Microwave‐Assisted Synthesis of Ethyl 1,3‐Disubstituted‐1,6‐dihydropyrrolo[2,3‐c]pyrazole‐5‐carboxylates

A novel series of ethyl 1,3‐disubstituted‐1,6‐dihydropyrrolo[2,3‐c]pyrazole‐5‐carboxylates can be rapidly and efficiently synthesized in excellent yields by condensing a variety of 1,3‐substituted‐4‐formyl‐5‐chloropyrazole with ethyl isocyanoacetate in the presence of 1‐methyl‐3‐butylimidazolium hydroxide under microwave irradiation. The simple experimental procedure, DMSO‐free condition, short period of conversion, and excellent yields are the advantages of the present method. The structures of the novel compounds are confirmed by IR, ¹H NMR, ¹³C NMR, MALDI‐TOF MS, and elemental analysis.     

Syngas production from methane over CeO2-Fe2O3 mixed oxides using a chemical-looping method

A series of mixed oxides Ce_{1 ? x} Fe _x O₂ was prepared by a hydrothermal method. XRD and Raman spectra were measured to study the structure of the prepared materials. The temperature-programmed reduction was undertaken to estimate reducibility of the oxides. Syngas generation from methane using these materials as oxygen carriers/catalysts via a chemical-looping procedure was investigated in detail. This procedure includes catalytic oxidation and decomposition of methane to produce H₂-rich gas at the first step followed by the production of the CO-rich gas by oxidizing the carbon deposited on deactivated catalysts. The results showed that all iron ions were incorporated into the ceria lattice with the formation of oxygen vacancies in the Ce_0.9Fe_0.1O₂ sample, while isolated Fe₂O₃ particles were distributed on the surface of the Ce_0.8Fe_0.2O₂ sample. TPR measurements and the analysis of the two-step chemical-looping reactions indicated a strong interaction between the Ce and Fe species which accounts for an increased activity of the mixed oxides in the syngas generation compared to that of individual oxides. Among the several samples, the Ce_0.8Fe_0.2O₂ catalyst showed the highest activity for methane partial oxidation due to the synergetic effects caused by the interaction of surface iron entities and Ce-Fe solid solution. In addition, selective oxidation of carbon by oxygen to CO can also be found over this material since gaseous products are formed at the carbon oxidation step with the selectivity to CO reaching 91.2%. Evidence is presented that syngas can be feasibly produced from methane with high selectivity via the chemical-looping procedure over the CeO₂-Fe₂O₃ mixed oxides.     

Selective recognition and electrochemical detection of p-nitrophenol based on a macroporous imprinted polymer containing gold nanoparticles

We have combined the molecular imprinting and the layer-by-layer assembly techniques to obtain molecularly imprint polymers (MIPs) for the electrochemical determination of p-nitrophenol (p-NPh). Silica microspheres functionalized with thiol groups and gold nanoparticles (Au-NPs) were assembled on a gold electrode surface layer by layer. The electrode was then immersed into a solution of pyrrole and p-NPh (the template), and electropolymerization led to the creation of a polymer-modified surface. After the removal of the silica spheres and the template, electrochemical impedance spectroscopy and differential pulse voltammetry (DPV) were employed to characterize the surface. The results demonstrated the successful fabrication of macroporous MIPs embedded with Au-NPs on the gold electrode. The effects of monomer concentration and scan rate on the performance of the electrode were optimized. Excellent recognition capacity is found for p-NPh over chemically similar species. The DPV peak current is linearly related to concentration of p-NPh in the 0.1 μM to 1.4 mM range, with a 0.1 μM limit of detection (at S/N?=?3).

Fast redox kinetics of a perovskite oxygen carrier measured using micro-fluidized bed thermogravimetric analysis

Redox kinetics of oxygen carrier in chemical looping combustion (CLC) is important for reactor design and its oxidation enthalpy is important in order to establish auto thermal demonstration. Most published redox kinetics of oxygen carrier has been measured by thermogravimetric analysis (TGA) which can include additional diffusion limitations and thus underestimate the overall kinetics. In this study, the redox kinetics of a new perovskite oxygen carrier (CaMn_0.375Ti_0.5Fe_0.125O_3-δ) was measured by a novel micro-fluidized bed thermogravimetric analysis (MFB-TGA) method which can achieve real-time weight measurement of oxygen carrier in a fluidizing state with similar mass and heat transfer characteristics as in a CLC reactor. The experimental data from MFB-TGA were analyzed with a reactor model. The redox kinetics was described by a two-stage model of gas-solid reaction. The effect of temperature, O₂ concentrations and reducing gas type (H₂ and CH₄) on the redox kinetics in MFB-TGA was investigated and compared with other oxygen carriers such as natural manganese ore and ilmenite. It is observed that the oxidation of both manganese ore and ilmenite can be divided into two stages, a fast initial stage followed by a second slower stage, resulting in slower total oxidation rates. A very interesting finding is that there is only the fast initial stage for the oxygen carrier of CaMn_0.375Ti_0.5Fe_0.125O_3-δ, and the full oxidation of CaMn_0.375Ti_0.5Fe_0.125O_3-δ can be finished within ～4 s which is ～7.5 and ～30 times faster than that of manganese ore and ilmenite. The reduction kinetics of CaMn_0.375Ti_0.5Fe_0.125O_3-δ by H₂ is also ～5 and ～2.2 times faster than that of manganese ore and ilmenite, respectively. The kinetic parameters of three oxygen carriers were compared and the redox mechanism of CaMn_0.375Ti_0.5Fe_0.125O_3-δ was discussed.     

Emissions of PM10 from the co-combustion of high-Ca pyrolyzed biochar and high-Si coal under air and oxyfuel atmosphere

The single or co-combustion experiments of high-Ca pyrolyzed biochar and high-Si coal were carried out on a drop tube furnace (DTF) at 1300 °C under air and oxyfuel (CO₂:O₂=50:50, oxy50) conditions. The produced PM₁₀ (of an aerodynamic diameter of 10 µm or less) was analyzed to investigate the interactions during co-combustion. Due to the characteristics of the selected samples (low S and Cl), the PM₁ emissions including PM_0.1 and PM_0.1–1 are very low during single combustion, except for the PM_0.1–1 emission during the combustion of biochar under oxy50 condition because of the massive partitioning of Mg, Ca and Fe. The interaction during co-combustion was observed to mainly occur in the generation of PM_1–10, and also slightly occur in the formation of PM_0.1–1 under oxy50 condition. The capture of Mg, Ca, and Fe from biochar by the Si-containing minerals in coal under the oxy50 condition results in a slight decrease in PM_0.1–1 during co-combustion. The higher the proportion of coal blended, the more obvious the reduction of elements. As for the formation of PM_1–10 during co-combustion, high-melting minerals of biochar would weaken the coalescence of minerals in coal to cause more PM₁₀, while the large mineral grains of coal would capture the minerals in biochar to generate more PM₁₀₊. Under the competition of the above two types of interactions, the experimental value of PM_1–10 yields was almost consistent with the theoretically calculated value, except for blended ratio of 80:20 (coal: biochar, air) or 50:50 (oxy50) with prior interaction predominating.     

Bioimaging agents based on redox-active transition metal complexes

Detecting the fluctuation and distribution of various bioactive species in biological systems is of great importance in determining diseases at their early stages. Metal complex-based probes have attracted considerable attention in bioimaging applications owing to their unique advantages, such as high luminescence, good photostability, large Stokes shifts, low toxicity, and good biocompatibility. In this review, we summarized the development of redox-active transition metal complex-based probes in recent five years with the metal ions of iron, manganese, and copper, which play essential roles in life and can avoid the introduction of exogenous metals into biological systems. The designing principles that afford these complexes with optical or magnetic resonance (MR) imaging properties are elucidated. The applications of the complexes for bioimaging applications of different bioactive species are demonstrated. The current challenges and potential future directions of these probes for applications in biological systems are also discussed.

This review summarizes transition metal complexes as bioimaging agents in optical and magnetic resonance imaging.     

Surface-Enhanced Raman Scattering of Hydrogen Plasma-Treated Few-Layer MoTe_2

Two-dimensional surface-enhanced Raman scattering(SERS) substrates have drawn intense attention due to their excellent spectral reproducibility, high uniformity and perfect anti-interference ability. However, the inferior detection sensitivity and low enhancement have limited the practical application of two-dimensional SERS substrates. To address this issue, we propose that the interaction between the MoTe_2 substrate and the analyte rhodamine 6 G molecules could be remarkably enhanced by the introduced p-doping effect and lattice distortion of MoTe_2 via hydrogen plasma treatment. After the treatment, the SERS is greatly improved, the enhancement factor of probe molecules reaches 1.83 × 10~6 as well as the limit of detection concentration reaches 10-13 M.This method is anticipated to afford new enhancement probability for other 2D materials, even non-metal oxide semiconductor SERS substrates.     

Subcomponent self-assembly of circular helical Dy6(L)6 and bipyramid Dy12(L)8 architectures directed via second-order template effects

In situ metal-templated (hydrazone) condensation also called subcomponent self-assembly of 4,6-dihydrazino-pyrimidine, o-vanillin and dysprosium ions resulted in the formation of discrete hexa- or dodecanuclear metallosupramolecular Dy₆(L)₆ or Dy₁₂(L)₈ aggregates resulting from second-order template effects of the base and the lanthanide counterions used in these processes. XRD analysis revealed unique circular helical or tetragonal bipyramid architectures in which the bis(hydrazone) ligand L adopts different conformations and shows remarkable differences in its mode of metal coordination. While a molecule of trimethylamine acts as a secondary template that fills the void of the Dy₆(L)₆ assembly, sodium ions take on this role for the formation of heterobimetallic Dy₁₂(L)₈ by occupying vacant coordination sites, thus demonstrating that these processes can be steered in different directions upon subtle changes of reaction conditions. Furthermore, Dy₆(L)₆ shows an interesting spin-relaxation energy barrier of 435 K, which is amongst the largest values within multinuclear lanthanide single-molecular magnets.

Subcomponent self-assembly gave access to Dy₁₂(L)₈ and Dy₆(L)₆ architectures via second-order template effects. The Dy₆(L)₆ assembly behaves as a single-molecule magnet exhibiting a high anisotropy barrier and butterfly-shaped magnetic hysteresis.     

A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability

The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of passenger flow distribution. Specifically, the existing methods have not been applied to practical large-scale subway networks due to the computational complexity. To fill this research gap, this paper analyzes the relationship between passenger travel behavior and train operation in the space and time dimension and formulates the passenger–train matching probability by using multi-source data including AFC, train timetables, and network topology. Then, a reverse derivation method, which can reduce the scale of possible train combinations for passengers, is proposed to improve the computational efficiency. Simultaneously, an estimation method of passenger flow distribution is presented based on the passenger–train matching probability. Finally, two sets of experiments, including an accuracy verification experiment based on synthetic data and a comparison experiment based on real data from the Beijing subway, are conducted to verify the effectiveness of the proposed method. The calculation results show that the proposed method has a good accuracy and computational efficiency for a large-scale subway network.     

AP Shadow Net: A Remote Sensing Shadow Removal Network Based on Atmospheric Transport and Poisson’s Equation

Shadow is one of the fundamental indicators of remote sensing image which could cause loss or interference of the target data. As a result, the detection and removal of shadow has already been the hotspot of current study because of the complicated background information. In the following passage, a model combining the Atmospheric Transport Model (hereinafter abbreviated as ATM) with the Poisson Equation, AP ShadowNet, is proposed for the shadow detection and removal of remote sensing images by unsupervised learning. This network based on a preprocessing network based on ATM, A Net, and a network based on the Poisson Equation, P Net. Firstly, corresponding mapping between shadow and unshaded area is generated by the ATM. The brightened image will then enter the Confrontation identification in the P Net. Lastly, the reconstructed image is optimized on color consistency and edge transition by Poisson Equation. At present, most shadow removal models based on neural networks are significantly data-driven. Fortunately, by the model in this passage, the unsupervised shadow detection and removal could be released from the data source restrictions from the remote sensing images themselves. By verifying the shadow removal on our model, the result shows a satisfying effect from a both qualitative and quantitative angle. From a qualitative point of view, our results have a prominent effect on tone consistency and removal of detailed shadows. From the quantitative point of view, we adopt the non-reference evaluation indicators: gradient structure similarity (NRSS) and Natural Image Quality Evaluator (NIQE). Combining various evaluation factors such as reasoning speed and memory occupation, it shows that it is outstanding among other current algorithms.