces and nanoparticle size. Direct and oxidative activation of the C-H bond of ethane and propane on various metal and oxide surfaces are subsequently reviewed, including the elucidation of active sites, intriguing mechanisms, microkinetic modeling, and electronic features of the ethane and propane conversion processes with a focus on suppressing the side reaction and coke formation. The main target of this review is to give fundamental insight into C-H bond activation of light alkanes, which can provide useful guidance for the optimization of catalysts in future research.

Synthesis of nitrogen and sulfur doped graphene on graphite foam for electro-catalytic phenol degradation and water splitting.

A rational design of electrode materials with both high electron conductivity and abundant of catalytic sites is essential for high-performance electrochemical reactions. Herein, a nitrogen and sulfur co-doped graphene (SNG) anchored on the interconnected conductive graphite foam (GF) is fabricated via drop-casting and in situ annealing. The SNG flakes are tightly immobilized on the GF surface, which can provide fast electron transfer rate and large electrolyte/electrode interfaces. The SNG@GF composite can be directly used as a free-standing electrode for electro-catalytic degradation of organic pollutants and overall water splitting. SNG@GF significantly enhanced the electrochemical activation of peroxymonosulfate (PMS) for catalytic oxidation. During the oxygen evolution reaction (OER), the SNG@GF exhibits an initial overpotential of 330 mV vs. RHE at 10 mA cm-2 with a Tafel slope of 149 mV dec-1 in 1 M KOH, which outperforms most of the reported metal-free catalysts. The density functional theory calculations are also used to unveil the S, N dual doping effects of carbon materials and their synergy in carbocatalysis. This study dedicates to developing multi-functional carbocatalysts for environmental and energy applications, and enables insights into carbocatalysis in electrochemistry.

Bi-reforming of methane with steam and CO2 under pressurized conditions on a durable Ir-Ni/MgAl2O4 catalyst.

High pressure reforming of methane is critical for process economics, but imposes increased risk of catalyst coke deposition. Herein, a coke- and sintering-resistant Ir-Ni alloy catalyst is presented, which is durable in methane bi-reforming at 850 °C and 20 bars for up to 434 h.

Towards rational catalyst design: boosting the rapid prediction of transition-metal activity by improved scaling relations.

Understanding the scaling relations of adsorption energies and activation energies greatly facilitates the computational catalyst design. To reduce the computational cost and guarantee efficiency, improved scaling relations were advocated in this study to rapidly acquire the energetics for transition metal surface reactions and further to rapidly and effectively map the activity of transition-metal catalysts. The overall catalytic activity for the surface reactions between C-, H- and O-containing species could be related to their adsorption energies using C, H and O binding energies as descriptors via improved scaling relations. The UBI-QEP (unity bond index-quadratic exponential potential) method, one of the scaling relations used to estimate the adsorption energies from descriptors, was significantly improved by taking into account the changes in the A-B bond indexes during adsorption and the molecular structure of adsorbed species using density functional theory (DFT) data as a benchmark. The improved UBI-QEP approach could satisfactorily predict the DFT (BEEF-vdW) and experimental adsorption energies. DFT calculations with the BEEF-vdW functional were also employed for establishing the BEP (Brønsted-Evans-Polanyi) relationships as scaling relations to correlate the reaction heats with activation energies for C-H, C-O, C-C, and O-H bond cleavages and recombination. The capability of the improved UBI-QEP+BEP approach was tested as a generic framework to map the activity trend for steam methane reforming (a probe reaction) through microkinetic modeling. The results demonstrated that our approach reduces the computational cost by six orders of magnitude while maintaining a reasonable degree of accuracy as compared to the DFT (BEEF-vdW) and experimental approaches.

Surface phase diagrams of La-based perovskites towards the O-rich limit from first principles.

The exposed termination of transition-metal oxide surfaces plays a major role in determining the catalyst performance in redox reactions. In this contribution, the surface phase diagrams of LaMO3(001) (M = Sc-Fe) and LaMO3(110) (M = Co-Cu) are constructed by using the DFT+U method. The stabilities of six terminations derived from the stoichiometric MO2 and LaO surfaces are determined over a wide range of temperatures and oxygen partial pressures. The surface phase diagrams are calculated towards the O-rich limit in which the chemical potential of oxygen anions of perovskites equals that of gas-phase oxygen while the chemical potential of M cations is limited by thermodynamic boundary conditions. It is found that the surface phase diagrams are closely related to the reducibility of M cations, which is reflected in the oxygen adsorption energy and oxygen vacancy formation energy on the MO2- and LaO-terminated surfaces and can be measured by the third ionization energies of the M2+ cations. According to the surface phase diagrams, the most stable surface termination is predicted to be of MO2 type for LaMO3 (M = Sc-Fe) and LaO type for LaMO3 (M = Co-Cu) under solid oxide fuel cell operating conditions. Because the M cations become more readily reduced on going from left to right across the period, LaCoO3 may form an oxygen-deficient crystal structure at high temperatures and LaNiO3 and LaCuO3 would be decomposed into oxides containing the transition metals in a lower oxidation state.

Insights into Hydrogen Transport Behavior on Perovskite Surfaces: Transition from the Grotthuss Mechanism to the Vehicle Mechanism.

Hydrogen transport on transition-metal oxides is a shared process in many important physical and chemical changes of interest. In this work, DFT + U calculations have been carried out to explore the mechanism for hydrogen migration on the defect-free and oxygen-deficient LaMO3(001) (M = Cr, Mn, and Fe) surfaces. The calculated results indicate that hydrogen is preferentially adsorbed at the oxygen sites on all surfaces other than the defective LaCrO3(001), where the occupation of vacancies is energetically most favorable. The resultant O-H bonds would be weakened when oxygen vacancies are formed in their immediate vicinity because the increased electron density on the remaining ions would limit the ability of O to withdraw electrons from H. On defect-free LaMO3(001), hydrogen prefers to migrate along the [010] axis, during which the O-H bond is reoriented at the oxygen site for the hopping to proceed by the Grotthuss mechanism. In the presence of oxygen vacancies, the vehicle mechanism in which hydrogen hops together with the underlying oxygen would dominate on LaMnO3 and LaFeO3, whereas on the defective LaCrO3(001) the Grotthuss mechanism prevails. The linear scaling relations established show that the hydrogen and hydroxyl migration barriers decrease and increase, respectively, with increasing the strength of ionic bonding in perovskites, which provides a rational interpretation of the change in the preferred hydrogen migration mechanism.

Sub-5 nm Ultra-Fine FeP Nanodots as Efficient Co-Catalysts Modified Porous g-C3N4 for Precious-Metal-Free Photocatalytic Hydrogen Evolution under Visible Light.

Sub-5 nm ultra-fine iron phosphide (FeP) nano-dots-modified porous graphitic carbon nitride (g-C3N4) heterojunction nanostructures are successfully prepared through the gas-phase phosphorization of Fe3O4/g-C3N4 nanocomposites. The incorporation of zero-dimensional (0D) ultra-small FeP nanodots co-catalysts not only effectively facilitate charge separation but also serve as reaction active sites for hydrogen (H2) evolution. Herein, the strongly coupled FeP/g-C3N4 hybrid systems are employed as precious-metal-free photocatalysts for H2 production under visible-light irradiation. The optimized FeP/g-C3N4 sample displays a maximum H2 evolution rate of 177.9 µmol h-1 g-1 with the apparent quantum yield of 1.57% at 420 nm. Furthermore, the mechanism of photocatalytic H2 evolution using 0D/2D FeP/g-C3N4 heterojunction interfaces is systematically corroborated by steady-state photoluminescence (PL), time-resolved PL spectroscopy, and photoelectrochemical results. Additionally, an increased donor density in FeP/g-C3N4 is evidenced from the Mott-Schottky analysis in comparison with that of parent g-C3N4, signifying the enhancement of electrical conductivity and charge transport owing to the emerging role of FeP. The density functional theory calculations reveal that the FeP/g-C3N4 hybrids could act as a promising catalyst for the H2 evolution reaction. Overall, this work not only paves a new path in the engineering of monodispersed FeP-decorated g-C3N4 0D/2D robust nanoarchitectures but also elucidates potential insights for the utilization of noble-metal-free FeP nanodots as remarkable co-catalysts for superior photocatalytic H2 evolution.

BEEF-vdW+U method applied to perovskites: thermodynamic, structural, electronic, and magnetic properties.

The recently developed BEEF-vdW exchange-correlation method provides a reasonably reliable description of both long-range van der Waals interactions and short-range covalent bonding between molecules and surfaces. However, this method still suffers from the excessive electron delocalization that is connected with the self-interaction error and, consequently, the calculated chemical and physical properties such as formation energy and band gap deviate markedly from the experimental values, especially when strongly correlated systems are under investigation. In this contribution, BEEF-vdW+U calculations have been performed to study the thermodynamic, structural, electronic, and magnetic properties of La-based perovskites. An effective interaction parameter [Formula: see text] and an energy adjustment [Formula: see text] are determined simultaneously by a mixing GGA and GGA+U method, where the enthalpy or Gibbs free energy of formation of oxides containing a transition metal in different oxidation states are fitted to available experimental data. The [Formula: see text] is found to have its origin in the fact that the GGA+U method gives rise to the offsets in the total energy that include not only the desired physical correction but also an arbitrary contribution. Calculated results indicate that the BEEF-vdW method provides a more accurate description of the bonding in the O2 molecule than the PBE method and has generally smaller [Formula: see text] values for the 3d-block transition metals, thereby giving rise to band gaps and magnetic moments that are in better agreement with the experimentally measured values.

Boosting Size-Selective Hydrogen Combustion in the Presence of Propene Using Controllable Metal Clusters Encapsulated in Zeolite.

A strategy is presented for making metal clusters encapsulated inside microporous solids selectively accessible to reactant molecules by manipulating molecular sieve size and affinity for adsorbed molecules. This expands the catalytic capabilities of these materials to reactions demanding high selectivity and stability. Selective hydrogen combustion was achieved over Pt clusters encapsulated in LTA zeolite (KA, NaA, CaA) in a propene-rich mixture obtained from propane dehydrogenation, showing pore-size dependent selectivity and coking rate. Propene tended to adsorb at channels or external surfaces of zeolite, interfering the diffusion of hydrogen and oxygen. Tailoring the surface of LTA zeolite with additional alkali or alkaline earth oxides contributed to narrowing zeolite pore size and their affinity for propene. The thus-modified Pt@KA catalyst displayed excellent hydrogen combustion selectivity (98.5 %) with high activity and superior anti-coking and anti-sintering properties.

Decoding structural complexity in conical carbon nanofibers.

Conical carbon nanofibers (CNFs) exist primarily as graphitic ribbons that fold into a cylindrical structure with the formation of a hollow core. Structural analysis aided by molecular modeling proves useful for obtaining a full picture of how the size of the central channel varies from fiber to fiber. From a geometrical perspective, conical CNFs possibly have cone tips that are nearly closed. On the other hand, their fiber wall thickness can be reduced to a minimum possible value that is determined solely by the apex angle, regardless of the outer diameter. A formula has been developed to express the number of carbon atoms present in conical CNFs in terms of measurable structural parameters. It appears that the energetically preferred fiber wall thickness increases not only with the apex angle, but also with the number of atoms in the constituent graphitic cones. The origin of the empirical observation that conical CNFs with small apex angles tend to have a large hollow core lies in the fact that in graphene sheets that are more highly curved the curvature-induced strain energy rises more rapidly as the fiber wall thickens.

Short- and Long-Term Tracking of Anionic Ultrasmall Nanoparticles in Kidney.

While biodistribution of nanoparticles (NPs) has been widely studied at the organ level, relatively little is known about their disposition in organs at the cellular level, especially after long-term exposure. The kidney is regarded as the key organ for the clearance of ultrasmall NPs (<5.5 nm). However, recent studies indicate that NPs in this size range could accumulate in the kidney for extended times without urinary excretion. Using negatively charged quantum dots (QDs) (∼3.7 nm) as a model system, we examined the suborgan disposition of anionic ultrasmall NPs in the kidney at the cellular level after intravenous injection by multiphoton microscopy coupled with fluorescence lifetime imaging. Most of the NPs were initially distributed in the peritubular capillaries or glomerular arterioles after injection, whereas they passed through the fenestrated glomerular endothelium and were gradually taken up by mesangial cells up to 30 days after injection. Only trace amounts of anionic QDs could be detected in the urine, which could be attributed to the barrier of the anionic glomerular basement membrane preventing filtration of anionic QDs. In contrast, cationic QDs of similar size (∼5.67 nm) were found to be readily excreted into urine. This study thus highlights the importance of surface charge in determining renal clearance of ultrasmall NPs. It provides a framework for characterizing and predicting the subcellular disposition in organs and long-term targeting of other NPs, with a physiologically based kinetic model being subsequently developed to describe the suborgan kinetics of anionic ultrasmall NPs.

Chelator-Free Labeling of Layered Double Hydroxide Nanoparticles for in Vivo PET Imaging.

Layered double hydroxide (LDH) nanomaterial has emerged as a novel delivery agent for biomedical applications due to its unique structure and properties. However, in vivo positron emission tomography (PET) imaging with LDH nanoparticles has not been achieved. The aim of this study is to explore chelator-free labeling of LDH nanoparticles with radioisotopes for in vivo PET imaging. Bivalent cation (64)Cu(2+) and trivalent cation (44)Sc(3+) were found to readily label LDH nanoparticles with excellent labeling efficiency and stability, whereas tetravalent cation (89)Zr(4+) could not label LDH since it does not fit into the LDH crystal structure. PET imaging shows that prominent tumor uptake was achieved in 4T1 breast cancer with (64)Cu-LDH-BSA via passive targeting alone (7.7 ± 0.1%ID/g at 16 h post-injection; n = 3). These results support that LDH is a versatile platform that can be labeled with various bivalent and trivalent radiometals without comprising the native properties, highly desirable for PET image-guided drug delivery.

Diagnostic imaging and therapeutic application of nanoparticles targeting the liver.

Liver diseases, particularly viral hepatitis, cirrhosis and hepatocellular carcinoma, are common in clinical practice with high morbidity and mortality worldwide. Many substances for diagnostic imaging and therapy of liver diseases may have either severe adverse effects or insufficient effectiveness in vivo because of their nonspecific uptake. Therefore, by targeting the delivery of drugs into the liver or specific liver cells, drug efficiency may be largely improved. This review summarizes the up-to-date research progress focusing on nanoparticles targeting the liver for both diagnostic and therapeutic purposes. Targeting strategies, mechanisms of enhanced effects, and clinical applications of nanoparticles are discussed specifically. We believe that new targeting nanotechnology such as nanoprobes for multi-modality imaging and multifunctional nanoparticles would facilitate significant advancements in this active research area in the near future.

Intravital multiphoton imaging of the selective uptake of water-dispersible quantum dots into sinusoidal liver cells.

Although many studies reporting the organ-level biodistribution of nanoparticles (NPs) in animals, very few have addressed the fate of NPs in organs at the cellular level. The liver appears to be the main organ for accumulation of NPs after intravenous injection. In this study, for the first time, the in vivo spatiotemporal disposition of recently developed mercaptosuccinic acid (MSA)-capped cadmium telluride/cadmium sulfide (CdTe/CdS) quantum dots (QDs) is explored in rat liver using multiphoton microscopy (MPM) coupled with fluorescence lifetime imaging (FLIM), with subcellular resolution (∼1 µm). With high fluorescence efficiency and largely improved stability in the biological environment, these QDs show a distinct distribution pattern in the liver compared to organic dyes, rhodamine 123 and fluorescein. After intravenous injection, fluorescent molecules are taken up by hepatocytes and excreted into the bile, while negatively charged QDs are retained in the sinusoids and selectively taken up by sinusoidal cells (Kupffer cells and liver sinusoidal endothelial cells), but not by hepatocytes within 3 h. The results could help design NPs targeting the specific types of liver cells and choose the fluorescent markers for appropriate cellular imaging.

Structural and electronic properties of the Pt(n)-PAH complex (n = 1, 2) from density functional calculations.

A detailed density functional study of the Pt atom and the Pt dimer adsorption on a polyaromatic hydrocarbon (PAH) is presented. The preferred adsorption site for a Pt atom is confirmed to be the bridge site. Upon adsorption of a single Pt atom, however, it is found here that the electronic ground state changes from the triplet state (5d(9)6s(1) configuration) to the closed-shell singlet state (5d(10)6s(0) configuration), which consequently will affect the catalytic activity of Pt when single Pt atoms bind to a carbon surface. The preferred adsorption site for the Pt dimer in the upright configuration is the hollow site. In contrast to the adsorption of a single Pt atom, the formation of a Pt-C bond in the adsorption of a Pt dimer is not accompanied by a change in the spin state, so the most stable electronic state is still the triplet state. While the atomic charge on the Pt atoms and dimers (in parallel configuration) in the Ptn-PAH complex is positive, a negative charge is found on the upper Pt atom for the upright configuration, indicating that single layers of Pt atoms will have a different catalytic activity as compared to Pt clusters on a carbon surface. Comparing the Pt-C bond length and the charge transfer on different sites, the magnitude of the charge transfer decreases with bond elongation, indicating that the catalytic activity of the Pt atom and dimer can be changed by modifying its chemical surroundings. The adsorption energy for the Pt dimer on a PAH surface is larger than that for two individual Pt atoms on the surface indicating that aggregation of Pt atoms on the PAH surface is favorable.